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00M-226 IBM Smart Analytics Sales Mastery Test v1

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00M-226 exam Dumps Source : IBM Smart Analytics Sales Mastery Test v1

Test Code : 00M-226
Test Name : IBM Smart Analytics Sales Mastery Test v1
Vendor Name : IBM
: 34 Real Questions

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IBM IBM Smart Analytics Sales

IBM Q1 revenue Surpass Estimates, Revenues miss, Down Y/Y | killexams.com Real Questions and Pass4sure dumps

foreign business Machines Corp IBM delivered first-quarter 2019 non-GAAP profits of $4.87 per share, which surpassed the Zacks Consensus Estimate of $2.21. besides the fact that children, revenue per share (EPS) decreased 8.2% from the 12 months-in the past quarter.

Revenues of $18.18 billion ignored the Zacks Consensus Estimate of $18.52 billion and declined four.7% on a yr-over-yr foundation. At regular currency (cc), the metric dipped 0.9%. The 12 months-over-12 months income decline can primarily be attributed to currency fluctuation and headwinds from IBM Z product cycle. also, softness within the emerging markets of Asia Pacific affected the right-line efficiency.

specifically, IBM mentioned that signings declined 14% on cc groundwork within the first quarter to $7.6 billion. functions backlog declined 2% year over year and totaled $111.6 billion.

In a year’s time, shares of IBM have lost 2.5% in comparison with the industry’s 0.5% decline.

 

Geographic salary details

Revenues from Americas reduced 1% on cc foundation, reflecting the headwind from the IBM Z product cycle. The same from Europe, core-East and Africa were flat yr over 12 months, whereas Asia-Pacific revenues declined 2% on a 12 months-over-year basis.

Structural adjustments

starting from first-quarter 2019, IBM combined Cloud enterprise and Cognitive utility in one section.  additional, the business merged security features with protection utility.

IBM also integrated all divested enterprise to the other classes with a purpose to supply greater transparency to the application and GBS segments. The divested business includes pending earnings of seven utility items to HCL, the sale of IBM’smarketing platform and commerce application choices to Centerbridge and the currently concluded sale of Seterus personal loan servicing business.

Cloud & Cognitive software section

The Cloud & Cognitive utility section’s revenues-external enhanced 2% year over year (on cc basis) to $5 billion. Revenues at Cloud & Cognitive utility (together with cloud and statistics platform, Cognitive application and transaction processing) extended essentially due to boom in application driven by way of security and solutions, boom in statistics and analytics in addition to synthetic intelligence (AI).

Segmental revenues bearing on Cloud elevated 10%. Cloud as-a-carrier earnings annual run expense became $2.1 billion.

Revenues from cloud and statistics systems increased 2% yr over year.

IBM stated that the combination of AI into choices like client experience analytics in commerce area and accelerated adoption of IBM Cloud private, which is developed on Linux containers and kubernetes. It additionally added that analytics performed well in the quarter under evaluation, courtesy of information science offerings and IBM Cloud inner most for records offering.

furthermore, IBM witnessed increase in trade verticals like fitness, key areas of analytics and protection within the quarter. Watson fitness witnessed vast-based mostly increase in Payer, issuer, Imaging and existence Sciences domains.

Revenues from Cognitive applications have been up 4% 12 months over year, pushed with the aid of protection, health, deliver chain and weather. protection increase was backed by means of choices in orchestration, facts protection and endpoint management.

Transaction Processing application contains software that runs mission-vital workloads, leveraging IBM’s hardware structures. Revenues have been flat on a year-over-yr foundation.

Story continues

global business features section

Revenues from global business functions-exterior segment totaled $four.1 billion, up 4% from the yr-in the past quarter. The yr-over-year raise in the exact line became primarily because of increase throughout all three company areas namely consulting, utility management and international process services.

Cloud revenues surged 25% yr over 12 months. Cloud as-a-provider profits annual run fee changed into $1.eight billion.

utility administration revenues have been flat yr over year. world manner services revenues climbed 5%. additionally, Consulting revenues elevated 9% 12 months over yr on solid performance of IBM’s digital business.

global expertise capabilities phase

Revenues from technology capabilities-external reduced three% from the 12 months-in the past quarter to $6.9 billion. Segmental revenues pertaining to cloud surged 13% from the 12 months-in the past quarter. Cloud as-a-provider earnings annual run cost changed into $7.5 billion.

Infrastructure & Cloud functions’ revenues decreased three% from the year-in the past quarter. also, Technical aid functions revenues declined 2% from the yr-in the past quarter.

programs Revenues

programs revenues reduced 9% on a year-over-year foundation to $1.3 billion, basically because of the impact of the IBM Z product cycle and stiff competitors. Segmental revenues touching on Cloud revenues declined 15%.

IBM Z revenues lowered 38% 12 months over 12 months.

youngsters, vigor revenues extended 9% from the year-in the past quarter. The upside can be especially attributed to Linux and mighty adoption throughout the newest POWER9-based structure.

meanwhile, storage hardware revenues declined on vulnerable performance in each high conclusion and mid-latitude, partly offset by means of potent growth in All Flash Arrays. IBM stated that pricing drive in the immensely competitive storage market is hurting revenues.

while working systems application revenues expanded 5%, programs Hardware slumped 14% from the 12 months-ago quarter.

at last, global Financing (includes financing and used gadget sales) revenues lowered 19% 12 months over 12 months and 9% at cc to $417 million.

operating particulars

Non-GAAP gross margin extended 100 foundation points (bps) from the yr-ago quarter and came in at forty four.7%. The gross margin benefited basically from a hundred and sixty bps growth in capabilities margin.

working expense (analysis & building prices and selling, conventional and administration expenses) declined 10.6% 12 months over year on attention of acquisition synergies and improving operational efficiencies. at the moment, IBM continues to put money into abruptly starting to be fields like hybrid cloud, synthetic intelligence (AI), safety and blockchain.

Pre-tax margin from continuing operations elevated 320 bps on a 12 months-over-year foundation to 12.three%.

Non-GAAP operating margins from carrying on with operations shrunk ninety bps and came in at eleven%.

stability Sheet & money circulation particulars

IBM ended first-quarter 2019 with $18 billion in total money and marketable securities compared with $11.9 billion within the outdated quarter. complete debt (including present portion) become $49.9 billion, up from $forty five.8 million from the old quarter.

IBM said cash flow from operations (except world Financing receivables) of $4.eight billion and generated free cash circulate of $1.7 billion within the quarter under review.

additionally, the business back $2.three billion to its shareholders through dividends and share repurchases. The enterprise again more than $10.three billion to its shareholders via dividends and share repurchases for the total yr.

at the end of the yr, the company had $2.4 billion remaining below latest buyback authorization.

suggestions

For 2019, IBM continues to predict non-GAAP EPS to be at the least $13.90. The Zacks Consensus Estimate is currently pegged at $13.90.

IBM nevertheless anticipates 2019 free cash circulation of $12 billion.

Zacks Rank & shares to accept as true with

IBM at the moment contains a Zacks Rank #four (sell).

Few more advantageous-ranked stocks within the broader expertise sector are Yelp Inc. YELP, Xilinx, Inc. XLNX and normal screen company OLED, every sporting a Zacks Rank #1 (strong buy). which you could see the complete checklist of today’s Zacks #1 Rank shares right here.

The long-time period income increase fee for Yelp, Xilinx and standard reveal is presently pegged at 18.6%, 12% and 30%, respectively.

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Is your investment marketing consultant fumbling your financial future?See the right way to more without problems shelter your retirement with a brand new particular document, “4 Warning signs Your investment consultant may be Sabotaging Your monetary Future.” click to get your free record. overseas business Machines company (IBM) : Free stock evaluation file Yelp Inc. (YELP) : Free inventory evaluation report usual screen organisation (OLED) : Free stock evaluation record Xilinx, Inc. (XLNX) : Free stock evaluation document To read this article on Zacks.com click here.


IBM Vet Peter Porter Named Oracle Federal system income Director | killexams.com Real Questions and Pass4sure dumps

Peter Porter

Peter Porter, formerly an authorized client government at IBM‘s (NYSE: IBM) public sector enterprise, joined Oracle (ORCL) as director of federal device income, G2Xchange and many others mentioned Monday.

He has more than 30 years of know-how revenue journey and is accountable for main a group of gurus that offers Oracle techniques to federal civilian companies.

Porter held a 29-yr profession at IBM, where he in the past managed the firm’s company construction efforts focused on the U.S. Postal carrier and income of the IBM Smarter Cities portfolio.

prior in his corporate career, he worked in revenue positions at Tektronix and Hewlett-Packard.

determine also

The branch of health and Human features has issued a solicitation for a potential 5-yr, …

A general Dynamics (NYSE: GD) business unit has received a $125M contract change from the …


IBM Q1 shows techniques Drag whereas firm Reaches toward The Cloud (And Blockchain) | killexams.com Real Questions and Pass4sure dumps

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Blockchain acquired a number of mentions all over IBM’s conference call with analysts after revenue have been released Tuesday (April 16) after the markets closed. artificial intelligence (AI) got extra publicity, tied in part to the continuing approach of embracing the cloud.

in terms of headline numbers, adjusted profits per share got here in at $2.25, beating expectations through three pennies.

Revenues neglected expectations, at $18.2 billion; the road had been looking for $18.5 billion. The latest top-line tally marked a 5 percent decline from a yr in the past, and persisted the reconfiguring of certain enterprise lines and outright income of alternative contraptions. by means of illustration, all over the quarter, the tech significant sold its loan servicing enterprise to Mr. Cooper community. And in the newest quarter, IBM changed the way it reports results – what was once the technology features & Cloud systems segment is now the Cloud & Cognitive application and global know-how services phase.

The global know-how capabilities section – tied to tech infrastructure and support of that infrastructure – noticed revenues of $6.9 billion, down 7 p.c. enterprise capabilities have been $4.1 billion, roughly flat. techniques income slipped 11 p.c as mainframe and other hardware demand slid, and demand seemed gentle in emerging markets. CFO James Kavanaugh pointed to the Asia Pacific (AP) vicinity, which saw profits deceleration.

The cloud and cognitive utility outcomes, which center of attention on cloud records and transactions, also saw profits declines, albeit greater muted, with $5 billion in revenue, off 1.5 p.c year on year. The company does not get away the salary contribution of efforts which are driven with the aid of and embody AI or blockchain.

separate from the name and the latest effects, in the past it has been cited that IBM has filed for a few blockchain-related patents. as an example, the company referred to it has worked with the shipping firm Maersk to support streamline foreign logistics. The collaboration, known as TradeLens, uses smart contracts to address expenses of lading and different documentation utilized in freight. before that announcement, IBM pointed out it is working with Walmart to enrich the latter’s meals business give chain.

In extra detail on first-quarter consequences, Kavanaugh spoke of the business in well-known had “robust performance in offerings that help consumers with their digital transformation and journeys to cloud.” Cloud growth accelerated to 12 p.c, measured in consistent forex, mentioned the government.

Cloud revenues are at $19.5 billion through the past year, pointed out administration. software earnings have been pushed through hybrid cloud products (with facts and AI structures), protection and solution and areas like supply chain and Watson fitness.

“These offerings are increasingly being infused with AI after which transaction processing systems, together with the middleware and database application that helps their valued clientele’ mission-important workloads,” pointed out Kavanaugh.

management noted that when it comes to concrete examples of demand for cloud and business automation – and as is germane to funds – one European tax authority is using the company’s digital company automation platform to “re-design their tax processes round their data lake and improve the tax payor adventure.”

——————————–

newest Insights: 

Our statistics and analytics crew has developed a couple of artistic methodologies and frameworks that measure and benchmark the innovation that’s reshaping the payments and commerce ecosystem. check out their April 2019 Unattended Retail report. 

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The Best Self-Service Business Intelligence (BI) Tools of 2018 | killexams.com real questions and Pass4sure dumps

Analytics Beyond Spreadsheets

For many years, Microsoft Excel and other spreadsheets were the tools of choice for business professionals who were looking to visualize their data. But spreadsheets had their limits for many business intelligence (BI)-related tasks. Even today, trying to creating charts analyzing complex datasets in Excel can still be frustrating. Sometimes you start with the wrong kind of data, for example, or you may not know how to manipulate the spreadsheet to create the data visualization{{/ZIFFARTICLE} you need. On the other hand, the rising tide of data democratization is giving everyone in an organization access to corporate data. The need has arisen for effective tools that people of all skill levels can use to make sense of the wealth of information created by businesses every single day.

Spreadsheets also fall down when the data isn't well-structured or can't be sorted out in neat rows and columns. And, if you have millions of rows or very sparse matrices, then the data in a spreadsheet can be painful to enter and it can be hard to visualize your data. Spreadsheets also have issues if you are trying to create a report that spans multiple data tables or that mixes in Structured Query Language (SQL)-based databases, or when multiple users try to maintain and collaborate on the same spreadsheet.

A spreadsheet containing up-to-the-minute data can also be a problem, particularly if you have exported graphics that need to be refreshed when the data changes. Finally, spreadsheets aren't good for data exploration; trying to spot trends, outlying data points, or counterintuitive results is difficult when what you are looking for is often hidden in a long row of numbers.

While spreadsheets and self-service BI tools both make use of tables of numbers, they are really acting in different arenas with different purposes. A spreadsheet is first and foremost a way to store and display calculations. While some spreadsheets can create very sophisticated mathematical models, at their core it is all about the math more than the model itself.

This is all a long-winded way of saying that when businesses use a spreadsheet, they are actively sabotaging themselves and their ability to consistently get valuable insights from their data. BI tools are specficially designed to help businesses better understand their data, and can prove to be a huge benefit to those upgrading from what a limited spreadsheet can do.

What Is Business Intelligence?

Defining BI is tricky. When you examine what it does and why companies use it, it can start to sound vague and nebulous. After all, many different kinds of software offer analytics features, and all businesses want to improve. Understanding what a BI is or isn't can be unclear.

BI is an umbrella term meant to cover all of the activities necessary for a company to turn raw information into actionable knowledge. In other words, it's a company's efforts to understand what it knows and what it doesn't know of its own existence and operations. The ultimate goal is being able to increase profits and sharpen its competitive edge.

Framed that way, BI as a concept has been around as long as business. But that concept has evolved from early basics [like Accounts Payable (AP) and Accounts Receivable (AR) reports and customer contact and contract information] to much more sophisticated and nuanced information. This information ranges across everything from customer behaviors to IT infrastructure monitoring to even long-term fixed asset performance. Separately tracking such metrics is something most businesses can do regardless of the tools employed. Combining them, especially disparate results from metrics normally not associated with one another, into understandable and actionable information, well, that's the art of BI. The future of BI is already shaping up to simultaneously broaden the scope and variety of data used and to sharpen the micro-focus to ever finer, more granular levels.

BI software has been instrumental in this steady progression towards more in-depth knowledge about the business, competitors, customers, industry, market, and suppliers, to name just a few possible metric targets. But as businesses grow and their information stores balloon, the capturing, storing, and organizing of information becomes too large and complex to be entirely handled by mere humans. Early efforts to do these tasks via software, such as customer relationship management (CRM) and enterprise resource planning (ERP), led to the formation of "data silos" wherein data was trapped and useful only within the confines of certain operations or software buckets. This was the case unless IT took on the task of integrating various silos, typically through painstaking and highly manual processes.

While BI software still covers a variety of software applications used to analyze raw data, today it usually refers to analytics for data mining, analytical processing, querying, reporting, and especially visualizing. The main difference between today's BI software and Big Data analytics is mostly scale. BI software handles data sizes typical for most organizations, from small to large. Big Data analytics and apps handle data analysis for very large data sets, such as silos measured in petabytes (PBs).

Self-Service BI and Data Democratization

The BI tools that were popular half a decade or more ago required specialists, not just to use but also to interpret the resulting data and conclusions. That led to an often inconvenient and fallible filter between the people who really needed to get and understand the business—the company decision makers—and those who were gathering, processing, and interpreting that data—usually data analysts and database administrators. Because being a data specialist is a demanding job, many of these folks were less well-versed in the actual workings of the business whose data they were analyzing. That led to a focus on data the company didn't need, a misinterpretation of results, and often a series of "standard" reporting that analysts would run on a scheduled basis instead of more ad hoc intelligence gathering and interpretation, which can be highly valuable in fast-moving situations.

This problem has led to a growing new trend among new BI tools coming onto the market today: that of self-service BI and data democratization. The goal for much of today's BI software is to be available and usable by anyone in the organization. Instead of requesting reports or queries through the IT or database departments, executives and decision makers can create their own queries, reports, and data visualizations through self-service models, and connect to disparate data both within and outside the organization through prebuilt connectors. IT maintains overall control over who has access to which tools and data through these connectors and their management tool arsenal, but IT no longer acts as a bottleneck to every query and report request.

As a result, users can take advantage of this distributed BI model. Key tools and critical data have moved from a centralized and difficult-to-access architecture to a decentralized model that merely requires access credentials and familiarity with new BI software. This results in a whole new kind of analysis becoming available to the organization, namely, that of experienced, front-line business people who not only know what data they need but how they need to use it.

The emerging crop of BI tools all work hard at developing front-end tools that are more intuitive and easier to use than those of older generations—with varying degrees of success. However, that means a key criteria in any BI tool purchasing decision will be to evaluate who in the organization should access such tools and whether the tool is appropriately designed for that audience. Most BI vendors indicate they're looking for their tool suites to become as ubiquitous and easy to use for business users as typical business collaboration tools or productivity suites, such as Microsoft Office. None have gotten quite that far yet in my estimation, but some are closer than others. To that end, these BI tool suites tend to focus on three core types of analytics: descriptive (what did happen), prescriptive (what should happen now), and predictive (what will happen later).

What Is Data Visualization?

In the context of BI software, data visualization is a fast and effective method of transferring information from a machine to a human brain. The idea is to place digital information into a visual context so that the analytic output can be quickly ingested by humans, often at a glance. If this sounds like those pie and bar charts you've seen in Microsoft Excel, then you're right. Those are early examples of data visualizations.

But today's visualization forms are rapidly evolving from those traditional pie charts to the stylized, the artistic, and even the interactive. An interactive visualization comes with layered "drill downs," which means the viewer can interact with the visual to reach more granular information on one or more aspects incorporated in the bigger picture. For example, new values can be added that will change the visualization on the fly, or the visualization is actually built on rapidly changing data that can turn a static visual into an animation or a dashboard.

The best visualizations do not seek artistic awards but instead are designed with function in mind, usually the quick and intuitive transfer of information. In other words, the best visualizations are simple but powerful in clearly and directly delivering a message. High-end visuals may look impressive at first glance but, if your audience needs help to understand what's being conveyed, then they've ultimately failed.

Most BI software, including those reviewed here, comes with visualization capabilities. However, some products offer more options than others so, if advanced visuals are key to your BI process, then you'll want to closely examine these tools. There are also third-party and even free data visualization tools that can be used on top of your BI software for even more options.

Products and Testing

In this review roundup, I tested each product from the perspective of a business analyst. But I also kept in mind the viewpoint of users who might have no familiarity with data processing or analytics. I loaded and used the same data sets and posed the same queries, evaluating results and the processes involved.

My aim was to evaluate cloud versions alone, as I often do analysis on the fly or at least on a variety of machines, as do legions of other analysts. But, in some cases, it was necessary to evaluate a desktop version as well or instead of the cloud version. One example of this is Tableau Desktop, a favorite tool of Microsoft Excel users who simply have an affinity for the desktop tool (and who just move to the cloud long enough to share and collaborate).

I ended up testing the Microsoft Power BI desktop version, too, on a Microsoft representative's recommendation because, as the rep said, "the more robust data prep tools are there." Besides, said the rep, "most users prefer the desktop tool over a web tool anyway." Again, I don't doubt Microsoft's claim but that does seem weird to me. I've heard it said that desktop tools are preferred when the data is local as the process feels faster and easier. But seriously, how much data is truly local anymore? I suspect this odd desktop tool preference is a bit more personal than fact-based, but to each his own.

Then there's Google Analytics, a pure cloud player. The tool is designed to analyze website and mobile app data so it's a different critter in the BI app zoo. That being the case, I had to deviate from using my test data set and queries, and instead test it in its natural habitat of website data. Nonetheless, it's the processes that are evaluated in this review, not the data.

While I didn't test any of these tools from a data scientist's role, I did mention advanced capabilities when I found them, simply to let buyers know they exist. IBM Watson Analytics is one tool with the ability to extend to highly advanced features and was also one of the easiest to use upfront. IBM Watson Analytics is well-suited for business analysts and for widespread data democratization because it requires little, if any, knowledge of data science. Instead, it works well by using natural language and keywords to form queries, a characteristic that can make it valuable to practically anyone. It's highly intuitive, very powerful, and easy to learn. Microsoft Power BI is a strong second as it, too, is powerful while also familiar, certainly to any of the millions of Microsoft business users. However, there are several other powerful and intuitive apps in this lineup from which to choose; they all have their own pros and cons. We'll be adding even more in the coming months.

One thing to watch out for during your evaluations of these products is that many don't yet handle streaming data. For many users, that won't be a problem in the immediate future. However, for those involved with analyzing business processes as they happen, such as website performance metrics or customer behavior patterns, streaming data can be invaluable. Also, the Internet of Things (IoT) will drive this issue in the near future and make streaming data and streaming analytics a must-have feature. Many of these tools will have to up their game accordingly so, unless you want to jump ship in a year or two, it's best to think ahead when considering BI and the IoT.

BI and Big Data

Another area in which self-service BI is taking off is in analyzing Big Data. This is a newer development in the database space but it's driving tremendous growth and innovation. The name is an apt descriptor because Big Data generally refers to huge data sets that are simply too big to be managed or queried with traditional data science tools. What's created these behemoth data collections is the explosion of data-generating, tracking, monitoring, transaction, and social media tools (to name a few) that have become so popular over the last several years.

Not only do these tools generate loads of new data, they also often generate a new kind of data, namely "unstructured" data. Broadly speaking, this is simply data that hasn't been organized in a predefined way. Unlike more traditional, structured data, this kind of data is heavy on text (even free-form text) while also containing more easily defined data, such as dates or credit card numbers. Examples of apps that generate this kind of data include the customer behavior-tracking tools you use to see what your customers are doing on your e-commerce website, the piles of log and event files generated from some smart devices (such as alarms and smart sensors), and broad-swath social media tracking tools.

Organizations deploying these tools are being challenged not only by a sudden deluge of unstructured data that quickly strains storage resources [think beyond terabytes (TB) into the PB and even exabyte (EB) range] but, even more importantly, they're finding it difficult to query this new information at all. Traditional data warehouse tools generally weren't designed to either manage or query unstructured data. New data storage innovations such as data lakes are emerging to solve for this need, but organizations still relying exclusively on traditional tools while deploying front-line apps that generate unstructured data often find themselves sitting on mountains of data they don't know how to leverage.

Enter Big Data analysis standards. The golden standard here is Hadoop, which is an open-source software framework that Apache specifically designed to query large data sets stored in a distributed fashion (meaning, in your data center, the cloud, or both). Not only does Hadoop let you query Big Data, it lets you simultaneously query both unstructured as well as traditional structured data. In other words, if you want to query all of your business data for maximum insight, then Hadoop is what you need.

You can download and implement Hadoop itself to perform your queries, but it's typically easier and more effective to use commercial querying tools that employ Hadoop as the foundation of more intuitive and full-featured analysis packages. Notably, most of the tools reviewed here, including Chartio, IBM Watson Analytics, Microsoft Power BI, and Tableau Desktop, all support this. However, each requires varying levels of configuration or even add-on tools to do so—with IBM, Microsoft, and Tableau offering exceptionally deep capabilities. However, both IBM and Microsoft will still expect customers to utilize additional tools around aspects such as data governance to ensure optimal performance.

Finding the Right BI Tool

Given the issues spreadsheets can have when used as ad hoc BI tools and how firmly ingrained they are in their psyches, finding the right BI tool isn't a simple process. Unlike spreadsheets, BI tools have major differences when it comes to how they consume data inputs and outputs and manipulate their tables. Some tools are better at exploration than analysis, and some require a fairly steep learning curve to really make use of their features. Finally, to make matters worse, there are dozens if not hundreds of such tools on the market today, with many vendors willing to claim the self-serve BI label even if it doesn't quite fit.

Getting the overall workflow down with these tools will take some study and discussion with the people you'll be designating as users. Tableau Desktop and Microsoft Power BI, for example, will start users out with the desktop version to build visualizations and link up to various data sources. Once you have this together, you can start sharing those results online or across your organization's network. With others, such as Chartio or Google Analytics, you start in the cloud and stay there.

In recent years, companies have been taking advantage of the wide selection of online learning platforms out there to train their employees on using these platforms. As intuitive as these platforms may be, it is important to make sure that your employees actually know how to use these BI platforms so that you can make sure your investment was worthwhile. There are many ways of approaching this, but using the right online learning platform might be a good place to start looking.

Given the wide price range of these products, you should segment your analytics needs before you make any buying decision. If you want to start out slowly and inexpensively, then the best route is to try something that offers significant functionality for free, such as Microsoft Power BI. Such tools are very affordable and make it easy to get started. Plus, they tend to have large ecosystems of add-ons and partners that can be a cost-effective replacement for doing BI inside a spreadsheet. Tableau Desktop still has the largest collection of charts and visualizations and the biggest partner network, though both IBM Watson Analytics and Microsoft Power BI are catching up fast.

IBM Watson Analytics scored the highest, and Microsoft Power BI and Tableau Desktop scored the next highest in their roundup. However, all three products received their Editors' Choice award. Tableau Desktop may have a big price tag depending on which version you choose but, as previously mentioned, it has an exceptionally large and growing collection of visualizations plus a manageable learning curve if you're willing to devote some effort to it. Microsoft Power BI and Tableau Desktop also have large and growing collections of data connectors, and both Microsoft and Tableau have their own sizable communities of users that are vocal about their wants and needs. This can carry a lot of weight with the vendors' development teams so it's a good idea to spend some time looking through those community forums to get an idea where these companies are headed.

  • Pros: Extremely user-friendly. Fantastic automatic report generation. Impressive support availability.

    Cons: Automated reports can quickly become defaults. Steep learning curve that might confuse beginners.

    Bottom Line: Zoho Reports is a solid option for general business users who might not be knowledgeable in analytics software. It's also available at an attractive price.

    Read Review
  • Pros: Accessible user interface. Smart guidance features. Impressively fast analytics. Robust natural language querying.

    Cons: Unable to do real-time streaming analytics.

    Bottom Line: IBM Watson Analytics is an exceptional business intelligence (BI) app that offers a strong analytics engine along with an excellent natural language querying tool. This is one of the best BI platforms you'll find and easily takes their Editors' Choice honor.

    Read Review
  • Pros: Extremely powerful platform with a wealth of data source connectors. Very user-friendly. Exceptional data visualization capabilities.

    Cons: Desktop and web versions divide data prep tools. Refresh cycle is limited on free version.

    Bottom Line: Microsoft Power BI earns their Editors' Choice honor for its impressive usability, top-notch data visualization capabilities, and superior compatibility with other Microsoft Office products.

    Read Review
  • Pros: Enormous collection of data connectors and visualizations. User-friendly design. Impressive processing engine. Mature product with a large community of users.

    Cons: Full mastery of the platform will require substantial training.

    Bottom Line: Tableau Desktop is one of the most mature offerings on the market and that shows in its feature set. While it has a steeper learning curve than other platforms, it's easily one of the best tools in the space.

    Read Review
  • Pros: Bottlenecks are eliminated thanks to in-chip processing. Impressive natural language query in third-party applications.

    Cons: Might be too difficult for self-service business intelligence (BI). Analytics process still needs to be ironed out. Natural language capability can be limited.

    Bottom Line: Sisense is a complete platform that should be popular for experienced BI users. It may fall short for beginners, however.

    Read Review
  • Pros: Wide range of connectors. Impressive sharing features. Limitless data storage.

    Cons: User interface is not intuitive. Steep learning curve. Unwelcoming to new analysts.

    Bottom Line: Domo isn't for newcomers but for companies that already have business intelligence (BI) experience in their organization. Domo's a powerful BI tool with a lot of data connectors and solid data visualization capabilities.

    Read Review
  • Pros: Exceptional platform for website and mobile app analytics.

    Cons: Customer support has way too much automation. Focus on marketing and advertising can be frustrating to users. Relies mostly on third parties for training.

    Bottom Line: Due to its brand recognition and the fact that it's free, Google Analytics is the biggest name in website and mobile app intelligence. It has a steep learning curve but it is an awesome business intelligence tool.

    Read Review
  • Pros: Designed with general business users in mind. Solid return on investment.

    Cons: The data you can use is limited. Needs additional platform to connect.

    Bottom Line: The Salesforce Einstein Analytics Platform is designed for customer, sales, and marketing analyses, although it can server other needs, too. Its powerful analytics capabilities along with its solid natural language querying functionality and a wide array of partners make it an attractive offering.

    Read Review
  • Pros: Real-time analytics for Internet of Things (IoT) and streaming data features. Massive ecosystem with plentiful extenders. Responsive pages make mobile publishing easiest. Impressive storytelling paradigm. Centralized view with consolidated analytics.

    Cons: Data prep features are lacking. Confusing toolbar design. Not friendly for beginners.

    Bottom Line: If your business already uses SAP's HANA database platform or some of its other back-end business platforms, then SAP Analytics Cloud is a powerful, well-priced choice. But be warned that there's a steep learning curve and a noted dependence on other SAP products for full functionality.

    Read Review
  • Pros: Impressive processing engine. Powerful query optimization on SQL. Entirely web-based. Complex queries are handled very well.

    Cons: Poorly designed user interface. Steep learning curve.

    Bottom Line: Chartio excels at building a powerful analytics platform that experienced business intelligence (BI) users will appreciate. Those new to BI, however, will find it very difficult to use.

    Read Review
  • Pros: Very deep SQL modeling ability. Uses Git for version management and collaboration.

    Cons: Very expensive. Not for small teams.

    Bottom Line: Looker is a great self-service business intelligence (BI) tool that can help unify SQL and Big Data management across your enterprise.

    Read Review
  • Pros: Custom access roles. Solid collection of public data online.

    Cons: Complex pricing is a deterrent.

    Bottom Line: Qlik Sense Enterprise Server is a self-service business intelligence (BI) tool that delivers the best collection of user access roles among the BI tools they tested, and also demonstrates a promising start towards integrating Data-as-a-Service (DaaS).

    Read Review
  • Pros: One of the largest collections of data connectors. Many granular access roles.

    Cons: No free trial available. Training webinars can be costly.

    Bottom Line: The company's Focus query language is showing its age but Information Builders' self-service business intelligence (BI) tool WebFocus nevertheless has some powerful analysis features.

    Read Review
  • Pros: Very easy to get started. Nice team management and collaboration features.

    Cons: The cloud version has a subset of features found in Windows version. Online documentation could be improved.

    Bottom Line: While Tibco is still making the transition from a desktop to a cloud software vendor, its self-service business intelligence (BI) tool Tibco Spotfire is a great way to start visualizing your Excel data.

    Read Review
  • Pros: Excellent analytical support for Intuit QuickBooks. Very easy setup.

    Cons: Installation and setup is a bit of chore. No support for Intuit QuickBooks' online versions.

    Bottom Line: Clearify QQube is the best self-service business intelligence (BI) tool for in-depth analysis of your Intuit QuickBooks files, though you'll need to look elsewhere for broader BI tasks.

    Read Review

  • IBM Extends Development and Test to the IBM Cloud | killexams.com real questions and Pass4sure dumps

    ARMONK, N.Y., March 16 /PRNewswire-FirstCall/ -- IBM (NYSE: IBM) today announced plans to go online with its commercial cloud service for software development and testing. IBM, which already delivers a test and development cloud, is now allowing enterprise and government clients to test and develop on an IBM Cloud. Following a successful beta program, IBM is working with partners in cloud management, cloud security and software development and testing support to provide businesses with a unique mix of flexibility, scalability, enterprise-grade security and control for development and test on the IBM Cloud.  

    (Logo:  http://www.newscom.com/cgi-bin/prnh/20090416/IBMLOGO)

    The average enterprise devotes up to 50 percent of its entire technology infrastructure to development and test, but typically up to 90 percent of it remains idle. IBM has seen that taking advantage of cloud computing within development and testing environments can help reduce IT labor costs by 50 percent, improve quality and drastically reduce time to market.

    IBM's new Smart Business Development & Test on the IBM Cloud allows enterprise clients to expand on internal development and test efforts with instant access to resources through IBM's secure, scalable cloud delivery model, IBM software and application lifecycle management capabilities. IBM's enterprise-friendly approach to cloud complements clients' current data centers and traditional development efforts, helping clients:

  • Reduce provision cycle times from weeks to minutes
  • Eliminate software defects by up to 30 percent.
  • Reduce time required for test and quality assurance
  • Enable rapid redeployment of environments across multiple IT projects
  • PayPal, the faster, safer way to pay and get paid online, is extending its global payments platform, PayPal X into the cloud. PayPal is working with the IBM Cloud Labs to allow its ecosystem of developers to not only innovate on the IBM cloud, but to quickly monetize new applications developed and made available via smart phones. "We want to provide a very simple way to make payments available on all platforms including mobile applications," said Osama Bedier, PayPal's vice president of platform and emerging technologies. "The IBM cloud provides a platform for developers to come together as a community, to create, develop and test new applications. They look forward to seeing the payments innovations their developers create through the IBM cloud and bringing the wallet into the cloud."

    The Collaborative Software Initiative is a company that engages the power of communities to develop and deliver new high value enterprise software.  CSI has developed an advanced new collaboration portal product for its partner Spencer Trask Collaborative Innovations (STCI).  Together they deployed the system as the Department of Education's new Open Innovation Portal -- an online community connecting teachers, administrators, education experts, and charitable foundations to request, propose, and refine ideas to improve public education in the United States.  "We used IBM's cloud environment to develop, test, and now deliver this very visible application because of its focus on open technology and its inherent scalability," said Evan Bauer, CTO, The Collaborative Software Initiative.

    Partner Ecosystem

    IBM is building an ecosystem of partners to deliver the most complete and comprehensive cloud computing solutions to clients. This ecosystem comprises existing and new cloud partners in the IT industry that intend to work with IBM and complement the IBM Cloud in key areas. For example, RightScale and Kaavo can help customers manage and provision cloud resources to facilitate more effective deployment of applications and workloads in the cloud, while Navajo Systems can provide additional security for cloud-based applications and Silanis' e-signature process management can enable secure e-transactions and e-contracts. Aviarc, Wavemaker and Corent can enable development of applications on the cloud, while VMLogix can provide manual, functional, and compatibility testing; AppFirst can provide performance monitoring; or SOASTA CloudTest can deliver load and performance testing -- all taking advantage of the IBM Cloud.

    IBM Business Partner and IBM software delivery services beta participant, Trinity Software, works with federal government agencies and clients faced with complex IT administration scenarios and mandatory requirements for compliance and security when developing in the cloud. "Our customers often have barriers to scalability and limited resources for deploying quickly," said Russell Stanley, principle quality management engineer, Trinity Software Solutions. "IBM Rational's software delivery services for cloud computing can be internal or external and scaled to fit on demand, while streamlining testing with minimal overhead. With the additional reduction of risk IBM enables in the cloud, they can prioritize quality."

    New Developer Tools and Resources

    Today, IBM is also introducing new Rational software delivery lifecycle solutions in the cloud. Rational Software Delivery Services for Cloud Computing v1.0, includes a collection of Rational's market-leading products and capabilities helping clients harness the agility and flexibility of the cloud. Development and delivery teams can more effectively collaborate and quickly develop, test, and deploy new technology-based business initiatives.

    Additionally, IBM is launching a new, online cloud computing resource center on IBM developerWorks, the industry's largest technical resource with 8 million registered developers, IT professionals, and students worldwide.  The new developerWorks Cloud Computing resources provide a single point of entry to beta and production cloud environments, as well as a place for visitors to learn how to make the most of cloud computing initiatives.  

    The new resource center will include cloud articles, videos, blogs and hands-on virtual workshops for IT professionals new to cloud or interested in developing cloud infrastructures or applications. developerWorks will host cloud-focused forums and online communities and provide no-charge access to IBM software to help developers get started. The new resource center will include cloud articles, videos and hands-on virtual workshops for IT professionals new to cloud or interested in developing cloud infrastructures or applications. developerWorks will host cloud-focused forums, blogs and online communities and provide no-charge access to IBM software to help developers get started.

    In 2010, IBM also will begin a new series of cloud computing workshops at its 40 worldwide IBM Innovation Centers to support ISV business partners seeking cloud skills.

    Development & Test for Private Clouds and on the IBM Cloud

    IBM has offered a private cloud solution for development and test since June 2009, and now offers development and test services in three flexible delivery models:

  • IBM Smart Business Development & Test Cloud – a private cloud service behind the client's firewall, built and managed by IBM.  The service now includes enhanced capabilities for collaborative cloud development using Rational Software Delivery Services for Cloud Computing.
  • IBM Smart Business Development & Test on the IBM Cloud – application development and test featuring Rational Software Delivery Services for Cloud Computing over IBM's secure, scalable cloud.
  • IBM CloudBurst offerings for Development & Test – IBM CloudBurst is a pre-integrated set of hardware, storage, virtualization and networking, with a sophisticated built-in service management system to allow clients to rapidly deploy an internal/private cloud environment. WebSphere CloudBurst is a hardware appliance which rapidly dispenses and manages IBM middleware products delivered as virtual images into a private cloud in the form of reusable and customizable patterns.
  • "Workload characteristics continue to drive the rate and degree of standardization of IT and business services," said Rich Esposito, vice president, IT Strategy & Architecture and Middleware Services, IBM. "Standardization is key to bringing discipline, efficiency and simplicity to the most complex corners of big businesses."

    IBM understands that not every kind of computing task will move to a cloud environment, so the company is helping clients identify cloud computing opportunities by workload. Some workloads will remain on premise, but others are ripe for external cloud environments, including development and test.

    For clients who need help determining workload and delivery model choices, IBM delivers Cloud Infrastructure Strategy and Design Services. Based on proven methodologies and intellectual property earned through more than 100 client engagements and first-of-a-kind cloud projects, these integrated design services give clients a ready-to-build blueprint for cloud. The services are integrated into IBM's private workload optimized clouds.

    Details and availability

    The new open cloud environment includes support for Linux -- through Red Hat Enterprise Linux and SUSE Linux Enterprise from Novell -- and Java. Smart Business Development and Test on the IBM Cloud is powered by Red Hat Enterprise Virtualization, the Red Hat branded and supported KVM offering.  The enterprise cloud allows clients to work with their own images as well as images from IBM Mashup Center, Lotus Forms Turbo, WebSphere Portal Server, Lotus Web Content Management, and IBM Information Management and WebSphere brands that can be configured per their selection.

    Smart Business Development & Test on the IBM Cloud will be available in the second quarter of 2010 in The United States and Canada, and it will roll out globally throughout 2010.  

    For more information on IBM's cloud computing portfolio, research and labs please visit, ibm.com/cloud. 

    SOURCE IBM


    Proposal – IBM blockchain to manage marijuana supply chain in British Columbia | killexams.com real questions and Pass4sure dumps

    Bob Marley marijuanaProbably not a headline you ever thought you’d read on diginomica, but the times they are a changin’.  The idea is probably not as big a pot-pipe dream as it sounds.

    Canada is in the process of legalizing marijuana by July 2018, fulfilling one of the key campaign promises of Prime Minister Justin Trudeau. Ottawa is leaving it up to provincial governments to regulate its legal sale and distribution.

    When the government of British Columbia asked for feedback on the best way to manage its legal marijuana market, IBM quickly proffered a regulatory filing, arguing that the province should use the distributed ledger technology called blockchain to manage its legal marijuana market.

    In the filing, the Armonk, NY-based software giant said:

    IBM suggests Blockchain is an ideal mechanism in which BC can transparently capture the history of cannabis through the entire supply chain, ultimately ensuring consumer safety while exerting regulatory control – from seed to sale.

    Blockchain is rapidly becoming a world leading technology enabling the assured exchange of value in both digital and tangible assets, while protecting privacy and eliminating fraud.  Blockchain offers a shared ledger that is updated and validated in real time with each network participant. It enables equal visibility of activities and reveals where an asset is at any point in time, who owns it and what condition it’s in.

    As every schoolboy now knows, blockchains were originally conceived as a public, shared ledger that keeps track of payments in the Bitcoin network.

    Bitcoin’s volatility has scared off a lot of potential mainstream adoption of blockchain as a payment network.

    But companies quickly realized that the core concept of the blockchain could be repurposed for many other chains of custody applications, ranging from diamonds and tomatoes to global supply chains. Or, as in this case, the growth, distribution, sale, regulation, and taxing of your next favorite pastime substance.

    Basically, a blockchain is nothing more than a distributed database that’s maintained by a peer-to-peer network of companies involved in almost any shared marketplace. Every company manages and maintains its own copy of the shared ledger.

    In the case of British Columbia’s pot initiative, “each party in the business network” (growers, processors, distributors, retail locations, and regulators) would get its own ledger copy showing all transactions. The shared ledger would be accessible for anyone with the right credentials to see, allowing regulators to conduct spot audits of every marijuana transaction in the province.

    Retailers could identify which farm a particular batch of marijuana came from and what safety inspections were conducted along the way. Reads the IBM pitch:

    The Blockchain shared ledger is updated and validated in real time with each network participant. This enables equal visibility of activities and reveals where an asset/product is at any point in time, who owns it and what condition or state it is in. This type of transparency would bring a new level of visibility and control to the provincial regulators and provide assurance to the multitude of cautious stakeholders regarding the way the management of a cannabis supply chain is rolled out within British Columbia.

    IBM’s brief proposal to the government of British Columbia identifies key benefits for each of the parties in a possible blockchain agreement:

    BC Government: Blockchain can help the Provincial Government take control of sourcing, selling and pricing of products, therefore can reduce or eliminate black market sales completely.

    Producers: Blockchain can assist producers with real-time inventory management, greater projections of supply and demand, and also elicit trends of consumption through data analytics.

    Retailers: Although the Government of BC hasn’t confirmed what end-user distribution model will be used, they anticipate that it is likely that government itself will play a role in that process. An interconnected Blockchain network can assist retailers identify supply/demand gaps ways to mitigate those gaps, providing feedback mechanisms to producers, and use data to create predictive insights.

    IBM has been promoting blockchain aggressively in recent months.  In March, the company released IBM Blockchain, which it says is the first enterprise-ready blockchain service based on the Linux Foundation’s open source Hyperledger project.

    IBM’s blockchain services are designed to help developers create, deploy and manage blockchain networks on the IBM Cloud and a number of clients have already done so, ranging from the startup Everledger, which bills itself as the digital vault of the future, to financial services leaders like Bank of Tokyo-Mitsubishi UFJ, Postal Savings Bank of China and Northern Trust.

    A blockchain approach to supply chain management has a number of useful business advantages. Transactions can be asynchronous—individual buyers and sellers can deal directly with each other.

    The Hyperledger stack has cryptographic features that can limit one vendor from spying on another vendor’s transactions.  Hyperledger can also be combined with Internet-of-things technology, attaching a tracking device to products in transit and automatically generating data about their progress as they move through the supply chain.

    Using its Watson IoT Platform, IBM makes it possible to use information from devices such as RFID-based locations, barcode-scan events, or device-reported data with IBM’s Blockchain. Devices will be able to communicate to blockchain-based ledgers to update or validate smart contracts.

    Built to scale to thousands of users quickly, IBM says its cloud will allow production blockchain networks to be deployed in minutes, running signed, certified and tested Docker images with dashboards and analytics as well as support.

    A blockchain is only as good as the security of its infrastructure and IBM has spent millions of dollars on teams of security experts, cryptographers, hardware experts, and researchers to make certain its blockchain and cloud services are tamper-resistant and free of back door vulnerabilities that allow unauthorized access.

    With so much buzz about blockchain and so many projects underway at the moment, we’re about to find out whether the technology is the real thing or, in the case of BC, one toke over the line. I’m becoming a believer.

    This just leaves me with two BIG questions – what would Bob Marley have said? Who gets to test the supply chain in the real world? Somehow I can’t see the Big Blue consultants out in the field, so to speak. 🙂

    Image credit - public images



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    References :


    weSRCH : https://www.wesrch.com/business/prpdfBU1HWO000ANLA
    Dropmark : http://killexams.dropmark.com/367904/11563360
    Wordpress : http://wp.me/p7SJ6L-C6
    Scribd : https://www.scribd.com/document/359007651/Pass4sure-00M-226-Braindumps-and-Practice-Tests-with-Real-Questions
    Issu : https://issuu.com/trutrainers/docs/00m-226
    Dropmark-Text : http://killexams.dropmark.com/367904/12088692
    Blogspot : http://killexams-braindumps.blogspot.com/2017/11/pass4sure-00m-226-dumps-and-practice.html
    Youtube : https://youtu.be/cD-vDY-cQUU
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    Google+ : https://plus.google.com/112153555852933435691/posts/SsKuUEoJGMR?hl=en
    Calameo : http://en.calameo.com/books/004923526e5d9404ae417
    Box.net : https://app.box.com/s/v1cedlimjvxgbdhn5msu56256nm6a5zb
    zoho.com : https://docs.zoho.com/file/3y7xk24a2a8e8eb7b4ba7bfa1411c7b82ff41






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