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A2090-558 exam Dumps Source : Assessment: Informix Fundamentals 11.70 Assessment
Test Code : A2090-558
Test Name : Assessment: Informix Fundamentals 11.70 Assessment
Vendor Name : IBM
: 120 Real Questions
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ability level: foundation reputation: lively
within your budget: $200 (shortest song)
summary:Entry-stage certification for people who work with IBM database products. There are two tracks to make a choice from: Informix Dynamic Server (eleven.50) Fundamentals, and Informix (11.70) Fundamentals.
preliminary requirements:You should flow the linked exam for your chosen track ($200). each assessments have a 90 minute cut-off date and encompass 60 questions. working towards is attainable however no longer required.
carrying on with necessities:None targeted
See all Ibm Certifications
supplier's page for this certification
BEVERLY, MA--(Marketwired - Oct 29, 2013) - Altova® (http://www.altova.com), creator of XMLSpy®, the industry main XML editor, today announced the free up of edition 2014 of its MissionKit® computer developer tools and server utility products. MissionKit 2014 products now include integration with the lightning fast validation and processing capabilities of RaptorXML®, support for Schema 1.1, XPath/XSLT/XQuery 3.0, aid for new databases and plenty extra. New facets in Altova server products consist of caching alternate options in FlowForce® Server and improved efficiency powered through RaptorXML throughout the server product line.
"we're so excited to be able to extend the hyper-performance delivered by way of the unparalleled RaptorXML Server to builders working in their laptop tools. This performance, together with robust aid for the very newest necessities, from XML Schema 1.1 to XPath three.0 and XSLT 3.0, provides their consumers the advantages of elevated efficiency alongside reducing-part expertise support," referred to Alexander Falk, President and CEO for Altova. "This, coupled with the skill to automate basic approaches via their high-efficiency server products, gives their shoppers a distinct abilities when building and deploying purposes."
a few of the new aspects available in Altova MissionKit 2014 consist of:
Integration of RaptorXML: introduced earlier this 12 months, RaptorXML Server is high-efficiency server software capable of validating and processing XML at lightning speeds -- while providing the strictest viable requisites conformance. Now the same hyper-performance engine that powers RaptorXML Server is completely built-in in a few Altova MissionKit equipment, together with XMLSpy, MapForce®, and SchemaAgent®, supplying lightning quickly validation and processing of XML, XSLT, XQuery, XBRL, and greater. The third-generation validation and processing engine from Altova, RaptorXML become developed from the ground as much as guide the very newest of all vital XML requisites, together with XML Schema 1.1, XSLT three.0, XPath three.0, XBRL 2.1, and myriad others.
help for Schema 1.1: XMLSpy 2014 contains critical help for XML Schema 1.1 validation and enhancing. The latest edition of the XML Schema typical, 1.1 provides new points aimed toward making schemas greater flexible and adaptable to business instances, similar to assertions, conditional types, open content, and extra.
All elements of XML Schema 1.1 are supported in XMLSpy's graphical XML Schema editor and are available in entry helpers and tabs. As at all times, the graphical modifying paradigm of the schema editor makes it handy to bear in mind and put in force these new facets.
help for XML Schema 1.1 is also offered in SchemaAgent 2014, allowing users to visualize and manipulate schema relationships by means of its graphical interface. here is additionally an abilities when connecting to SchemaAgent in XMLSpy.
Coinciding with XML Schema 1.1 aid, Altova has additionally launched a free, online XML Schema 1.1 technology practising direction, which covers the basics of the XML Schema language as smartly because the changes introduced in XML Schema 1.1.
help for XPath 3.0, XSLT 3.0, and XQuery 3.0:
aid for XPath in XMLSpy 2014 has been up-to-date to include the newest version of the XPath advice. XPath three.0 is a superset of the XPath 2.0 recommendation and provides effective new performance comparable to: dynamic characteristic cells, inline characteristic expressions, and help for union forms to name just just a few. Full guide for brand new features and operators introduced in XPath three.0 is accessible through intelligent XPath auto-completion in text and Grid Views, in addition to in the XPath Analyzer window.
help for modifying, debugging, and profiling XSLT is now obtainable for XSLT three.0 in addition to outdated versions. Please notice that a subset of XSLT 3.0 is supported for the reason that the usual is still a working draft that continues to adapt. XSLT three.0 guide conforms to the W3C XSLT 3.0 Working Draft of July 10, 2012 and the XPath 3.0 Candidate advice. although, support in XMLSpy now gives developers the means to birth working with this new edition immediately.
XSLT 3.0 takes potential of the brand new features brought in XPath 3.0. additionally, a massive feature enabled by way of the new version is the brand new xsl:are trying / xsl:seize construct, which will also be used to trap and recuperate from dynamic blunders. other enhancements in XSLT three.0 encompass support for greater order capabilities and partial services.
As with XSLT and XPath, XMLSpy support for XQuery now additionally contains a subset of edition three.0. builders will now have the choice to edit, debug, and profile XQuery three.0 with advantageous syntax coloring, bracket matching, XPath auto-completion, and different clever modifying facets.
XQuery 3.0 is, of course, an extension of XPath and hence merits from the brand new services and operators brought in XPath three.0, akin to a brand new string concatenation operator, map operator, math capabilities, sequence processing, and extra -- all of which are available in the context sensitive entry helper home windows and drop down menus within the XMLSpy 2014 XQuery editor.
New Database assist:
Database-enabled MissionKit items together with XMLSpy, MapForce, StyleVision®, DatabaseSpy®, UModel®, and DiffDog®, now include finished assist for more moderen models of previously supported databases, as well as aid for brand spanking new database companies:
New in Altova Server utility 2014:
introduced past in 2013, Altova's new line of cross-platform server software products includes FlowForce Server, MapForce Server, StyleVision Server, and RaptorXML Server. FlowForce Server provides finished management, job scheduling, and safety alternatives for the automation of essential business methods, while MapForce Server and StyleVision Server offer high-speed automation for initiatives designed using prevalent Altova MissionKit developer tools. RaptorXML Server is the third-era, hyper-fast validation and processing engine for XML and XBRL.
starting with version 2014, Altova server products are powered by way of RaptorXML for sooner, more productive processing. additionally, FlowForce Server now helps outcomes caching for jobs that require a long time to process, as an instance when a job requires complicated database queries or needs to make its own net carrier statistics requests. FlowForce Server administrators can now time table execution of a time-consuming job and cache the consequences to avoid these delays. The cached information can then be provided when any consumer executes the job as a carrier, delivering immediate results. A job that generates a customized earnings report for the previous day can be a pretty good utility for caching.
These and a lot of extra facets can be found in the 2014 version of MissionKit desktop developer tools and Server utility. For an entire record of recent points, supported specifications, and trial downloads please discuss with: http://www.altova.com/whatsnew.html
About Altova Altova® is a software enterprise that specialize in equipment to help builders with statistics administration, software and software development, and information integration. The creator of XMLSpy® and different award-winning XML, SQL and UML tools, Altova is a key player in the software tools business and the chief in XML solution development tools. Altova makes a speciality of its shoppers' needs by using offering a product line that fulfills a large spectrum of requirements for application building groups. With over four.5 million users global, together with ninety one% of Fortune 500 companies, Altova is proud to serve consumers from one-adult stores to the realm's greatest agencies. Altova is committed to providing standards-based mostly, platform-impartial solutions that are potent, low-cost and simple-to-use. situated in 1992, Altova is headquartered in Beverly, Massachusetts and Vienna, Austria. seek advice from Altova on the internet at: http://www.altova.com.
Altova, MissionKit, XMLSpy, MapForce, FlowForce, RaptorXML, StyleVision, UModel, DatabaseSpy, DiffDog, SchemaAgent, genuine, and MetaTeam are emblems and/or registered trademarks of Altova GmbH within the u.s. and/or other nations. The names of and reference to different corporations and items mentioned herein can be the logos of their respective house owners.
In-DepthEveryman's book to statistics Warehousing
you have read the articles, attended the entire conferences, and are now charged to delivery your personal records warehousing project and attain that 401% ROI you have got heard each person is getting. in addition, you have gone to the CFO or the vice president of advertising and won funding in your commercial enterprise statistics warehouse. Congratulations ... now it's time for the precise work to begin.
and you had greater be a hit, as a result of this assignment usually are not affordable and all eyes may be upon it. you're going to ought to evaluate and buy Extraction, Transformation and cargo (ETL) software, OLAP software, all types of hardware, middleware, and employ expensive consultants. And if that is not complex satisfactory, an enterprise records warehouse also contains integrating statistics from a company perspective. therefore, you'll have to have interaction with probably the most senior people in each of your business's divisions and e book them to consensus. And if you don't deliver on that 401% ROI, and appease all of those division heads, your supervisor simply might hand you a one-method ticket to the enterprise's Siberian office.
however earlier than your resolution assist equipment (DSS) task even starts, take a moment to investigate these primary questions. in case you reply "No" or "i am now not sure" to any of here, you could want to do some extra homework earlier than heading down the facts warehousing trail.
1. What are the specific strategic business aims (drivers) that the warehouse is think to obtain?The overriding motive many decision aid projects fail is not that the initiatives had been technically unfeasible. On the opposite, most of the technological challenges of facts warehousing have confirmed solutions. probably the most typical reason for failure is that the warehouse did not meet the enterprise ambitions of the corporation. I have viewed many organizations do a fine job of technically constructing a data warehouse; alas, the device didn't remedy any of their company needs. Warehouses that do not satisfy business person's needs don't seem to be accessed and eventually die.
2. What are the specific, calculable measurements that should be used to evaluate the ROI of the DSS equipment in meeting your business's business targets?Clear enterprise pursuits are measurable. This endeavor is important, as a result of once the information warehouse challenge is achieved, the administration crew will should justify the expenditure. additionally, it is important to remember that an information warehouse is not a venture, it is a system. records warehouses are organic in nature. They develop very quickly and in directions you in no way predicted. Most warehouses double in size and within the variety of users in their first 12 months of creation. as soon as a price justification may also be quantified for the preliminary unlock, the procedure for gaining funding for follow-up releases is tremendously simplified.
3. Are the important thing users of the statistics warehouse identified and committed to the success of the mission?The users all the time dictate the success or failure of the warehouse. They for this reason should be closely involved all the way through the records warehousing venture. Taking it a step further, users need to have a private stake in the success of the challenge. it's superb how straight away complications vanish when all and sundry has a vested interest within the assignment. also, make it a point to train users on the fundamentals and processes of records warehousing. train them its advantages, in addition to its barriers. this may assist vastly in managing their expectations. an outstanding rule of thumb is that if you have long past greater than two weeks with out speaking to your clients, then it's time to deploy a gathering. keep in mind that again and again these people are the ones selecting up the tab on these tasks.
four. Is the corporation trying to build a +1 Terabyte, "do-all, be-all" statistics warehouse on its first iteration?facts warehousing projects stretch a company in techniques unlike operational methods projects do. From a political point of view, an commercial enterprise records warehouse requires consent and dedication from the entire key departments inside a company. additionally, the studying curve of a call guide assignment group is seldom understood or deliberate for. There will be a brand new and dizzying array of software tools (ETL, OLAP, portal, meta records, records cleaning and records mining) as a way to require device-certain practising.
by means of adding huge amounts of data into the equation the features of failure boost significantly. additionally, significant volumes of records will push the envelope of the RDBMS, middleware and hardware, and could drive builders into using parallel construction recommendations if a massively parallel processing (MPP) structure is needed. bear in mind that the answer to a lot of these challenges is available in the form of a hefty expense tag. in consequence, including the dimension of size is just too painful and costly for most enterprises to effort right through the primary iteration.
information warehouses are most useful inbuilt an iterative trend. do not misunderstand; here is not to recommend that a company should still no longer build a totally practical, distinct Terabyte, +7 discipline area, net-enabled, end-to-end, commercial enterprise facts warehouse with an entire meta information interface. It without difficulty means that the highest chance for success comes from implementing a choice help system in a phased strategy. through the use of the first iteration as an opportunity to instruct the supplier, it'll set the stage for bigger and improved future implementations.
5. Does the resolution support professional-ject have guide from government administration?Any tremendous-scale venture, whether it is a data warehouse or imposing that sizzling new customer relationship administration (CRM) device, wants executive management on board. furthermore, their involvement is integral in breaking down the barriers and "ivory towers" in companies. Their place enables them to rally the various departments within an organization at the back of the assignment. Any giant undertaking lacking government management participation has a high likelihood of failure.
6. Does the firm have a clear realizing of the ideas and tools worried in records warehousing?if you do not need an information warehouse constructed, then the reply to this question will absolutely be "No." subsequently, practicing and training may be required. however keep in mind that training is required at many tiers. preliminary education is integral to deliver the ideas of an information warehouse, facts mart, operational facts shop, superstar schema design and meta statistics. statistics acquisition developers will also doubtless should be proficient on a transformation device (Informix DataStage, as an example), whereas data warehouse access developers will require gigantic practising in an OLAP device (for example, BusinessObjects and Cognos PowerPlay). statistics administration builders will should be proficient on a device in an effort to combine the entire company's meta facts into one repository (Platinum Repository, for example). And, more than likely, there could be an internet part used to access the records warehouse and the meta information repository. reckoning on your company, extra practicing and outdoors consulting can be vital for each of these areas. keep in mind that these are most effective the facts warehousing-particular practicing considerations. There nevertheless needs to be an understanding of the hardware, middleware, desktop, RDBMS and coding language (COBOL, C++ and the like) of the transformation tool.
7. Is there a incredibly experienced task manager and facts warehouse architect, with experience in constructing warehouses, who will actively participate right through the project?information warehousing tasks are essentially distinct from operational tasks. Operational projects are imperative in order to function the daily enterprise of the company. determination help projects are important for making strategic selections about your firm. in addition, facts warehouses develop at an alarming cost during the primary few years of production. An skilled information warehouse assignment leader understands these data and continues the imaginative and prescient of the assignment in live performance with the precise-world fact of decision help. furthermore, the information warehouse architect ought to design a scalable, effective and maintainable structure that may accommodate the increasing and altering resolution guide requirements.
These simple challenges require tremendously skilled, senior-level individuals. These positions may also be filled by the use of in-apartment supplies or by consultants. If consultants are used to fill these roles, it is indispensable that they are extremely expert at talents switch; in-residence personnel should still be assigned to shadow consultants for each of those roles.
8. Has an experienced consultant been brought in to do a readiness assessment of the company?This step is very vital as a result of an skilled hand can identify difficulty areas in the corporation that will also be dealt with early within the DSS undertaking's existence cycle. however settling on that adult is an additional subject. Be wary of consultants with out true-world, arms-on event. it is one issue to be in a position to write or communicate about data warehousing; it is a different count absolutely to have the event needed to navigate during the political quagmires and to grasp what it takes to physically build a data warehouse.
David Marco is the creator of building and Managing the Meta statistics Repository: A Full life-Cycle book from John Wiley & Sons. he's founder and president of business Warehousing solutions Inc. (EWS), a Chicago-primarily based gadget integrator. He will also be reached at 708-233-6330 or by means of electronic mail at email@example.com.
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In-DepthEveryman's Guide to Data Warehousing
You have read the articles, attended all of the conferences, and are now charged to start your own data warehousing project and attain that 401% ROI you have heard everyone is getting. In addition, you have gone to the CFO or the vice president of marketing and gained funding for your enterprise data warehouse. Congratulations ... now it is time for the real work to begin.
And you had better be successful, because this project will not be cheap and all eyes will be upon it. You will have to evaluate and purchase Extraction, Transformation and Load (ETL) software, OLAP software, all forms of hardware, middleware, and hire expensive consultants. And if that is not difficult enough, an enterprise data warehouse also involves integrating data from a corporate perspective. Therefore, you will have to interact with the most senior people in each of your company's divisions and guide them to consensus. And if you do not deliver on that 401% ROI, and appease all of those division heads, your supervisor just might hand you a one-way ticket to the company's Siberian office.
But before your decision support system (DSS) project even begins, take a moment to examine these essential questions. If you answer "No" or "I'm not sure" to any of the following, you might want to do some more homework before heading down the data warehousing trail.
1. What are the specific strategic business objectives (drivers) that the warehouse is suppose to achieve?The overriding reason many decision support projects fail is not that the projects were technically unfeasible. On the contrary, many of the technological challenges of data warehousing have proven answers. The most common cause of failure is that the warehouse did not meet the business objectives of the organization. I have seen many companies do a fine job of technically building a data warehouse; unfortunately, the system did not solve any of their business needs. Warehouses that do not satisfy business user's needs are not accessed and eventually die.
2. What are the specific, calculable measurements that will be used to evaluate the ROI of the DSS system in meeting your company's business objectives?Clear business objectives are measurable. This activity is critical, because once the data warehouse project is completed, the management team will have to justify the expenditure. Moreover, it is important to understand that a data warehouse is not a project, it is a process. Data warehouses are organic in nature. They grow very fast and in directions you never anticipated. Most warehouses double in size and in the number of users in their first year of production. Once a cost justification can be quantified for the initial release, the process for gaining funding for follow-up releases is greatly simplified.
3. Are the key users of the data warehouse identified and committed to the success of the project?The users always dictate the success or failure of the warehouse. They therefore need to be heavily involved throughout the data warehousing project. Taking it a step further, users need to have a personal stake in the success of the project. It is amazing how quickly problems vanish when everyone has a vested interest in the project. Also, make it a point to educate users on the fundamentals and processes of data warehousing. Teach them its benefits, as well as its limitations. This will aid significantly in managing their expectations. A good rule of thumb is that if you have gone more than two weeks without talking to your users, then it is time to set up a meeting. Keep in mind that many times these people are the ones picking up the tab on these projects.
4. Is the organization trying to build a +1 Terabyte, "do-all, be-all" data warehouse on its first iteration?Data warehousing projects stretch an organization in ways unlike operational systems projects do. From a political perspective, an enterprise data warehouse requires consent and commitment from all of the key departments within a corporation. In addition, the learning curve of a decision support project team is seldom understood or planned for. There will be a new and dizzying array of software tools (ETL, OLAP, portal, meta data, data cleansing and data mining) that will require tool-specific training.
By adding massive amounts of data into the equation the points of failure increase significantly. Moreover, large volumes of data will push the envelope of the RDBMS, middleware and hardware, and could force developers into using parallel development techniques if a massively parallel processing (MPP) architecture is needed. Keep in mind that the answer to many of these challenges comes in the form of a hefty price tag. As a result, adding the dimension of size is just too painful and costly for most enterprises to attempt during the first iteration.
Data warehouses are best built in an iterative fashion. Do not misunderstand; this is not to recommend that a company should not build a fully functional, multiple Terabyte, +7 subject area, Web-enabled, end-to-end, enterprise data warehouse with a complete meta data interface. It simply means that the highest probability for success comes from implementing a decision support system in a phased approach. By using the first iteration as an opportunity to train the corporation, it will set the stage for bigger and better future implementations.
5. Does the decision support pro-ject have support from executive management?Any large-scale project, whether it is a data warehouse or implementing that hot new customer relationship management (CRM) system, needs executive management on board. Moreover, their involvement is imperative in breaking down the barriers and "ivory towers" in companies. Their position allows them to rally the various departments within a corporation behind the project. Any substantial project lacking executive management participation has a high probability of failure.
6. Does the organization have a clear understanding of the concepts and tools involved in data warehousing?If you do not have a data warehouse built, then the answer to this question will most likely be "No." As a result, training and education will be required. But keep in mind that training is required at many levels. Initial education is necessary to convey the concepts of a data warehouse, data mart, operational data store, star schema design and meta data. Data acquisition developers will also probably need to be trained on a transformation tool (Informix DataStage, for example), while data warehouse access developers will require significant training in an OLAP tool (for example, BusinessObjects and Cognos PowerPlay). Data administration developers will need to be trained on a tool that will integrate all of the company's meta data into one repository (Platinum Repository, for example). And, more than likely, there will be a Web component used to access the data warehouse and the meta data repository. Depending on your organization, additional training and outside consulting could be needed for each of these areas. Keep in mind that these are only the data warehousing-specific training issues. There still needs to be an understanding of the hardware, middleware, desktop, RDBMS and coding language (COBOL, C++ and so on) of the transformation tool.
7. Is there a highly experienced project manager and data warehouse architect, with experience in building warehouses, who will actively participate throughout the project?Data warehousing projects are fundamentally different from operational projects. Operational projects are necessary in order to operate the day-to-day business of the company. Decision support projects are critical for making strategic decisions about your organization. In addition, data warehouses grow at an alarming rate during the first few years of production. An experienced data warehouse project leader understands these facts and keeps the vision of the project in concert with the real-world reality of decision support. In addition, the data warehouse architect must design a scalable, robust and maintainable architecture that can accommodate the expanding and changing decision support requirements.
These fundamental challenges require highly experienced, senior-level individuals. These positions can be filled via in-house resources or by consultants. If consultants are used to fill these roles, it is imperative that they are highly skilled at knowledge transfer; in-house employees should be assigned to shadow consultants for both of these roles.
8. Has an experienced consultant been brought in to do a readiness assessment of the organization?This step is very important because an experienced hand can identify problem areas in the organization that can be dealt with early in the DSS project's life cycle. But identifying that person is another issue. Be wary of consultants without real-world, hands-on experience. It is one thing to be able to write or speak about data warehousing; it is another matter entirely to have the experience needed to navigate through the political quagmires and to know what it takes to physically build a data warehouse.
David Marco is the author of Building and Managing the Meta Data Repository: A Full Life-Cycle Guide from John Wiley & Sons. He is founder and president of Enterprise Warehousing Solutions Inc. (EWS), a Chicago-based system integrator. He can be reached at 708-233-6330 or via E-mail at firstname.lastname@example.org.
It’s been a decade of lows for commodities after posting 7 declines in 11 years, but we’ve seriously underestimated lithium. It’s back with a vengeance in 2019.
The commodities market endured yet another annus horribilis, with just four commodities—natural gas, uranium, cocoa and wheat—recording any uptick at all. Last year’s 12 percent slide by the Bloomberg Commodity Index--spurred by 20 percent-plus declines by industrial bellwethers like West Texas Intermediate crude, steel and platinum—came in the wake of two years of modest gains.
Viewed against that kind of backdrop, lithium’s 50 percent correction that snapped a multi-year winning streak appears less vicious. It’s important to remember that prior to the crash, lithium had enjoyed a meteoric rise with prices doubling since the beginning of 2016 and nearly quadrupling over the past decade. The fact that much of the rally coincided with a sharp rise in the value of the U.S. dollar makes it all the more remarkable.
Investing in the commodity market can be a roller-coaster ride; what with the incessant boom-and-bust cycles driven by the ebb and flow in infrastructural spending, production ramps/cutbacks and stockpiling/destocking supplies. And just like other financial markets, trader sentiment plays a big role in determining trajectories.
Related: Political Crisis In Venezuela To Reshape OPEC
Unfortunately, it’s the latter scenario that took center-stage during last year’s lithium crash. A furor around anticipated new supply especially from China’s new hard-rock projects and Chilean brine mines got out whack and derailed the market.
(Click to enlarge)
(Click to enlarge)
Source: Trading Economics
Tsunami of Oversupply?
The situation was not helped by Wall Street punters sounding the alarm over the dangers of oversupply …
Shares of major lithium producers and explorers including Sociedad Quimica y Minera de Chile (NYSE:SQM), Albemarle Corp. (NYSE:ALB) and Orocobre Ltd (ASX:ORE) received a severe hammering in March after Morgan Stanley forecast that Chilean low cost brine producers could add as much as 200kt per year by 2025, while expansion of China’s and Australia’s hard-rock mines could pump in another half a million metric tonnes over the timeframe. That’s certainly a massive production ramp-up considering that global production in 2017 totaled just over 200kt.
In August, Macquarie Research provided the final straw after chiming in with a warning that the market was “sleepwalking into a tsunami of oversupply.”
The report put the final nail in the coffin of the decade-long lithium rally-- Fastmarkets reckons that prices for battery-grade lithium carbonate in China, by far the world’s largest consumer of high-grade lithium carbonate, tumbled 50.31 percent last year to 75,000-83,000 ($10,885-12,046) yuan per tonne from 158,000-160,000 ($22,932-23,222) yuan per tonne the previous year, as demand waned.
(Click to enlarge)
Source: Metal Bulletin
But maybe the bear camp rushed their fences this time…
While it’s undeniable that the carnage managed to exceed even Morgan Stanley’s decidedly pessimistic outlook for global lithium prices to drop 45 percent by 2021, the fundamentals suggest that the selloff was greatly overdone and such low prices cannot be justified by simple market forces of supply and demand.
According to London-based Benchmark Minerals Intelligence senior analyst Andrew Miller, the disconnect between lithium prices and the demand side of the equation has never been bigger.
A cross-section of materials experts have raised eyebrows at the negative assessment, criticizing the investment analysts for underestimating the rise in lithium demand and the complex nature of lithium mining and production ramps. According to them, both MS and Macquarie failed to account for just how big the gap between supply forecast and actual production can be.
And, they might be spot on.
Supply expansions in 2018 came in much lower than predicted and the tsunami of oversupply forecast by the likes of Macquarie Research proved to be little more than changing tides in the lithium supply chain.
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A good case in point is Brisbane-based Orocobre, which has become the poster child for just how challenging new brine mining can be. The company’s Salar de Olaroz project in Argentina took seven years to hit its stride but still came up short of production targets. Meanwhile, run-ins with the courts and regulators coupled with mutual accusations of license violations facing Chile’s lithium giants SQM and Albemarle at their Atacama brine projects further reinforce this point.
The screenshot below from Orocobre’s investor slide presentation is a sobering reminder to this reality.
(Click to enlarge)
In terms of feedstock supply, SQM and Albemarle had laid out plans for increased production rates. But as is often the case with brine evaporation, the process has been hindered by seemingly endless production delays. SQM hit technical obstacles at its new brine conversion facilities that delayed its target capacity of 70,000 tpa LCE by end of 2018 while Albemarle continues to struggle to achieve full capacity at La Negra II.
The situation has not been much better in China—the ultimate lynchpin to the lithium bear thesis. Many Chinese brine producers in the Qinghai region had outlined plans to triple or quadruple capacities over the coming 3-4 years. A visit by Benchmark Minerals to these operations, however, has painted a dire picture—the technical challenges related to high magnesium concentrations in the region are nowhere near being comprehensively overcome. Across Qinghai’s 10 producers, only an additional 5,000-10,000 tonnes of lithium product found its way to the market, majority of which failed to reach technical grade specifications. This, in effect, means that much of what came online from the region was either reprocessed thus adding to costs or converted to lithium hydroxide in a bid to meet growing demand for nickel-rich cathode technologies.
Although tight credit in China forced some lithium buyers to destock and contributed to the glut, the predicted huge oversupply failed to materialize. Around mid-September, analysts at CRU estimated lithium surplus for 2018 at a relatively mild 22,000 tonnes against a demand of 277,000 tonnes.'
Source: Benchmark Minerals
2019: A Transition Year
So far, there is no clear data or evidence that that the lithium demand narrative is about to slowdown, let alone reverse. On the contrary, certain emerging trends in the industry suggest just the opposite.
The biggest near-term driver for lithium demand is the NCM trend. The shift towards cathodes that use huge amounts of lithium hydroxide is already underway, something that is expected to trigger a huge NCM (nickel-cobalt-manganese) ramp up. Benchmark Minerals estimates that 44 percent of mega-and-giga-factories will use lithium as a raw material by 2028 translating into 534,000 tonnes of additional demand.
That projection seems to resonate with Elon Musk’s ambitious target to build 20 gigafactories across the globe over the next decade. Miller sees 2019 as the tipping point where demand will eventually outstrip supply starting 2020.
Meanwhile, Roskill has predicted that the shift to higher-nickel-cathode materials will push many lithium producers to favor production of lithium hydroxide over lithium carbonate thus taking some pressure off the lithium carbonate supply side. The firm has forecast lithium demand to expand by a brisk 21 percent annual clip between 2018 and 2025 with demand expected to grow 13.5 percent in the current year.
But, of course, no lithium bull thesis would be complete without the EV angle.
Currently, the EV market accounts for about 47 percent of global lithium demand. That, however, is expected to drastically change as EV penetration rates coupled with the ongoing trend of electric vehicles using larger battery packs that yield longer ranges leading to electric mobility gobbling up 83 percent of lithium supply a by 2027.
Fastmarkets has predicted EV penetration to hit 15 percent by 2025 from 2 percent currently. EV demand has actually been beating estimates and is constantly being revised upwards to reflect this. The EV explosion is expected to drive a nearly six-fold increase in lithium demand for the forecast period.
(Click to enlarge)
Source: Infinity Lithium company presentation
Key lithium trends to watch in 2019 and beyond
Miller advises investors to keep an eye on new spodumene production, particularly how quickly it can be integrated into the chemical and converter supply chain and turned into either lithium carbonate or hydroxide. A slower ramp is likely to lead to supply constraints and raise prices and vice-versa.
By Alex Kimani for Oilprice.com
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