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A2090-719 Assessment: InfoSphere Warehouse V9.5-Assessment

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A2090-719 exam Dumps Source : Assessment: InfoSphere Warehouse V9.5-Assessment

Test Code : A2090-719
Test Name : Assessment: InfoSphere Warehouse V9.5-Assessment
Vendor Name : IBM
: 93 Real Questions

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IBM Assessment: InfoSphere Warehouse V9.5-Assessment

An introduction to facts great | killexams.com Real Questions and Pass4sure dumps

1. what's records first-rate?

there are lots of definitions of facts satisfactory, in regularly occurring, information first-class is the evaluation of how lots the records is usable and matches its serving context.

Many components helps measuring statistics first-rate similar to:

  • records Consistency: Violation of semantic guidelines described over the dataset. [1].
  • information Accuracy: facts are accurate when information values stored in the database correspond to precise-world values. [1]
  • information uniqueness: A measure of unwanted duplication present within or throughout techniques for a particular container, listing, or records set. [2]
  • records Completeness: The diploma to which values are existing in an information collection. [1]
  • facts Timeliness: The extent to which age of the data is appropriated for the assignment at hand. [3]
  • different components may also be taken into consideration [4] similar to Availability, Ease of Manipulation, Believability, and currency.

    2. Why records quality is crucial?

    improving the records exceptional is a vital problem as data is considered because the core of all activities within corporations, negative information high-quality results in inaccurate reporting in order to influence inaccurate decisions and certainly financial damages.

    3. how to enrich facts excellent?

    facts best growth is carried out by:

  • practicing body of workers
  • implementing records first-class solutions
  • three.1. training group of workers

    earlier than brooding about imposing records pleasant solutions, first they must lower the facts first-class complications resulted via in-firm human activities such as records entry. additionally all developers and database directors have to have a pretty good capabilities of the company method and must check with a unified schema when setting up and designing databases and purposes. [5]

    three.2. implementing information excellent solutions

    The wrong way to enrich facts great is by implementing information fine solutions. records nice options is a collection of equipment or application that operate pleasant projects such as:

  • skills base introduction: a knowledge base is a computing device-readable aid for the dissemination of advice. [6]
  • information de-duplication: eliminate duplicated tips based on a collection of semantic guidelines.
  • information cleaning: disposing of undesirable characters and symbols from values.
  • data profiling: is the method of examining the statistics purchasable from an latest suggestions supply (e.g. a database or a file) and gathering data or informative summaries about that statistics. [7]
  • statistics matching: facts matching describes efforts to examine two units of collected facts using technologies similar to listing Linkage and Entity decision. [8]
  • 4. prevalent statistics excellent options

    during this section, i will show one of the most most widely wide-spread information first-class options in the market.

    four.1. IBM Infosphere guidance server

    IBM InfoSphere® tips Server is a market-main statistics integration platform, which comprises a family of products that allow you to take note, cleanse, computer screen, transform and convey data, and to collaborate to bridge the gap between enterprise and IT. InfoSphere assistance Server offers hugely parallel processing (MPP) capabilities to deliver a enormously scalable and versatile integration platform that handles all facts volumes, big and small.

    InfoSphere counsel Server gives you with the capacity to flexibly meet your pleasing counsel integration requirements — from records integration to records nice and statistics governance — to bring depended on tips to your mission-important business initiatives (corresponding to large statistics and analytics, facts warehouse modernization, master records administration and point-of-influence analytics). [9]

    four.2. Informatica facts best

    Informatica records first-rate can provide faithful statistics to all stakeholders, projects, and statistics domains for all company functions on premise or within the cloud. [10]

    four.three. Oracle records high-quality

    Oracle commercial enterprise facts quality gives you an entire, premiere-of-breed strategy to birthday celebration and product information resulting in trustworthy master data that integrates with applications to enrich enterprise perception. [11]

    4.four. Microsoft statistics excellent services

    SQL Server records first-class features (DQS) is a knowledge-driven facts nice product. DQS enables you to build an information base and use it to function quite a lot of critical statistics high-quality initiatives, including correction, enrichment, standardization, and de-duplication of your information. DQS enables you to operate information cleaning through the use of cloud-based reference facts capabilities provided through reference statistics providers. DQS additionally offers you with profiling it truly is built-in into its records-exceptional tasks, enabling you to analyze the integrity of your facts. [12]

    four.5. Melissa data satisfactory

    considering 1985, Melissa has been featuring commercial enterprise information nice equipment with large capabilities together with data profiling and standardization, cleaning, enriching, linking and deduping. Their mission is to supply agencies with surest-of-breed solutions that bring trusted, legitimate, accurate guidance for enhanced perception. [10]

    four.6. Talend records quality

    Talend’s commercial enterprise records nice tool profiles, cleanses, and masks facts, while monitoring records fine over time, in any format or measurement. facts de-duplication, validation, and standardization creates clear facts for access, reporting, analytics, and operations. Enrich facts with exterior sources for postal validation, business identification, credit score ranking guidance, and extra. [13]

    4.7. Syncsort Trillium application Lead

    Syncsort’s Trillium Cloud supplies an business-main commercial enterprise facts nice solution with the deployment ease and operational flexibility of a Syncsort-administered hardened, relaxed colud ambiance. [14]

    4.eight. SAS facts fine

    The SAS information great utility makes it possible for you to increase the consistency and integrity of your facts. when you increase the pleasant of your records, you raise the cost of your analytical results.

    The SAS statistics satisfactory utility helps numerous facts first-class operations. The data quality operations employ predefined guidelines that apply to the specific context of your records (such as names or road addresses). Examples of statistics satisfactory operations include casing, parsing, fuzzy matching, and standardization. [15]

    5. References
  • [1] C. Batini, C. Cappiello, C. Francalanci, A. Maurino, “Methodologies for facts first-rate evaluation and improvement,” ACM Computing Surveys (CSUR), vol. forty one, p. 16, 2009.
  • [2] D. McGilvray, “Ten Steps to exceptional facts and trusted advice,” MIT counsel fine trade Symposium, 2008.
  • [3] R. Y. W. a. D. M. robust, “past accuracy: What statistics best ability to information consumers,” Journal of administration information systems, vol. 12, pp. 5–33, 1996.
  • [4] Sidi Fatimah,Shariat Panahy, Payam Hassany, Lilly Suriani Affendey, Marzanah A. Jabar, Hamidah Ibrahim, Aida Mustapha, “data exceptional: A survey of facts best dimensions,” in court cases — 2012 overseas convention on tips Retrieval and knowledge administration, CAMP’12, 2012.
  • [5] Herzog, Thomas N.,scheuren, f.j, winkler, “what's records high-quality and Why may still They Care,” Journal of commercial Engineering and administration, vol. 4(2), no. 2nd version, pp. 1–9, 2016.
  • [6] M. Rouse, “advantage Base,” TechTarget, three 2007. [Online]. accessible: https://searchcrm.techtarget.com/definition/competencies-base. [Accessed 9 12 2018].
  • [7] “data Profiling,” Wikipedia, [Online]. purchasable: https://en.wikipedia.org/wiki/Data_profiling. [Accessed 9 12 2018].
  • [8] “what's information Matching?,” Techopedia, [Online]. accessible: https://www.techopedia.com/definition/28041/data-matching. [Accessed 9 12 2018].
  • [9] “IBM counsel Server,” IBM, [Online]. purchasable: https://www.ibm.com/analytics/tips-server. [Accessed 9 12 2018].
  • [10] “foremost records fine software,” G2Crowd, [Online]. attainable: https://www.g2crowd.com/categories/records-fine. [Accessed 9 12 2018].
  • [11] “Oracle business information first-rate,” Oracle, [Online]. obtainable: http://www.oracle.com/us/products/middleware/statistics-integration/business-information-fine/overview/index.html. [Accessed 12 9 2018].
  • [12] “records satisfactory services,” Microsoft, 10 12 2013. [Online]. accessible: https://doctors.microsoft.com/en-us/sql/records-satisfactory-features/statistics-great-functions?view=sql-server-2017. [Accessed 12 9 2018].
  • [13] “records first-class,” Talend, [Online]. accessible: https://www.talend.com/items/records-excellent/. [Accessed 9 12 2018].
  • [14] “Trillium software,” Syncsort, [Online]. attainable: http://www.syncsort.com/en/About/Trillium-utility. [Accessed 9 12 2018].
  • [15] “SAS records first-rate and statistics satisfactory Server,” SAS, [Online]. accessible: http://help.sas.com/utility/products/dataqual/index.html. [Accessed 9 12 2018]

  • global information Warehouse administration utility industry | killexams.com Real Questions and Pass4sure dumps

    ny, Aug. 6, 2013 /PRNewswire by means of COMTEX/ -- Reportlinker.com declares that a new market research record is purchasable in its catalogue:

    international statistics Warehouse administration software Industryhttp://www.reportlinker.com/p01591574/world-information-Warehouse-management-utility-business.html#utm_source=prnewswire&utm_medium=pr&utm_campaign=Logistics_and_Freight

    This report analyzes the global markets for information Warehouse administration software in US$ Million by using here Product Segments: facts Warehouse Database management application, and data Warehouse Integration application.

    The document provides separate complete analytics for the us, Canada, Japan, Europe, Asia-Pacific, Latin the us, and leisure of World.

    Annual estimates and forecasts are offered for the period 2010 through 2018. also, a six-12 months historic evaluation is supplied for these markets.

    The document profiles 37 organizations including many key and niche avid gamers reminiscent of Astera utility, EMC service provider, Heron engage, Hewlett-Packard, Vertica programs, HiT application, Inc., IBM service provider, Informatica service provider, Microsoft business enterprise, Oracle corporation, SAP AG, Sybase, Inc., software AG, SAS Institute Inc., Sensage, Inc., and Teradata enterprise.

    Market records and analytics are derived from primary and secondary research. enterprise profiles are basically in accordance with public area suggestions together with enterprise URLs.

    I. INTRODUCTION, METHODOLOGY & PRODUCT DEFINITIONSStudy Reliability and Reporting barriers I-1Disclaimers I-2Data Interpretation & Reporting stage I-2Quantitative recommendations & Analytics I-2Product Definitions and Scope of look at I-3Data Warehouse Database administration utility I-3Data Warehouse Integration software I-three

    II. govt abstract

    1. business OVERVIEW II-1A quick Prelude II-1Impact of the 2007-2009 Recession looking back II-2Decline in IT Spending in Europe & the USA toDampen growth in 2013 II-3Key Market developments, Drivers & issues II-3Data Explosion Drives Demand for next era DataWarehouse systems II-3Growing center of attention on enterprise Intelligence to advantage the DataWarehousing Market II-4Opportunity Indicator II-6Table 1: World market for company Intelligence application(2013E): Breakdown of sales (In US$ Million) by GeographicRegion (includes corresponding Graph/Chart) II-6Big statistics: A probability or a chance? II-6Big facts Amplifies the need for facts Integration options II-6Big statistics: A challenge to normal data Warehouse or Is It? II-7Banking & economic features: The greatest conclusion UserIndustry II-9Implementation of Basel III Regulatory Framework Spurs Growthin statistics Warehousing II-9Deployments of BI& statistics Warehousing grow in the HealthcareSector II-10Retail company Intelligence Boosts potentialities for DataWarehousing utility II-11Popularity of business records Warehouse home equipment: A Threatto records Warehousing utility II-11Data Virtualization style Lays the Platform for the Evolutionof Logical information Warehouse II-11Transition from Transaction primarily based DWSystems to AnalyticalBased DW programs Set To proceed II-12Performance demands Drives improvements in statistics WarehouseArchitecture II-13Real-Time facts Warehouse: The Cynosure of focal point II-13In-memory expertise positive aspects Prominence II-14Embedded In-Database Analytics gain floor II-14Big information Proliferation Spurs construction of NoSQL Databases II-14Low cost Open source records Warehouse grow in popularity II-15Data Warehousing As a carrier Turns the aggressive heat onOn-Premises information Warehouses II-15Market Share Findings II-16Table 2: World data Warehousing Market (2012): PercentageShare Breakdown of Revenues of leading avid gamers (includescorresponding Graph/Chart) II-16Market Outlook II-16

    2. PRODUCT OVERVIEW II-17Data Warehousing: A Definition II-17Types of data II-17Subject Oriented II-17Integrated: II-18Non-risky: II-18Time Variant: II-18Accessibility II-18Query Flexibility II-18Integration: II-18Multidimensional representation II-18Information Conciseness II-18Correctness & Completeness II-18OLAP II-18Reporting II-19Ad-hoc Queries II-19Dashboards II-19Mixed Workloads II-19Predictive analysis II-19Data Warehousing utility: A Definition II-20Primary features of statistics Warehousing utility II-20Data Warehouse IntegrationSoftware II-21Importance & want for data Integration software II-21Data Warehouse Database management utility II-21End-Use trade Verticals II-22Insurance II-22Telecommunications II-22Retailing II-23Traffic Telemetry & clever Transportation programs II-23Research II-23Government II-24Enterprise: inventory administration II-24Medical health Care II-24Banking & financial services II-25E-Commerce II-25Logistics II-25

    3. REGULATORY scenario II-26ISO 9001: 2008 II-26Tax Audits II-26Financial functions Modernization Act II-26

    four. PRODUCT LAUNCHES II-27Calpont Unveils InfiniDB enterprise 2.0 II-27Amazon net services Introduces Redshift, a Cloud data Warehouse II-28IBM Introduces InfoSphere Warehouse 10 and DB2 10 application II-28DTCC proclaims Plans to Launch a new overseas alternate DataRepository in Partnership with SWIFT II-28BitYota Introduces facts Warehouse carrier on Amazon web services II-29Treasure records Introduces Cloud-primarily based statistics Warehouse II-29Oracle Introduces economic capabilities facts Warehouse II-29EMC Launches EMC® Greenplum® Database Free neighborhood edition II-30Juniper innovations Introduces WPMS Warehouse utility II-30Heron interact Introduces New CrossTie established LedgerConnector and have interaction records Warehouse options II-31Microsoft Introduces Novel SQL Server 2008 R2 Parallel DataWarehouse and important capabilities program II-31Microsoft Introduces advanced edition of SQL Server speedy TrackData Warehouse II-31OTC Launches new version of PAT DWData Warehouse solution II-32Blackboard Introduces BlackboardAnalytics Suite II-32Appfluent Unveils Visibility 90X II-32Zettaset Introduces safety facts Warehouse, a knowledge Warehousefor Forensic evaluation II-33Unify rectangular Launches PowerView three.0 II-33Embarcadero Introduces new version of ER/Studio XE II-34Teradata and Kalido Introduce Agile statistics Warehouse II-35EMC Unveils New EMC Greenplum facts Computing appliance II-35eScholar Introduces new version of eScholar comprehensive DataWarehouse® for Postsecondary II-35HP Introduces HP enterprise Intelligence assessment capabilities forUse with SAP options II-36Fujitsu Introduces Two facts Warehousing options II-36NWP capabilities Launches ConsumptionSmart II-37IBM Unveils 9.7 InfoSphere and DB2 II-37Oracle Unveils Oracle® Retail facts mannequin II-38Teradata Launches accelerate for Demand signal Repository II-38IBM Launches Informix Database application II-39Infobright Unveils windows Infobright community version II-39Microsoft Launches Preconfigured records Warehouse ReferenceArchitectures II-40Infobright and Talend Unveil integrated Open supply Solutionsfor facts Warehousing II-40Kickfire Launches New data Warehouse appliance II-40Teradata Introduces Teradata 13 Database answer II-41EMC Launches NewSolutions and capabilities II-41SenSage Launches SenSage 4.5 II-42

    5. STRATEGIC company tendencies II-44Systems the us Acquires Bartronics america II-44Deloitte broadcasts the Acquisition of Recombinant statistics II-45KEYW Acquires Sensage II-45Teradata Acquires Aprimo II-45SenSage Enters into Partnership with Go IP international services II-46Virtua and Moses Cone fitness system opt for Cisco UnifiedComputing SystemTM II-46QVC Chooses IBM Netezza® TwinFinTM equipment II-47Astera Enters into Complementary technology Partnership withNetezza II-47Astera® application and Teradata Enter into Partnership II-48Teradata and best buy sign contract II-48Appfluent expertise and Informatica Enter into Partnership II-48IBM Takes Over Netezza II-49HP Takes Over Stratavia II-49EMC to Take Over Greenplum II-49Oracle Takes Over solar Microsystems II-50Oracle Takes Over Silver Creek techniques II-50IBM signals prolonged contract with NEC II-50Teradata indications agreement with Walmart II-51Claraview Inks agreement with WFUBMC II-51BI source Enters into Partnership with Sybase II-51NEC signals agreement with Netezza II-52Dell upgrades energetic business statistics Warehouse Platform ofTeradata II-52HealthNow ny Deploys Informatica records capabilities II-52Coffing information Warehousing Enters into Partnership and OEMAgreement with Microsoft II-53Pakistan Telecom mobile Enters into agreement with Teradata II-53Oracle Takes Over GoldenGate application II-53Acxius Strategic Consulting Enters into Partnership Agreementwith Aster statistics programs II-54Cisco programs Acquires Tidal software II-54expressor application Enters into expertise accomplice Agreementwith BIReady II-55Teradata signs settlement with SAP II-55GoldenGate software Collaborates with Greenplum II-56Netezza Enters into Partnership with Kalido II-56HiT utility and Netezza Enter into Partnership II-57

    6. FOCUSON select global players II-58Astera application (u . s . a .) II-58EMC supplier (country) II-58Heron interact (us of a) II-58Hewlett-Packard (united states of america) II-59Vertica programs (united states of america) II-59HiT application Inc.,(u . s . a .) II-59IBM agency (u . s .) II-59Informatica supplier (us of a) II-60Microsoft organization (us of a) II-60Oracle corporation (united states) II-60SAP AG (Germany) II-61Sybase, Inc. II-61Software AG (Germany) II-62SAS Institute Inc., II-62Sensage, Inc (u . s .) II-62Teradata organisation (usa) II-62

    7. global MARKET perspective II-63Table three: World recent previous, current & Future evaluation for DataWarehouse administration application Market with the aid of GeographicRegion/country - US, Canada, Japan, Europe, Asia-Pacific,Latin the united states and relaxation of World Markets Independently Analyzedwith Annual revenue Figures in US$ Million for Years 2010through 2018 (contains corresponding Graph/Chart) II-sixty three

    desk four: World historical evaluate for facts Warehouse ManagementSoftware Market by means of Geographic place/nation - US, Canada,Japan, Europe, Asia-Pacific, Latin the us and leisure of WorldMarkets Independently Analyzed with Annual income Figures inUS$ Million for Years 2004 via 2009 (includescorresponding Graph/Chart) II-sixty four

    table 5: World 14-year point of view for facts WarehouseManagement software by Geographic vicinity/nation - PercentageBreakdown of dollar income for US, Canada, Japan, Europe,Asia-Pacific, Latin america, and rest of World Markets forYears 2005, 2013, & 2018 (contains corresponding Graph/Chart) II-65

    desk 6: World fresh previous, current & Future analysis for DataWarehouse Database administration application with the aid of GeographicRegion/country - US, Canada, Japan, Europe, Asia-Pacific,Latin the us and leisure of World Markets Independently Analyzedwith Annual sales Figures in US$ Million for Years 2010through 2018 (contains corresponding Graph/Chart) II-sixty six

    desk 7: World historical evaluate for records Warehouse DatabaseManagement software via Geographic area/ country - US,Canada, Japan, Europe, Asia-Pacific, Latin the usa and rest ofWorld Markets Independently Analyzed with Annual earnings Figuresin US$ Million for Years 2004 through 2009 (includescorresponding Graph/Chart) II-sixty seven

    desk 8: World 14-yr perspective for information Warehouse DatabaseManagement utility via Geographic area/nation - PercentageBreakdown of dollar income for US, Canada, Japan, Europe,Asia-Pacific, Latin america and rest of World Markets forYears 2005, 2013, & 2018 (includes corresponding Graph/Chart) II-68

    table 9: World contemporary previous, existing & Future evaluation for DataWarehouse Integration utility by means of Geographic location - US,Canada, Japan, Europe, Asia-Pacific, Latin the us and leisure ofWorld Markets Independently Analyzed with Annual sales Figuresin US$ Million for Years 2010 through 2018 (includescorresponding Graph/Chart) II-69

    table 10: World historic overview for statistics Warehouse IntegrationSoftware with the aid of Geographic location - US, Canada, Japan, Europe,Asia-Pacific, Latin the united states and leisure of World MarketsIndependently Analyzed with Annual earnings Figures in US$Million for Years 2004 via 2009 (includes correspondingGraph/Chart) II-70

    table eleven: World 14-12 months point of view for records WarehouseIntegration application by Geographic place/country - PercentageBreakdown of greenback sales for US, Canada, Japan, Europe,Asia-Pacific, Latin the usa and rest of World Markets forYears 2005, 2013, and 2018 (comprises correspondingGraph/Chart) II-seventy one

    III. MARKET

    1. the united states III-1A.Market analysis III-1Current & Future analysis III-1High Penetration of advice expertise Ensures SustainedGrowth in US Market III-1Retailing business Boosts potentialities for statistics WarehousingTechnology III-2Product Launches III-2Strategic company trends III-16Key avid gamers III-29B.Market Analytics III-34Table 12: US contemporary past, latest & Future evaluation for DataWarehouse management with the aid of Product phase - facts WarehouseDatabase management software & information Warehouse IntegrationSoftware Independently Analyzed with Annual earnings Figures inUS$ Million for Years 2010 through 2018 (includescorresponding Graph/Chart) III-34

    desk 13: US ancient assessment for facts Warehouse ManagementMarket by way of Product Segments - information Warehouse DatabaseManagement utility & statistics Warehouse Integration SoftwareIndependently Analyzed with Annual earnings Figures in US$Million for Years 2004 through 2009 (comprises correspondingGraph/Chart) III-35

    table 14: US 14-yr viewpoint for data WarehouseManagement Market by means of Product Segments - percent Breakdownof dollar income for information Warehouse Database ManagementSoftware & facts Warehouse Integration utility Segments forYears 2005, 2013, and 2018 (includes correspondingGraph/Chart) III-36

    2. CANADA III-37A.Market evaluation III-37Current & Future evaluation III-37B.Market Analytics III-37Table 15: Canada fresh past, latest & Future evaluation forData Warehouse administration through Product phase - DataWarehouse Database management utility & data WarehouseIntegration utility Independently Analyzed with AnnualSales Figures in US$ Million for Years 2010 via 2018(includes corresponding Graph/Chart) III-37

    table sixteen: Canada ancient overview for data WarehouseManagement Market through Product Segments - data WarehouseDatabase management utility & facts Warehouse IntegrationSoftware Independently Analyzed with Annual income Figures inUS$ Million for Years 2004 via 2009 (includescorresponding Graph/Chart) III-38

    desk 17: Canada 14-year standpoint for statistics WarehouseManagement Market via Product Segments - percentage Breakdownof dollar revenue for records Warehouse Database ManagementSoftware & statistics Warehouse Integration application Segments forYears 2005, 2013, and 2018 (contains correspondingGraph/Chart) III-39

    3. JAPAN III-40A.Market evaluation III-40Product Launches III-40Strategic company traits III-40B.Market Analytics III-41Table 18: jap contemporary past, current & Future Analysisfor facts Warehouse management by Product phase - DataWarehouse Database administration software & information WarehouseIntegration software Independently Analyzed with AnnualSales Figures in US$ Million for Years 2010 via 2018(contains corresponding Graph/Chart) III-41

    desk 19: japanese historic evaluate for statistics WarehouseManagement Market with the aid of Product Segments - statistics WarehouseDatabase administration software & information Warehouse IntegrationSoftware Independently Analyzed with Annual revenue Figures inUS$ Million for Years 2004 through 2009 (includescorresponding Graph/Chart) III-42

    desk 20: japanese 14-yr point of view for records WarehouseManagement Market by Product Segments - percent Breakdownof dollar sales for records Warehouse Database ManagementSoftware & information Warehouse Integration software Segments forYears 2005, 2013, and 2018 (includes correspondingGraph/Chart) III-43

    four. EUROPE III-44A.Market evaluation III-44Current & Future analysis III-44B.Market Analytics III-44Table 21: Europe recent past, latest & Future analysis forData Warehouse management through vicinity - France, Germany,Italy, UK, Spain, Russia, rest of Europe IndependentlyAnalyzed with Annual earnings Figures in US$ Million for Years2010 via 2018 (includes corresponding Graph/Chart) III-44

    desk 22: Europe ancient assessment for records WarehouseManagement by way of area - France, Germany, Italy, UK, Spain,Russia, relaxation of Europe Independently Analyzed with AnnualSales Figures in US$ Million for Years 2004 through 2009(contains corresponding Graph/Chart) III-45

    desk 23: Europe 14-yr viewpoint for information WarehouseManagement via area - percent Breakdown of dollar Salesfor France, Germany, Italy, UK, Spain, Russia, and relaxation ofEurope Markets for Years 2005, 2013 and 2018 (includescorresponding Graph/Chart) III-forty six

    table 24: Europe recent past, latest & Future evaluation forData Warehouse administration by using Product phase - DataWarehouse Database management software & records WarehouseIntegration application Independently Analyzed with AnnualSales Figures in US$ Million for Years 2010 through 2018(comprises corresponding Graph/Chart) III-forty seven

    table 25: Europe historical overview for data WarehouseManagement Market via Product Segments - statistics WarehouseDatabase administration application & records Warehouse IntegrationSoftware Independently Analyzed with Annual revenue Figures inUS$ Million for Years 2004 via 2009 (includescorresponding Graph/Chart) III-48

    desk 26: Europe 14-12 months standpoint for facts WarehouseManagement Market by means of Product Segments - percent Breakdownof greenback revenue for statistics Warehouse Database ManagementSoftware & statistics Warehouse Integration application Segments forYears 2005, 2013, and 2018 (includes correspondingGraph/Chart) III-forty nine

    4a. FRANCE III-50Market evaluation III-50Table 27: French contemporary previous, current & Future evaluation forData Warehouse administration by Product segment - DataWarehouse Database management software & records WarehouseIntegration utility Independently Analyzed with AnnualSales Figures in US$ Million for Years 2010 through 2018(includes corresponding Graph/Chart) III-50

    desk 28: French historical overview for information WarehouseManagement Market through Product Segments - records WarehouseDatabase administration application & facts Warehouse IntegrationSoftware Independently Analyzed with Annual income Figures inUS$ Million for Years 2004 via 2009 (includescorresponding Graph/Chart) III-51

    table 29: French 14-12 months perspective for facts WarehouseManagement Market by means of Product Segments - percent Breakdownof dollar revenue for data Warehouse Database ManagementSoftware & statistics Warehouse Integration software Segments forYears 2005, 2013, and 2018 (includes correspondingGraph/Chart) III-52

    4b. GERMANY III-53A.Market analysis III-53Strategic company trends III-53B.Market Analytics III-54Table 30: German fresh previous, present & Future evaluation forData Warehouse management by Product phase - DataWarehouse Database management software & records WarehouseIntegration utility Independently Analyzed with AnnualSales Figures in US$ Million for Years 2010 via 2018(includes corresponding Graph/Chart) III-fifty four

    table 31: German historical assessment for statistics WarehouseManagement Market by Product Segments - information WarehouseDatabase management utility & information Warehouse IntegrationSoftware Independently Analyzed with Annual income Figures inUS$ Million for Years 2004 through 2009 (includescorresponding Graph/Chart) III-fifty five

    desk 32: German 14-yr perspective for information WarehouseManagement Market by means of Product Segments - percentage Breakdownof dollar income for facts Warehouse Database ManagementSoftware & records Warehouse Integration software Segments forYears 2005, 2013, and 2018 (comprises correspondingGraph/Chart) III-56

    4c. ITALY III-57Market analysis III-57Table 33: Italian contemporary past, present & Future evaluation forData Warehouse management through Product segment - DataWarehouse Database management application & records WarehouseIntegration utility Independently Analyzed with AnnualSales Figures in US$ Million for Years 2010 via 2018(contains corresponding Graph/Chart) III-fifty seven

    desk 34: Italian historic evaluation for information WarehouseManagement Market with the aid of Product Segments - data WarehouseDatabase administration software & facts Warehouse IntegrationSoftware Independently Analyzed with Annual income Figures inUS$ Million for Years 2004 via 2009 (includescorresponding Graph/Chart) III-fifty eight

    desk 35: Italian 14-12 months point of view for information WarehouseManagement Market with the aid of Product Segments - percentage Breakdownof dollar revenue for records Warehouse Database ManagementSoftware & data Warehouse Integration software Segments forYears 2005, 2013, and 2018 (includes correspondingGraph/Chart) III-59

    4d. uk (UK) III-60A.Market evaluation III-60Product Launches III-60B.Market Analytics III-61Table 36: UK contemporary previous, latest & Future evaluation for DataWarehouse administration by means of Product section - data WarehouseDatabase administration utility & information Warehouse IntegrationSoftware Independently Analyzed with Annual earnings Figures inUS$ Million for Years 2010 via 2018 (includescorresponding Graph/Chart) III-61

    table 37: UK historical evaluate for records Warehouse ManagementMarket through Product Segments - statistics Warehouse DatabaseManagement software & data Warehouse Integration SoftwareIndependently Analyzed with Annual revenue Figures in US$Million for Years 2004 through 2009 (includes correspondingGraph/Chart) III-62

    table 38: UK 14-year point of view for statistics WarehouseManagement Market by using Product Segments - percent Breakdownof greenback revenue for facts Warehouse Database ManagementSoftware & facts Warehouse Integration application Segments forYears 2005, 2013, and 2018 (comprises correspondingGraph/Chart) III-63

    4e. SPAIN III-64Market analysis III-64Table 39: Spain fresh previous, latest & Future analysis forData Warehouse management by Product section - DataWarehouse Database management utility & records WarehouseIntegration utility Independently Analyzed with AnnualSales Figures in US$ Million for Years 2010 through 2018(comprises corresponding Graph/Chart) III-sixty four

    desk forty: Spain historic overview for information WarehouseManagement Market with the aid of Product Segments - facts WarehouseDatabase administration application & information Warehouse IntegrationSoftware Independently Analyzed with Annual income Figures inUS$ Million for Years 2004 via 2009 (includescorresponding Graph/Chart) III-sixty five

    table 41: Spain 14-Yea

    To order this file:Logistics_and_Freight business: global records Warehouse administration utility trade

    Contact Clare: clare@reportlinker.com US:(339) 368 6001 Intl:+1 339 368 6001

    supply Reportlinker

    Copyright (C) 2013 PR Newswire. All rights reserved


    BI, advanced analytics present area for wind turbine, blinds makers | killexams.com Real Questions and Pass4sure dumps

    As corporations seem to derive greater price from all their property -- including their facts -- superior analytics concepts, the skill to handle "large statistics" and superior reporting and enterprise intelligence (BI) capabilities have become more and more critical to company success.

    as an instance, Denmark-based wind turbine company Vestas Wind systems is the usage of analytics tools as a way to provide its business operations an side over competitors.

    Situating wind mills is about greater than raising finance and successful governmental planning permission. The region of wind farms is an more and more science-primarily based endeavor, with developers modeling not just where to position the farms but also the way to arrange each and every particular person turbine to maximum impact.

    From working out the way to maximise electricity technology and minimise upkeep expenses, power businesses deserve to examine wind patterns in addition to rainfall, humidity and atmospheric pressure. and they need to model the airflow throughout turbine blades to calculate the finest approach to place every turbine tower.

    "americans buy turbines no longer as a result of they're eye-catching, however as a result of they need a return on funding," mentioned Lars Christian Christensen, a vice chairman at Vestas. "Our job is to be certain the purchaser has the right website, but additionally the most advantageous layout for the turbines."

    using advanced analytics software and different tools to optimise wind turbine areas allows for Christensen's team to "improve the output of the vigour plant by using a few p.c," he pointed out. "You gain a much better output for a similar charge. They use application modeling and tools to give an improved enterprise case evaluation and extra sure bet."

    ‘Hindcasts’ -- climate models with hindsight

    The scope of statistics investigated by way of the Vestas group is massive. The company has maps of the realm, down to 3 km by means of 3 km squares on a grid, and can call up wind, temperature, solar radiation and humidity facts from the current back to the year 2000 on an hourly foundation. "That allows us to create a worldwide, historical view," Christensen said.

    The facts is used to generate "hindcasts," or fashions of what climate situations would had been at prospective turbine sites, and the electrical energy that could have been generated by using distinct combos of turbine places.

    methods and tools employed as a part of the method consist of computational fluid dynamics, database flow models, and computational and evaluation tools such as IBM's InfoSphere BigInsights, a Hadoop-based mostly know-how for examining massive volumes of each structured and unstructured records.

    "Our big records problem is that we've a library that runs to 3 petabytes," Christensen said. "in case you can not retrieve that suggestions from storage, it serves no intention." maintaining such a large database and the equipment required to analyse it's fundamental for a world operation, like Vestas: no longer everywhere that wishes eco-friendly power has a large flat space in which to construct a wind vigour plant.

    superior analytics allows for Vestas to inform if a particular location could be a pretty good web page for wind turbines, Christensen explained. "from time to time they assist valued clientele locate undiscovered supplies," he referred to. "The statistics they have is the digital equivalent of a map of gold mines."

    Blinds maker beneficial properties visibility into sales statistics

    Hillarys Blinds is a UK manufacturer with 27% of the united kingdom marketplace for made-to-measure blinds and other home windows coverings. The business operates a right away sales model, with 1,000 self-employed income advisers who talk over with consumers in their homes or companies and measure and order the goods. they're supported via the a hundred-grownup manufacturing and head workplace crew in Nottinghamshire.

    The problem for Hillarys changed into to make certain a speedier circulate of assistance to and from the earnings advisers. but, because it director Julian Bond facets out, considering they are self-employed, the top workplace couldn't impose IT techniques on them. "We can't take a sheep dip approach," he pointed out. "We need to take into account the results of regional adaptations, competitors and the financial system, so that you can pleasant-tune their offerings county by means of county."

    however the company additionally wanted to shorten the cycle between revenue, manufacturing and finance. "here's a retail business, so they now have a weekly cycle of trading conferences and the finance team would spend all Monday trying to kind the buying and selling photo," Bond talked about. "And if somebody desired some different facts, it could take a week to find the answer."

    Hillarys additionally desired to break up out facts from its all of a sudden-transforming into customized products enterprise. This unit in general takes on industrial contracts, which can be a long way larger than home orders; due to this fact, it skewed the weekly figures.

    The issue, Bond pointed out, is that there become no easy approach to pull collectively all the records: "We had whole families of spreadsheets, and it became resulting in frustrations within the enterprise as they did not have entry to the totals they wanted."

    After evaluating a few BI and analytics products, Hillarys opted to roll out SAP's business tips Warehouse (BW), primarily on account of its tight integration with the company's SAP-primarily based manufacturing programs.

    different BI equipment can be richer in performance than BW is, Bond talked about, however the integration became the most essential element for the business. "We don't make stock objects, corresponding to 30 several types of blinds," he defined. "every order is enjoyable and so needs its own invoice of substances."

    And the effects have justified the choice, in response to Bond: the enterprise has been in a position to carry its weekly buying and selling assembly ahead, and the excellent of the facts obtainable for evaluation has superior. "we're able to analyze questions [in their sales data] we'd now not up to now had been able to reply," he spoke of. "we've a a great deal clearer view."


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    Assessment: InfoSphere Warehouse V9.5-Assessment

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    Global Data Warehouse Management Software Industry | killexams.com real questions and Pass4sure dumps

    NEW YORK, Aug. 6, 2013 /PRNewswire via COMTEX/ -- Reportlinker.com announces that a new market research report is available in its catalogue:

    Global Data Warehouse Management Software Industryhttp://www.reportlinker.com/p01591574/Global-Data-Warehouse-Management-Software-Industry.html#utm_source=prnewswire&utm_medium=pr&utm_campaign=Logistics_and_Freight

    This report analyzes the worldwide markets for Data Warehouse Management Software in US$ Million by the following Product Segments: Data Warehouse Database Management Software, and Data Warehouse Integration Software.

    The report provides separate comprehensive analytics for the US, Canada, Japan, Europe, Asia-Pacific, Latin America, and Rest of World.

    Annual estimates and forecasts are provided for the period 2010 through 2018. Also, a six-year historic analysis is provided for these markets.

    The report profiles 37 companies including many key and niche players such as Astera Software, EMC Corporation, Heron InterAct, Hewlett-Packard, Vertica Systems, HiT Software, Inc., IBM Corporation, Informatica Corporation, Microsoft Corporation, Oracle Corporation, SAP AG, Sybase, Inc., Software AG, SAS Institute Inc., Sensage, Inc., and Teradata Corporation.

    Market data and analytics are derived from primary and secondary research. Company profiles are primarily based on public domain information including company URLs.

    I. INTRODUCTION, METHODOLOGY & PRODUCT DEFINITIONSStudy Reliability and Reporting Limitations I-1Disclaimers I-2Data Interpretation & Reporting Level I-2Quantitative Techniques & Analytics I-2Product Definitions and Scope of Study I-3Data Warehouse Database Management Software I-3Data Warehouse Integration Software I-3

    II. EXECUTIVE SUMMARY

    1. INDUSTRY OVERVIEW II-1A Quick Prelude II-1Impact of the 2007-2009 Recession in Retrospect II-2Decline in IT Spending in Europe & the United States toDampen Growth in 2013 II-3Key Market Trends, Drivers & Issues II-3Data Explosion Drives Demand for Next Generation DataWarehouse Platforms II-3Growing Focus on Business Intelligence to Benefit the DataWarehousing Market II-4Opportunity Indicator II-6Table 1: World Market for Business Intelligence Software(2013E): Breakdown of Sales (In US$ Million) by GeographicRegion (includes corresponding Graph/Chart) II-6Big Data: A Threat or an Opportunity? II-6Big Data Amplifies the Need for Data Integration Solutions II-6Big Data: A Challenge to Traditional Data Warehouse or Is It? II-7Banking & Financial Services: The Largest End UserIndustry II-9Implementation of Basel III Regulatory Framework Spurs Growthin Data Warehousing II-9Deployments of BI& Data Warehousing Grow in the HealthcareSector II-10Retail Business Intelligence Boosts Prospects for DataWarehousing Software II-11Popularity of Enterprise Data Warehouse Appliances: A Threatto Data Warehousing Software II-11Data Virtualization Trend Lays the Platform for the Evolutionof Logical Data Warehouse II-11Transition from Transaction Based DWSystems to AnalyticalBased DW Systems Set To Continue II-12Performance Demands Drives Innovations in Data WarehouseArchitecture II-13Real-Time Data Warehouse: The Cynosure of Focus II-13In-Memory Technology Gains Prominence II-14Embedded In-Database Analytics Gain Ground II-14Big Data Proliferation Spurs Development of NoSQL Databases II-14Low Cost Open Source Data Warehouse Grow in Popularity II-15Data Warehousing As a Service Turns the Competitive Heat onOn-Premises Data Warehouses II-15Market Share Findings II-16Table 2: World Data Warehousing Market (2012): PercentageShare Breakdown of Revenues of Leading Players (includescorresponding Graph/Chart) II-16Market Outlook II-16

    2. PRODUCT OVERVIEW II-17Data Warehousing: A Definition II-17Types of Data II-17Subject Oriented II-17Integrated: II-18Non-Volatile: II-18Time Variant: II-18Accessibility II-18Query Flexibility II-18Integration: II-18Multidimensional Representation II-18Information Conciseness II-18Correctness & Completeness II-18OLAP II-18Reporting II-19Ad-hoc Queries II-19Dashboards II-19Mixed Workloads II-19Predictive Analysis II-19Data Warehousing Software: A Definition II-20Primary Functions of Data Warehousing Software II-20Data Warehouse IntegrationSoftware II-21Importance & Need for Data Integration Software II-21Data Warehouse Database Management Software II-21End-Use industry Verticals II-22Insurance II-22Telecommunications II-22Retailing II-23Traffic Telemetry & Intelligent Transportation Systems II-23Research II-23Government II-24Enterprise: Inventory Management II-24Medical Health Care II-24Banking & Financial Services II-25E-Commerce II-25Logistics II-25

    3. REGULATORY SCENARIO II-26ISO 9001: 2008 II-26Tax Audits II-26Financial Services Modernization Act II-26

    4. PRODUCT LAUNCHES II-27Calpont Unveils InfiniDB Enterprise 2.0 II-27Amazon Web Services Introduces Redshift, a Cloud Data Warehouse II-28IBM Introduces InfoSphere Warehouse 10 and DB2 10 Software II-28DTCC Announces Plans to Launch a New Foreign Exchange DataRepository in Partnership with SWIFT II-28BitYota Introduces Data Warehouse Service on Amazon Web Services II-29Treasure Data Introduces Cloud-Based Data Warehouse II-29Oracle Introduces Financial Services Data Warehouse II-29EMC Launches EMC® Greenplum® Database Free Community Edition II-30Juniper Innovations Introduces WPMS Warehouse Software II-30Heron InterAct Introduces New CrossTie General LedgerConnector and InterAct Data Warehouse Solutions II-31Microsoft Introduces Novel SQL Server 2008 R2 Parallel DataWarehouse and Critical Advantage Program II-31Microsoft Introduces Advanced Version of SQL Server Fast TrackData Warehouse II-31OTC Launches New Version of PAT DWData Warehouse Solution II-32Blackboard Introduces BlackboardAnalytics Suite II-32Appfluent Unveils Visibility 90X II-32Zettaset Introduces Security Data Warehouse, a Data Warehousefor Forensic Analysis II-33Unify Square Launches PowerView 3.0 II-33Embarcadero Introduces New Version of ER/Studio XE II-34Teradata and Kalido Introduce Agile Data Warehouse II-35EMC Unveils New EMC Greenplum Data Computing Appliance II-35eScholar Introduces New Version of eScholar Complete DataWarehouse® for Postsecondary II-35HP Introduces HP Business Intelligence Assessment Services forUse with SAP Solutions II-36Fujitsu Introduces Two Data Warehousing Solutions II-36NWP Services Launches ConsumptionSmart II-37IBM Unveils 9.7 InfoSphere and DB2 II-37Oracle Unveils Oracle® Retail Data Model II-38Teradata Launches Accelerate for Demand Signal Repository II-38IBM Launches Informix Database Software II-39Infobright Unveils Windows Infobright Community Edition II-39Microsoft Launches Preconfigured Data Warehouse ReferenceArchitectures II-40Infobright and Talend Unveil Integrated Open Source Solutionsfor Data Warehousing II-40Kickfire Launches New Data Warehouse Appliance II-40Teradata Introduces Teradata 13 Database Solution II-41EMC Launches NewSolutions and Services II-41SenSage Launches SenSage 4.5 II-42

    5. STRATEGIC CORPORATE DEVELOPMENTS II-44Systems America Acquires Bartronics America II-44Deloitte Announces the Acquisition of Recombinant Data II-45KEYW Acquires Sensage II-45Teradata Acquires Aprimo II-45SenSage Enters into Partnership with Go IP Global Services II-46Virtua and Moses Cone Health System Choose Cisco UnifiedComputing SystemTM II-46QVC Chooses IBM Netezza® TwinFinTM Appliance II-47Astera Enters into Complementary Technology Partnership withNetezza II-47Astera® Software and Teradata Enter into Partnership II-48Teradata and Best Buy Sign Agreement II-48Appfluent Technology and Informatica Enter into Partnership II-48IBM Takes Over Netezza II-49HP Takes Over Stratavia II-49EMC to Take Over Greenplum II-49Oracle Takes Over Sun Microsystems II-50Oracle Takes Over Silver Creek Systems II-50IBM Signs Extended Agreement with NEC II-50Teradata Signs Agreement with Walmart II-51Claraview Inks Agreement with WFUBMC II-51BI Source Enters into Partnership with Sybase II-51NEC Signs Agreement with Netezza II-52Dell Upgrades Active Enterprise Data Warehouse Platform ofTeradata II-52HealthNow New York Deploys Informatica Data Services II-52Coffing Data Warehousing Enters into Partnership and OEMAgreement with Microsoft II-53Pakistan Telecom Mobile Enters into Agreement with Teradata II-53Oracle Takes Over GoldenGate Software II-53Acxius Strategic Consulting Enters into Partnership Agreementwith Aster Data Systems II-54Cisco Systems Acquires Tidal Software II-54expressor Software Enters into Technology Partner Agreementwith BIReady II-55Teradata Signs Agreement with SAP II-55GoldenGate Software Collaborates with Greenplum II-56Netezza Enters into Partnership with Kalido II-56HiT Software and Netezza Enter into Partnership II-57

    6. FOCUSON SELECT GLOBAL PLAYERS II-58Astera Software (USA) II-58EMC Corporation (USA) II-58Heron InterAct (USA) II-58Hewlett-Packard (USA) II-59Vertica Systems (USA) II-59HiT Software Inc.,(USA) II-59IBM Corporation (USA) II-59Informatica Corporation (USA) II-60Microsoft Corporation (USA) II-60Oracle Corporation (USA) II-60SAP AG (Germany) II-61Sybase, Inc. II-61Software AG (Germany) II-62SAS Institute Inc., II-62Sensage, Inc (USA) II-62Teradata Corporation (USA) II-62

    7. GLOBAL MARKET PERSPECTIVE II-63Table 3: World Recent Past, Current & Future Analysis for DataWarehouse Management Software Market by GeographicRegion/Country - US, Canada, Japan, Europe, Asia-Pacific,Latin America and Rest of World Markets Independently Analyzedwith Annual Sales Figures in US$ Million for Years 2010through 2018 (includes corresponding Graph/Chart) II-63

    Table 4: World Historic Review for Data Warehouse ManagementSoftware Market by Geographic Region/Country - US, Canada,Japan, Europe, Asia-Pacific, Latin America and Rest of WorldMarkets Independently Analyzed with Annual Sales Figures inUS$ Million for Years 2004 through 2009 (includescorresponding Graph/Chart) II-64

    Table 5: World 14-Year Perspective for Data WarehouseManagement Software by Geographic Region/Country - PercentageBreakdown of Dollar Sales for US, Canada, Japan, Europe,Asia-Pacific, Latin America, and Rest of World Markets forYears 2005, 2013, & 2018 (includes corresponding Graph/Chart) II-65

    Table 6: World Recent Past, Current & Future Analysis for DataWarehouse Database Management Software by GeographicRegion/Country - US, Canada, Japan, Europe, Asia-Pacific,Latin America and Rest of World Markets Independently Analyzedwith Annual Sales Figures in US$ Million for Years 2010through 2018 (includes corresponding Graph/Chart) II-66

    Table 7: World Historic Review for Data Warehouse DatabaseManagement Software by Geographic Region/ Country - US,Canada, Japan, Europe, Asia-Pacific, Latin America and Rest ofWorld Markets Independently Analyzed with Annual Sales Figuresin US$ Million for Years 2004 through 2009 (includescorresponding Graph/Chart) II-67

    Table 8: World 14-Year Perspective for Data Warehouse DatabaseManagement Software by Geographic Region/Country - PercentageBreakdown of Dollar Sales for US, Canada, Japan, Europe,Asia-Pacific, Latin America and Rest of World Markets forYears 2005, 2013, & 2018 (includes corresponding Graph/Chart) II-68

    Table 9: World Recent Past, Current & Future Analysis for DataWarehouse Integration Software by Geographic Region - US,Canada, Japan, Europe, Asia-Pacific, Latin America and Rest ofWorld Markets Independently Analyzed with Annual Sales Figuresin US$ Million for Years 2010 through 2018 (includescorresponding Graph/Chart) II-69

    Table 10: World Historic Review for Data Warehouse IntegrationSoftware by Geographic Region - US, Canada, Japan, Europe,Asia-Pacific, Latin America and Rest of World MarketsIndependently Analyzed with Annual Sales Figures in US$Million for Years 2004 through 2009 (includes correspondingGraph/Chart) II-70

    Table 11: World 14-Year Perspective for Data WarehouseIntegration Software by Geographic Region/Country - PercentageBreakdown of Dollar Sales for US, Canada, Japan, Europe,Asia-Pacific, Latin America and Rest of World Markets forYears 2005, 2013, and 2018 (includes correspondingGraph/Chart) II-71

    III. MARKET

    1. THE UNITED STATES III-1A.Market Analysis III-1Current & Future Analysis III-1High Penetration of Information Technology Ensures SustainedGrowth in US Market III-1Retailing Industry Boosts Prospects for Data WarehousingTechnology III-2Product Launches III-2Strategic Corporate Developments III-16Key Players III-29B.Market Analytics III-34Table 12: US Recent Past, Current & Future Analysis for DataWarehouse Management by Product Segment - Data WarehouseDatabase Management Software & Data Warehouse IntegrationSoftware Independently Analyzed with Annual Sales Figures inUS$ Million for Years 2010 through 2018 (includescorresponding Graph/Chart) III-34

    Table 13: US Historic Review for Data Warehouse ManagementMarket by Product Segments - Data Warehouse DatabaseManagement Software & Data Warehouse Integration SoftwareIndependently Analyzed with Annual Sales Figures in US$Million for Years 2004 through 2009 (includes correspondingGraph/Chart) III-35

    Table 14: US 14-Year Perspective for Data WarehouseManagement Market by Product Segments - Percentage Breakdownof Dollar Sales for Data Warehouse Database ManagementSoftware & Data Warehouse Integration Software Segments forYears 2005, 2013, and 2018 (includes correspondingGraph/Chart) III-36

    2. CANADA III-37A.Market Analysis III-37Current & Future Analysis III-37B.Market Analytics III-37Table 15: Canada Recent Past, Current & Future Analysis forData Warehouse Management by Product Segment - DataWarehouse Database Management Software & Data WarehouseIntegration Software Independently Analyzed with AnnualSales Figures in US$ Million for Years 2010 through 2018(includes corresponding Graph/Chart) III-37

    Table 16: Canada Historic Review for Data WarehouseManagement Market by Product Segments - Data WarehouseDatabase Management Software & Data Warehouse IntegrationSoftware Independently Analyzed with Annual Sales Figures inUS$ Million for Years 2004 through 2009 (includescorresponding Graph/Chart) III-38

    Table 17: Canada 14-Year Perspective for Data WarehouseManagement Market by Product Segments - Percentage Breakdownof Dollar Sales for Data Warehouse Database ManagementSoftware & Data Warehouse Integration Software Segments forYears 2005, 2013, and 2018 (includes correspondingGraph/Chart) III-39

    3. JAPAN III-40A.Market Analysis III-40Product Launches III-40Strategic Corporate Developments III-40B.Market Analytics III-41Table 18: Japanese Recent Past, Current & Future Analysisfor Data Warehouse Management by Product Segment - DataWarehouse Database Management Software & Data WarehouseIntegration Software Independently Analyzed with AnnualSales Figures in US$ Million for Years 2010 through 2018(includes corresponding Graph/Chart) III-41

    Table 19: Japanese Historic Review for Data WarehouseManagement Market by Product Segments - Data WarehouseDatabase Management Software & Data Warehouse IntegrationSoftware Independently Analyzed with Annual Sales Figures inUS$ Million for Years 2004 through 2009 (includescorresponding Graph/Chart) III-42

    Table 20: Japanese 14-Year Perspective for Data WarehouseManagement Market by Product Segments - Percentage Breakdownof Dollar Sales for Data Warehouse Database ManagementSoftware & Data Warehouse Integration Software Segments forYears 2005, 2013, and 2018 (includes correspondingGraph/Chart) III-43

    4. EUROPE III-44A.Market Analysis III-44Current & Future Analysis III-44B.Market Analytics III-44Table 21: Europe Recent Past, Current & Future Analysis forData Warehouse Management by Region - France, Germany,Italy, UK, Spain, Russia, Rest of Europe IndependentlyAnalyzed with Annual Sales Figures in US$ Million for Years2010 through 2018 (includes corresponding Graph/Chart) III-44

    Table 22: Europe Historic Review for Data WarehouseManagement by Region - France, Germany, Italy, UK, Spain,Russia, Rest of Europe Independently Analyzed with AnnualSales Figures in US$ Million for Years 2004 through 2009(includes corresponding Graph/Chart) III-45

    Table 23: Europe 14-Year Perspective for Data WarehouseManagement by Region - Percentage Breakdown of Dollar Salesfor France, Germany, Italy, UK, Spain, Russia, and Rest ofEurope Markets for Years 2005, 2013 and 2018 (includescorresponding Graph/Chart) III-46

    Table 24: Europe Recent Past, Current & Future Analysis forData Warehouse Management by Product Segment - DataWarehouse Database Management Software & Data WarehouseIntegration Software Independently Analyzed with AnnualSales Figures in US$ Million for Years 2010 through 2018(includes corresponding Graph/Chart) III-47

    Table 25: Europe Historic Review for Data WarehouseManagement Market by Product Segments - Data WarehouseDatabase Management Software & Data Warehouse IntegrationSoftware Independently Analyzed with Annual Sales Figures inUS$ Million for Years 2004 through 2009 (includescorresponding Graph/Chart) III-48

    Table 26: Europe 14-Year Perspective for Data WarehouseManagement Market by Product Segments - Percentage Breakdownof Dollar Sales for Data Warehouse Database ManagementSoftware & Data Warehouse Integration Software Segments forYears 2005, 2013, and 2018 (includes correspondingGraph/Chart) III-49

    4a. FRANCE III-50Market Analysis III-50Table 27: French Recent Past, Current & Future Analysis forData Warehouse Management by Product Segment - DataWarehouse Database Management Software & Data WarehouseIntegration Software Independently Analyzed with AnnualSales Figures in US$ Million for Years 2010 through 2018(includes corresponding Graph/Chart) III-50

    Table 28: French Historic Review for Data WarehouseManagement Market by Product Segments - Data WarehouseDatabase Management Software & Data Warehouse IntegrationSoftware Independently Analyzed with Annual Sales Figures inUS$ Million for Years 2004 through 2009 (includescorresponding Graph/Chart) III-51

    Table 29: French 14-Year Perspective for Data WarehouseManagement Market by Product Segments - Percentage Breakdownof Dollar Sales for Data Warehouse Database ManagementSoftware & Data Warehouse Integration Software Segments forYears 2005, 2013, and 2018 (includes correspondingGraph/Chart) III-52

    4b. GERMANY III-53A.Market Analysis III-53Strategic Corporate Developments III-53B.Market Analytics III-54Table 30: German Recent Past, Current & Future Analysis forData Warehouse Management by Product Segment - DataWarehouse Database Management Software & Data WarehouseIntegration Software Independently Analyzed with AnnualSales Figures in US$ Million for Years 2010 through 2018(includes corresponding Graph/Chart) III-54

    Table 31: German Historic Review for Data WarehouseManagement Market by Product Segments - Data WarehouseDatabase Management Software & Data Warehouse IntegrationSoftware Independently Analyzed with Annual Sales Figures inUS$ Million for Years 2004 through 2009 (includescorresponding Graph/Chart) III-55

    Table 32: German 14-Year Perspective for Data WarehouseManagement Market by Product Segments - Percentage Breakdownof Dollar Sales for Data Warehouse Database ManagementSoftware & Data Warehouse Integration Software Segments forYears 2005, 2013, and 2018 (includes correspondingGraph/Chart) III-56

    4c. ITALY III-57Market Analysis III-57Table 33: Italian Recent Past, Current & Future Analysis forData Warehouse Management by Product Segment - DataWarehouse Database Management Software & Data WarehouseIntegration Software Independently Analyzed with AnnualSales Figures in US$ Million for Years 2010 through 2018(includes corresponding Graph/Chart) III-57

    Table 34: Italian Historic Review for Data WarehouseManagement Market by Product Segments - Data WarehouseDatabase Management Software & Data Warehouse IntegrationSoftware Independently Analyzed with Annual Sales Figures inUS$ Million for Years 2004 through 2009 (includescorresponding Graph/Chart) III-58

    Table 35: Italian 14-Year Perspective for Data WarehouseManagement Market by Product Segments - Percentage Breakdownof Dollar Sales for Data Warehouse Database ManagementSoftware & Data Warehouse Integration Software Segments forYears 2005, 2013, and 2018 (includes correspondingGraph/Chart) III-59

    4d. UNITED KINGDOM (UK) III-60A.Market Analysis III-60Product Launches III-60B.Market Analytics III-61Table 36: UK Recent Past, Current & Future Analysis for DataWarehouse Management by Product Segment - Data WarehouseDatabase Management Software & Data Warehouse IntegrationSoftware Independently Analyzed with Annual Sales Figures inUS$ Million for Years 2010 through 2018 (includescorresponding Graph/Chart) III-61

    Table 37: UK Historic Review for Data Warehouse ManagementMarket by Product Segments - Data Warehouse DatabaseManagement Software & Data Warehouse Integration SoftwareIndependently Analyzed with Annual Sales Figures in US$Million for Years 2004 through 2009 (includes correspondingGraph/Chart) III-62

    Table 38: UK 14-Year Perspective for Data WarehouseManagement Market by Product Segments - Percentage Breakdownof Dollar Sales for Data Warehouse Database ManagementSoftware & Data Warehouse Integration Software Segments forYears 2005, 2013, and 2018 (includes correspondingGraph/Chart) III-63

    4e. SPAIN III-64Market Analysis III-64Table 39: Spain Recent Past, Current & Future Analysis forData Warehouse Management by Product Segment - DataWarehouse Database Management Software & Data WarehouseIntegration Software Independently Analyzed with AnnualSales Figures in US$ Million for Years 2010 through 2018(includes corresponding Graph/Chart) III-64

    Table 40: Spain Historic Review for Data WarehouseManagement Market by Product Segments - Data WarehouseDatabase Management Software & Data Warehouse IntegrationSoftware Independently Analyzed with Annual Sales Figures inUS$ Million for Years 2004 through 2009 (includescorresponding Graph/Chart) III-65

    Table 41: Spain 14-Yea

    To order this report:Logistics_and_Freight Industry: Global Data Warehouse Management Software Industry

    Contact Clare: clare@reportlinker.com US:(339) 368 6001 Intl:+1 339 368 6001

    SOURCE Reportlinker

    Copyright (C) 2013 PR Newswire. All rights reserved


    Using Hadoop to Augment Data Warehouses with Big Data Capabilities | killexams.com real questions and Pass4sure dumps

    If you run a data warehouse at your organization, you may be wondering how the latest big data technologies, such as Hadoop, can benefit your information analysis. According to IBM product manager Vijay Ramaiah, there are several ways that Hadoop and related tools can augment an existing data warehouse and deliver new analytical capabilities along the way.

    Organizations that have already invested lots of time and money into building a data warehouse may be good candidates for augmenting their warehouse with a Hadoop-based system if they face one of several circumstances, Ramaiah, who is the product manager for IBM’s big data portfolio, says in a recent video.

    When an organization is “drowning” in big data or throwing away data because it lack the capability to store and process it, that may signify a good time to front-end an existing data warehouse with a Hadoop repository include, Ramaiah says. Similarly, if an organization is using the warehouse to store all data, including cold or rarely accessed data, they may be better off shunting that data over to Hadoop. Organizations that want to analyze non-operational data; that want to explore large and complex sets of data; or that are looking to delay a data warehouse upgrade are also good candidates.

    One effective way of using of Hadoop with an existing data warehouse is to use Hadoop as a “landing zone” for big, raw data, Ramaiah says. “Instead of taking all this directly into your warehouse or other aspects of your enterprise environment, what if you could bring all this data, land it in Hadoop, use it as a place where you can do some pre-processing of this data, and then determine if you take it on to other systems?” he asks in the video.

    The second common job for Hadoop in existing data warehousing environments is using Hadoop to perform data discovery and analytics on combinations of structured, semi-structured, and unstructured data, including real-time streaming data (possibly in conjunction with IBM’s text analytics engine). Since most data warehouses require structured data, this is an area where Hadoop and other big data tools can bring net new capabilities to an organization.

    The third common way customers with existing data warehouses use Hadoop is by using their existing query tools against the columnar data store. “It’s a very effective way to do analytics,” Ramaiah says. “The MapReduce technology provides great performance. What would previously take you weeks and days now takes minutes and hours.”

    Ramaiah advises organizations to start small with their Hadoop-based data warehouse augmentations, and grow from there. Given the large volume, velocity, and variety of big data, most projects will benefit from master data management (MDM) and data lifecycle management tools.

    Organizations can assemble the various components they need as projects and budgets dictate, eliminating the need for a “big bang” big data project, according to Ramaiah. IBM’s distribution of the open source Hadoop database, dubbed InfoSphere BigInsights, includes additional components and capabilities in the areas of text analytics, performance and workload optimization, data visualization, developer and administrative workbenches, enterprise application connectors and accelerators, and security.

    Other big data products from Big Blue that might be used in a data warehouse augmentation project may include InfoSphere Information Server, Optim, and Guardium.

    Related items:

    Hadoop Sharks Smell Blood; Take Aim at Status Quo

    Hadoop Distros Orbit Around Solr

    The Transformational Role of the CIO in the New Era of Analytics


    An introduction to Data Quality | killexams.com real questions and Pass4sure dumps

    1. What is Data Quality?

    There are many definitions of data quality, in general, data quality is the assessment of how much the data is usable and fits its serving context.

    Many factors helps measuring data quality such as:

  • Data Consistency: Violation of semantic rules defined over the dataset. [1].
  • Data Accuracy: Data are accurate when data values stored in the database correspond to real-world values. [1]
  • Data Uniqueness: A measure of unwanted duplication existing within or across systems for a particular field, record, or data set. [2]
  • Data Completeness: The degree to which values are present in a data collection. [1]
  • Data Timeliness: The extent to which age of the data is appropriated for the task at hand. [3]
  • Other factors can be taken into consideration [4] such as Availability, Ease of Manipulation, Believability, and Currency.

    2. Why Data Quality is Important?

    Enhancing the data quality is a critical concern as data is considered as the core of all activities within organizations, poor data quality leads to inaccurate reporting which will result inaccurate decisions and surely economic damages.

    3. How to improve Data Quality?

    Data quality improvement is achieved by:

  • Training Staff
  • Implementing data quality solutions
  • 3.1. Training Staff

    Before thinking about implementing data quality solutions, first they must minimize the data quality problems resulted by in-organization human activities such as data entry. Also all developers and database administrators must have a good knowledge of the business process and must refer to a unified schema when developing and designing databases and applications. [5]

    3.2. Implementing data quality solutions

    The other way to improve data quality is by implementing data quality solutions. Data quality solutions is a set of tools or application that perform quality tasks such as:

  • Knowledge base creation: a knowledge base is a machine-readable resource for the dissemination of information. [6]
  • Data de-duplication: Remove duplicated information based on a set of semantic rules.
  • Data cleansing: Removing unwanted characters and symbols from values.
  • Data profiling: is the process of examining the data available from an existing information source (e.g. a database or a file) and collecting statistics or informative summaries about that data. [7]
  • Data matching: Data matching describes efforts to compare two sets of collected data using technologies such as Record Linkage and Entity resolution. [8]
  • 4. Popular data quality solutions

    In this section, i will show some of the most popular data quality solutions in the market.

    4.1. IBM Infosphere information server

    IBM InfoSphere® Information Server is a market-leading data integration platform, which includes a family of products that enable you to understand, cleanse, monitor, transform and deliver data, and to collaborate to bridge the gap between business and IT. InfoSphere Information Server provides massively parallel processing (MPP) capabilities to deliver a highly scalable and flexible integration platform that handles all data volumes, big and small.

    InfoSphere Information Server provides you with the ability to flexibly meet your unique information integration requirements — from data integration to data quality and data governance — to deliver trusted information to your mission-critical business initiatives (such as big data and analytics, data warehouse modernization, master data management and point-of-impact analytics). [9]

    4.2. Informatica Data Quality

    Informatica Data Quality delivers trustworthy data to all stakeholders, projects, and data domains for all business applications on premise or in the cloud. [10]

    4.3. Oracle Data Quality

    Oracle Enterprise Data Quality delivers a complete, best-of-breed approach to party and product data resulting in trustworthy master data that integrates with applications to improve business insight. [11]

    4.4. Microsoft Data Quality Services

    SQL Server Data Quality Services (DQS) is a knowledge-driven data quality product. DQS enables you to build a knowledge base and use it to perform a variety of critical data quality tasks, including correction, enrichment, standardization, and de-duplication of your data. DQS enables you to perform data cleansing by using cloud-based reference data services provided by reference data providers. DQS also provides you with profiling that is integrated into its data-quality tasks, enabling you to analyze the integrity of your data. [12]

    4.5. Melissa Data Quality

    Since 1985, Melissa has been providing enterprise data quality tools with wide capabilities including data profiling and standardization, cleansing, enriching, linking and deduping. Their mission is to provide organizations with best-of-breed solutions that deliver trusted, reliable, accurate information for greater insight. [10]

    4.6. Talend Data Quality

    Talend’s enterprise data quality tool profiles, cleanses, and masks data, while monitoring data quality over time, in any format or size. Data de-duplication, validation, and standardization creates clean data for access, reporting, analytics, and operations. Enrich data with external sources for postal validation, business identification, credit score information, and more. [13]

    4.7. Syncsort Trillium Software Lead

    Syncsort’s Trillium Cloud delivers an industry-leading enterprise data quality solution with the deployment ease and operational flexibility of a Syncsort-administered hardened, secure colud environment. [14]

    4.8. SAS Data Quality

    The SAS Data Quality software enables you to improve the consistency and integrity of your data. When you increase the quality of your data, you increase the value of your analytical results.

    The SAS Data Quality software supports a variety of data quality operations. The data quality operations employ predefined rules that apply to the specific context of your data (such as names or street addresses). Examples of data quality operations include casing, parsing, fuzzy matching, and standardization. [15]

    5. References
  • [1] C. Batini, C. Cappiello, C. Francalanci, A. Maurino, “Methodologies for data quality assessment and improvement,” ACM Computing Surveys (CSUR), vol. 41, p. 16, 2009.
  • [2] D. McGilvray, “Ten Steps to Quality Data and Trusted Information,” MIT Information Quality Industry Symposium, 2008.
  • [3] R. Y. W. a. D. M. Strong, “Beyond accuracy: What data quality means to data consumers,” Journal of management information systems, vol. 12, pp. 5–33, 1996.
  • [4] Sidi Fatimah,Shariat Panahy, Payam Hassany, Lilly Suriani Affendey, Marzanah A. Jabar, Hamidah Ibrahim, Aida Mustapha, “Data quality: A survey of data quality dimensions,” in Proceedings — 2012 International Conference on Information Retrieval and Knowledge Management, CAMP’12, 2012.
  • [5] Herzog, Thomas N.,scheuren, f.j, winkler, “What Is Data Quality and Why Should They Care,” Journal of Industrial Engineering and Management, vol. 4(2), no. 2nd edition, pp. 1–9, 2016.
  • [6] M. Rouse, “Knowledge Base,” TechTarget, 3 2007. [Online]. Available: https://searchcrm.techtarget.com/definition/knowledge-base. [Accessed 9 12 2018].
  • [7] “Data Profiling,” Wikipedia, [Online]. Available: https://en.wikipedia.org/wiki/Data_profiling. [Accessed 9 12 2018].
  • [8] “What is Data Matching?,” Techopedia, [Online]. Available: https://www.techopedia.com/definition/28041/data-matching. [Accessed 9 12 2018].
  • [9] “IBM Information Server,” IBM, [Online]. Available: https://www.ibm.com/analytics/information-server. [Accessed 9 12 2018].
  • [10] “Best Data Quality Software,” G2Crowd, [Online]. Available: https://www.g2crowd.com/categories/data-quality. [Accessed 9 12 2018].
  • [11] “Oracle Enterprise Data Quality,” Oracle, [Online]. Available: http://www.oracle.com/us/products/middleware/data-integration/enterprise-data-quality/overview/index.html. [Accessed 12 9 2018].
  • [12] “Data Quality Services,” Microsoft, 10 12 2013. [Online]. Available: https://docs.microsoft.com/en-us/sql/data-quality-services/data-quality-services?view=sql-server-2017. [Accessed 12 9 2018].
  • [13] “Data Quality,” Talend, [Online]. Available: https://www.talend.com/products/data-quality/. [Accessed 9 12 2018].
  • [14] “Trillium Software,” Syncsort, [Online]. Available: http://www.syncsort.com/en/About/Trillium-Software. [Accessed 9 12 2018].
  • [15] “SAS Data Quality and Data Quality Server,” SAS, [Online]. Available: http://support.sas.com/software/products/dataqual/index.html. [Accessed 9 12 2018]


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    coursehero.com : "Excel"
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