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IBM C2090-616 : DB2 11.1 Fundamentals for LUW Exam

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Test Number : C2090-616
Test Name : DB2 11.1 Fundamentals for LUW
Vendor Name : IBM
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C2090-616 exam Format | C2090-616 Course Contents | C2090-616 Course Outline | C2090-616 exam Syllabus | C2090-616 exam Objectives

Exam ID : C2090-616
Exam Title : DB2 11.1 Fundamentals for LUW
Number of questions: 63
Number of questions to pass: 43
Time allowed: 90 mins
Status: Live

This Database Associate certification is an entry level exam for a user of any of the DB2 family of products. This individual is knowledgeable about the fundamental concepts of DB2 11.1 through either hands on experience or formal and informal education. The database associate should have an in-depth knowledge of the basic to intermediate tasks required in day-to-day administration, basic SQL (Structured Query Language), understand which additional products are available with DB2 11.1, understand how to create databases and database objects, and have a basic knowledge of database security and transaction isolation.

Section 1 - Planning 21%
- Identify and describe the DB2 products available
- Identify and decribe the DB2 Cloud offerings available
- Describe the characteristics of OLTP and Data Warehouse workloads
- Describe the benefits of DB2 pureScale
- Demonstrate the ability to use DB2 BLU Acceleration
- Explain Federation support
- Identify and describe Oracle and Netezza Compatibility Features

Section 2 - Security 17%
- Describe methods used to restrict data access
- Identify and describe the authorities and privileges available
- Identify and describe the DCL statements available
- Describe Roles and Trusted Contexts

Section 3 - Working with Databases and Database Objects 16%
- Create and connect to DB2 servers and databases
- Identify DB2 objects
- Identify and describe the DDL statements available
- Describe the different types of tables available

Section 4 - Working with DB2 Data using SQL 19%
- Demonstrate the ability to use SQL to SELECT data from tables
- Demonstrate the ability to use SQL to UPDATE, DELETE, or INSERT data
- Demonstrate the ability to manage transactions
- Demonstrate the ability to create and call an SQL stored procedure or a user defined function
- Identify and describe SQL compatibility enhancements
- Identify the OLAP function used to meet a specific business requirement

Section 5 - Working with DB2 Tables, Views, and Indexes 13%
- Identify and describe the DB2 data types available
- Identify the characteristics of a table, view or index
- Demonstrate the ability to create and use temporary tables
- Demonstrate the ability to create and use triggers

Section 6 - Data Concurrency 14%
- Identify factors that influence locking
- List objects on which locks can be obtained
- Identify characteristics of DB2 locks
- Given a situation, identify the isolation level that should be used

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IBM is the use of mild, as a substitute of electricity, to create ultra-fast computing | C2090-616 PDF obtain and PDF Download

To quench algorithms' seemingly limitless thirst for processing energy, IBM researchers have unveiled a brand new method that might suggest massive adjustments for deep-studying purposes: processors that function computations completely with light, as opposed to electrical energy.  

The researchers have created a photonic tensor core that, in accordance with the homes of light particles, is capable of processing records at extraordinary speeds, to deliver AI purposes with ultra-low latency.  

youngsters the equipment has best been tested at a small scale, the document means that because the processor develops, it may obtain 1000 trillion multiply-accumulate (MAC) operations per 2nd and per square-millimeter – according to the scientists, that is 2 to 3 orders more than "state-of-the-art AI processors" that rely on electrical signals.  

SEE: Kubernetes security guide (free PDF) (TechRepublic)

IBM has been working on novel processes to processing devices for a number of years now. a part of the business's analysis has focused on establishing in-reminiscence computing technologies, wherein reminiscence and processing co-exist in some kind. This avoids transferring records between the processor and a separate RAM unit, saving energy and decreasing latency. 

ultimate 12 months, the company's researchers unveiled that they had efficiently developed an all-optical method to in-memory processing: they built-in in-memory computing on a photonic chip that used light to carry out computational tasks. As part of the scan, the group proven that a primary scalar multiplication could readily be conducted the usage of the know-how. 

In a new weblog put up, IBM research personnel member Abu Sebastian shared a new milestone that has now been achieved the use of gentle-based mostly in-memory processors. Taking the technology to the subsequent stage, the group has developed a photonic tensor core, which is a type of processing core that performs refined matrix math, and is primarily relevant for deep-researching purposes. The light-based mostly tensor core turned into used to perform an operation known as convolution, it really is helpful to system visible information akin to pictures. 

"Our experiments in 2019 had been often about showing the competencies of the technology. A scalar multiplication is awfully removed from any true-life utility," Abu Sebastian, research team of workers member at IBM analysis, tells ZDNet. "however now, they now have a whole convolution processor, which you might maybe use as a part of a deep neural network. That convolution is a killer software for optical processing. In that feel, or not it's quite a big step." 

essentially the most huge abilities that mild-primarily based circuits have over their electronic counterparts is never-before-seen pace. Leveraging optical physics, the expertise developed by means of IBM can run complex operations in parallel in a single core, using diverse optical wavelengths for each and every calculation. combined with in-reminiscence computing, IBM's scientists done ultra-low latency that's yet to be matched through electrical circuits. For applications that require very low latency, hence, the velocity of photonic processing could make a large difference. 

Sebastian places ahead the example of self-using automobiles, where speed of detection could have lifestyles-saving implications. "if you're riding on the toll road at a hundred miles-per-hour, and also you deserve to become aware of something inside a certain distance – there are some situations the place the present expertise would not allow you to do this. however the form of velocity that you just get with photonic-primarily based techniques is a few orders of magnitude enhanced than electrical approaches." 

SEE: This powerful new supercomputer will let scientists ask 'the appropriate questions'

With its skill to operate a few operations simultaneously, the easy-based processor developed by IBM also requires lots much less compute density. in accordance with Sebastian, this may be a further key differentiator: there will be a point, says the scientist, the place loading automobile trunks with rows of widespread GPUs to support ever-greater refined AI methods might not cut it anymore.  

With most colossal vehicle agencies now opening their personal AI research facilities, Sebastian sees autonomous vehicles as a key software for gentle-based processors. "there is a real need for low latency inference in the domain of independent using, and no expertise that can meet it as of now. this is a distinct opportunity." 

IBM's team, even though it has efficaciously designed and confirmed an impressive core, still must extend trials to make certain that the technology can be built-in at a device degree to ensure conclusion-to-conclusion performance. "We deserve to do a whole lot more there," says Sebastian; however according to the scientist, work is already underway, and as research continues, more purposes are best more likely to come up. buying and selling electrical energy for mild, in the box of computing, definitely makes for a spot to watch. 

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