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C2090-461 - IBM InfoSphere Optim for Distributed Systems v9.1 Upgrade - BrainDump Information

Vendor Name : IBM
Exam Code : C2090-461
Exam Name : IBM InfoSphere Optim for Distributed Systems v9.1 Upgrade
Questions and Answers : 34 Q & A
Updated On : April 25, 2019
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C2090-461 IBM InfoSphere Optim for Distributed Systems v9.1 Upgrade

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C2090-461 exam Dumps Source : IBM InfoSphere Optim for Distributed Systems v9.1 Upgrade

Test Code : C2090-461
Test Name : IBM InfoSphere Optim for Distributed Systems v9.1 Upgrade
Vendor Name : IBM
Q&A : 34 Real Questions

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IBM IBM InfoSphere Optim for

IBM facts Studio | killexams.com Real Questions and Pass4sure dumps

This chapter is from the e-book 

IBM data Studio is covered in every DB2 edition. IBM records Studio gives a single built-in environment for database administration and application building. that you can operate initiatives which are concerning database modeling and design, developing database applications, administering and managing databases, tuning SQL efficiency, and monitoring databases all in one single device. it's an ideal device that may greatly improvement a crew atmosphere with diverse roles and tasks.

IBM statistics Studio is available in three favors: full customer, administration client, and web console.

the complete customer contains both the database administrative and the application construction capabilities. The building atmosphere is Eclipse-primarily based. This presents a collaborative construction atmosphere by integrating with different advanced Eclipse-based mostly equipment corresponding to InfoSphere facts Architect and InfoSphere Optim pureQuery Runtime. observe that one of the vital superior InfoSphere equipment are handiest protected within the DB2 superior editions and the DB2 Developer version. which you could also one after the other purchase the superior tools.

The administration client is a subset of the complete client. It nonetheless offers a wide range of database administrative performance reminiscent of DB2 instance management, object administration, information administration, and query tuning. basic application construction tasks comparable to SQL Builder, question formatting, visible explain, debugging, modifying, and running DB2 routines are supported. Use the complete client for advanced software building aspects.

The net console, as the identify implies, it is an internet-primarily based browser interface that offers health monitoring, job administration, and connection administration.

IBM records Studio Workspace and the project Launcher

when you have correctly put in the IBM statistics Studio, you are requested to provide a workspace identify. A workspace is a folder that saves your work and projects. It refers to the computing device building atmosphere, which is an Eclipse-based mostly concept.

project Launcher is displayed, which highlights right here class of projects:

  • Design
  • increase
  • Administer
  • Tune
  • video display
  • every class is described in additional aspect in its own tab. click any tab, and also you see the key and primary tasks listed within the field on the left. See determine four.26 to get a concept on the way to navigate the task Launcher.

    for instance, the determine indicates you the enhance tasks. which you can locate the key development tasks on the left. On the proper appropriate, it lists more projects regarding development. On the bottom right, IBM data Studio offers a couple of documentation hyperlinks the place that you could be taught greater about development. the place applicable, it also suggests the advanced tools purchasable in the InfoSphere Optim portfolio that observe to the project you have got chosen.

    Connection Profiles

    every assignment you had been to perform against a database requires to first establish a database connection. To hook up with a database from IBM information Studio, open the Database Administration perspective. On the suitable appropriate corner, click the Open viewpoint icon and choose Database Administration.

    On the Administration Explorer, correct-click the white house or beneath the brand new menu, choose New Connection to a database. From the new Connection window, you see that you can use the IBM facts Studio to connect to distinct IBM information sources, in addition to non-IBM records sources. choose the database supervisor and enter the imperative connection parameters. determine 4.28 indicates an example.

    Figure 4.27

    determine 4.27 Open the Database Administration point of view

    Pull down the JDBC driver drop-down menu, and you may select the type of JDBC driver to make use of. JDBC classification 4 driver is used by means of default.

    Use the test Connection button to ensure the connection guidance you enter is valid. click on conclude.

    At this element, you have created a connection profile. Connection profiles contain tips about how to connect with a database comparable to indicating the class of authentication for use when connecting the database, specifying default schema, and configuring tracing alternatives. different group members can import the connection profiles to their own IBM records Studio and be able to installation a group of constant connection settings.

    To replace the connection profile, right-click the database and select residences. residences for the database are displayed as shown in determine four.29.

    usual Database Administration equipment

    There are few different beneficial administration initiatives accessible within the menu illustrated in figure 4.29.

    The manipulate Connection characteristic makes it possible for you to rename the connection profile, delete the connection profile, change the user identification and password, and replica the profile. The back Up and restore feature makes it possible for you to setup a database or desk space backups. in the appropriate editor, that you can specify the classification of backup, region of the backup pictures, and performance alternate options for the backup. Database backup and recuperation is mentioned in Chapter 10, “holding, Backing Up, and recuperating facts.”

    The deploy and Configure characteristic permits you to configure the database. Database configuration and this IBM statistics Studio function are coated in detail in Chapter 5. observe from the menu, you could launch the Configure computerized maintenance editor. DB2 gives automated upkeep capabilities for performing database backups, reorganizing tables and indexes, and updating the database statistics as vital. The editor allows you customise the computerized renovation policy (see determine 4.30).

    Figure 4.30

    determine four.30 select the computerized protection policy alternatives

    The manage Database feature enables you to start and stop the database. In DB2, that means activating and deactivating the database. Activating a database allocates all the crucial database memory and functions or techniques required. Deactivating a database releases the memory and prevents DB2 features and techniques.

    The computer screen characteristic launches the IBM records Studio web Console. check with the part, “IBM information Studio web Console,” for introduction of the tool.

    The Generate DDL function uses the DB2 command-based tool db2look to extract the facts Definition Language (DDL) statements for the identified database objects or the entire database. This function and gear come easy if you happen to wish to mimic a database, a group of database objects, or the database information to a different database. as a result of the Generate DDL characteristic in IBM information Studio or the DB2 command db2look, you receive a DDL script. The script contains statements to re-create the database objects you've got chosen. See figure four.31 for a reference of the styles of statements which you can generate the usage of the IBM data Studio.

    Figure 4.31

    determine four.31 Generate DDL feature in the IBM information Studio

    For finished alternatives for the DB2 command db2look, consult with the DB2 information middle.

    The delivery Tuning feature configures the database to allow question tuning. You could receive a warning indicating that you simply should spark off the InfoSphere Optim question Workload Tuner (OQWT) license for superior tuning capability. word that IBM DB2 superior commercial enterprise Server version comes with OQWT. observe the guidelines to practice the product license or click on sure to configure the database server for tuning with the points complementary in the IBM facts Studio.

    When the database is configured to make use of the tuning advisors and equipment, you're presented with the query Tuner Workflow Assistant, as proven in determine 4.32.

    From the question Tuner Workflow Assistant, that you can acquire a statement from a number of sources and tune the statement. in the capture view, it offers you a listing of sources where that you would be able to capture the statements. figure four.33 suggests an instance on taking pictures the SQL statements from the kit Cache. This illustration captures over one hundred statements. right-click on the remark in which you have an interest and choose display SQL observation or Run Single-question Advisors and tools on the selected statement.

    Run the question advisors and equipment on the selected statement. that you would be able to now enter the Invoke view. The device collects suggestions and data and generates a knowledge entry plan (see figure 4.34).

    When the question tuning actions are finished, you're brought to the evaluation view. It gifts you the analysis outcomes and an marketing consultant advice, such as the one proven in determine 4.35. The tool documentation recommends gathering and re-amassing all of vital facts of the question.

    you could additionally evaluation the entry plan graph generated by way of the DB2 explain characteristic (see figure 4.36 for an instance). remember to store the evaluation for future references and evaluate them if vital.

    The manipulate Privileges characteristic permits you to provide database privileges to the clients. confer with Chapter 8, “enforcing safety,” for particulars about privileges and database access controls.

    everyday Database building equipment

    IBM statistics Studio consolidates the database administration and database construction capabilities. From the task Launcher – enhance, you find an inventory of key development projects equivalent to creating and working SQL statements, debugging saved approaches, and consumer-defined capabilities (UDFs). every project brings you to a device that helps you accomplish it.

    SQL and XQuery Editor

    The SQL and XQuery editor helps you create and run SQL scripts that comprise multiple SQL and XQuery statements. To launch the editor, open the information project Explorer; below SQL Scripts opt for New > SQL or XQuery Script. As shown in figure four.37, a sample SQL script is entered. you can configure the run options for the script.

    The editor codecs the SQL statements nicely and provides syntax highlights for simpler analyzing as you enter the SQL statements. The performance content material support is additionally very advantageous. It lists the entire existing schemas within the database so that you can just select one from the drop-down menu. The editor additionally parses the statement and validates the statement syntax. you could validate the syntax in scripts with multiple database parsers and run scripts against multiple database connections.

    SQL query Builder

    The SQL query Builder makes it possible for you to create a single SQL commentary, but it surely does not support XQuery. as the name implies, the tool helps you construct an SQL statement. It helps you seem to be on the underlying database schema or build an expression, as shown in determine 4.38.

    Database Routines Editor and Debugger

    stored strategies and consumer-described capabilities (UDFs) are database utility objects that encapsulate application good judgment at the database server instead of in utility-level code. Use of software objects support cut back overhead of SQL statements and the results which are passed throughout the network. saved tactics and UDFs are also called routines. IBM facts Studio supports routines development and debugging.

    From the records venture Explorer, create a new statistics development task. within the challenge, you can create quite a few kinds of database utility objects akin to stored approaches and UDFs (see determine 4.39). To debug a hobbies, appropriate-click on the events and choose Debug.


    IBM InfoSphere Optim examine information administration solution for SAP functions - software Subscription and assist Renewal collection | killexams.com Real Questions and Pass4sure dumps

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    IBM specializes in counsel Governance with New software, features | killexams.com Real Questions and Pass4sure dumps

    IBM closing week announced two new items aimed toward helping businesses make certain that guidelines and guidelines involving access to suggestions are enforced. both products, Optim statistics Redaction and IBM InfoSphere company information display screen, will develop into purchasable in March. InfoSphere handiest will develop into purchasable to a choose neighborhood of customers. IBM additionally announced new features and a brand new core of Excellence dedicated to assistance governance.

    New regulations, such because the currently bolstered HIPAA and the hi-Tech Act, are inserting superior restraints on how corporations–especially organizations in the healthcare enterprise–manage delicate records. IBM has moved aggressively to fulfill these new necessities through the development of latest items, like the new Optim and InfoSphere equipment, and acquisitions, similar to remaining week’s announced acquisition of provoke, a developer of records integrity utility for groups within the healthcare and government industries.

    Optim information Redaction is the latest product to be part of the Optim family unit of equipment, which IBM bought through its 2007 acquisition of Princeton Softech. The utility is designed to automatically admire and take away sensitive content material from files and kinds. The application may be used by means of a bank, for example, to hide a consumer’s credit score ratings in a mortgage doc from an office clerk, while allowing it to be viewed via a loan officer, based on IBM.

    It’s no longer clear no matter if Optim data Redaction will work without delay with DB2/400; IBM did not say and particulars of the product don't seem to be yet accessible. If it’s like other Optim items, such because the archiving and look at various administration software for JD Edwards EnterpriseOne that work with DB2/400 and i/OS handiest through “toleration guide”, then it’s dubious a device i store would are looking to leap in the course of the hoops to make use of it, except they've loads of different statistics to give protection to on Unix, windows, Linux, and mainframe techniques.

    IBM noted that the upcoming InfoSphere company monitor product would work with all DB2 statistics, including, presumably, DB2/four hundred (which IBM officially calls DB2 for i), besides other important DBMSes, company intelligence techniques, and ERP methods. The utility is designed to alert directors when unexpected breaks within the stream of facts lift the probability of blunders constructing within the facts.

    IBM offers the illustration of a medical health insurance company this is inspecting income margins across distinctive product strains and geographies. If the information feed from one part of the realm did not make it into the aggregated database used for evaluation, InfoSphere business computer screen would alert the administrator to the difficulty, and steps may be taken to fix it.

    IBM says InfoSphere company computer screen is primarily based partially on know-how developed by Guardium, a database security software business that IBM obtained last fall. Guardium’s products received DB2/four hundred help last spring.

    large Blue’s international features unit also introduced the groundwork of a new company committed to assisting purchasers with their advice governance needs. called the IBM international enterprise services’ assistance Governance middle of Excellence (COE), the corporation can be capable of tap greater than 250 IBM professionals with knowledge within the design, building, and deployment of information governance initiatives.

    linked experiences

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    information masking tool from dataguise to Get DB2/400 aid

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    How Hadoop Keeps Even Small Businesses In the Loop for Big Data Analytics | killexams.com real questions and Pass4sure dumps

    Hadoop is a software system developed by Apache that allows a company’s data science team to process for analytical purposes large sets of data that are located on distributed servers.  The software framework is mainly used by those companies that want the capability of extracting unstructured data to improve things like business performance and customer relationship management.  This unstructured data is known in the industry as big data.  Every company that conducts physical and electronic transactions has access to big data, but it was not until recently that corporate leaders began to fully recognize big data’s potential to help them to forecast trends needed to improve competitive advantage.  Large businesses were at an advantage because they could purchase specialized hardware and hire the human resources that are needed to prepare the diverse data for analysis.  Convenient features like Excel reporting in Hadoop allow small businesses to harness the power of big data analytics as even non-technical users are able to access large data sets from inexpensive, off the shelf servers for data analysis projects.  Here are some other reasons why Hadoop is considered a leading tool for corporate data science teams.

    Use Hadoop With Leading Storage TechnologyHadoop has leveled the playing field for companies that want to effectively use big data to optimize their business processes.  For example, many medical companies collecting genetic data for advanced personalized medicine initially lacked the storage capacity needed for effective big data analysis.  Today, businesses of varying sizes use cloud storage options to expand their storage capabilities, and one of the most popular brands is Google Cloud Storage.  The value of Hadoop is well known in the information technology industry, and Google has responded by building a custom connector that integrates Google Cloud Storage with Hadoop.  Additionally, providers of storage area network and virtualization storage options have plans to integrate their products and services with Apache’s Hadoop.

    Tighten Up Big Data Security Using Third Party Tools and Add-OnsData security remains a hot button issue for many companies, non profit organizations and government agencies.  It seems that no organization is immune to attacks by hackers who want to steal information or corrupt the integrity of stored data.  As a result, many businesses are forced to pay fines or legal reparations for not adequately protecting the information entrusted to them, and other businesses experience productivity losses.  The storage and processing of big data by numerous companies just opens up a new path for cyber criminals because they have greater amounts of unsecured data to exploit.  Hadoop was not originally built with security mechanisms in place, but third party tools like IBM InfoSphere Optim Data Masking, Cloudera Sentry and DataStax Enterprise have incorporated authentication and data privacy features into their versions of Hadoop.  Many of these tools provide for the authentication of Hadoop processes, services and users; they also allow for the encryption of the Hadoop file system and data access blocking.  Maintenance and customer support are additional benefits of purchasing these distributed, third party versions of Hadoop versus using the free, original Apache product.

    Improve Big Data Processing Through Hadoop Integration With Popular IT System BrandsA great advantage of using Hadoop over other business intelligence software is the capability that it provides to developers and analysts to quickly extract and process large groupings of data.  The efficiency of processing is dependent on many factors including the location of the data and the server platform used.  Many businesses trust Microsoft’s brand and have outfitted their organization with the company’s servers, operating system and application software.  Although Microsoft’s products have been known not to be compatible with competing software systems,  the computing giant has taken great strides to update their flagship MS SQL Server product so that it and its Parallel Data Warehouse utility connects with Hadoop.  Microsoft Office applications like Excel have also been updated to integrate with the Apache product; this functionality allows Hadoop users to import data analysis output into a spreadsheet format.  The distributed version of Hadoop that is used by IBM’s InfoSphere BigInsights system also allows Hadoop users to view, analyze, graph and update data from multiple sources using a web based spreadsheet; IBM’s plan was to make their version of Hadoop the preferred one for business users. The fact that Hadoop can be implemented on these many platforms, and the many resources available to those learning it for the first time, make it the ideal product to use.

    Modify Hadoop To Extend FunctionalityAlthough the development team for the original Apache Hadoop software positively responds to the user community with value added updates, many businesses want to customize the open source software to quickly meet their organization’s’ unique needs.  Hadoop is Java based, but developers do not have to be Java programming experts to make modifications to the software framework. Database developers can use SQL similar scripting languages like Hive and Pig that are exclusively associated with Hadoop to add structure to data sets and import value added customizations into Hadoop.

    Author: Lindsey Patterson

    Lindsey Patterson is a freelance writer and entrepreneur who specializes in business technology, employee appreciation, and management. She loves music, poetry, and researching the latest trends.… View full profile ›

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    Top 10 IBM Information Management Trends | killexams.com real questions and Pass4sure dumps

    Julian Stuhler shares his pick of the most important current trends in the world of IBM Information Management. Some are completely new and some are evolutions of existing technologies, and he's betting that every one of them will have some sort of impact on data management professionals during the next 12-18 months.

    Introduction

    The Greek philosopher Heraclitus is credited with the saying "Nothing endures but change". Two millennia later those words still ring true, and nowhere more so than within the IT industry. Each year brings exciting new technologies, concepts and buzzwords for us to assimilate. Here is my pick of the most important current trends in the world of IBM Information Management. Some are completely new and some are evolutions of existing technologies, but I'm betting that every one of them will have some sort of impact on data management professionals during the next 12-18 months.

    1. Living on a Smarter Planet

    You don't have to be an IT professional to see that the world around us is getting smarter. Let's just take a look at a few examples from the world of motoring: we've become used to our in-car GPS systems giving us real-time traffic updates, signs outside car parks telling us exactly how many spaces are free, and even the cars themselves being smart enough to brake individual wheels in order to control a developing skid. All of these make our lives easier and safer by using real-time data to make smart decisions.

    However, all of this is just the beginning: everywhere you look the world is getting more "instrumented", and clever technologies are being adopted to use the real-time data to make things safer, quicker and greener. Smart electricity meters in homes are giving consumers the ability to monitor their energy usage in real time and make informed decisions on how they use it, resulting in an average reduction of 10% in a recent US study. Sophisticated traffic management systems in our cities are reducing congestion and improving fuel efficiency, with an estimated reduction in journey delays of 700,000 hours in another study covering 439 cities around the world.

    All of this has some obvious implications for the volume of data our systems will have to manage (see trend #2 below) but the IT impact goes a lot deeper than that. The very infrastructure that we run our IT systems on is also getting smarter. Virtualization technologies allow server images to be created on demand as capacity increases, and just as easily torn down again when the demand reduces. More extensive instrumentation and smarter analysis allows the peaks and troughs in demand to be more accurately measured and predicted so that capacity can be dynamically adjusted to cope. With up to 85% of server capacity typically sitting idle on distributed platforms, the ability to virtualize and consolidate multiple physical servers can save an enormous amount of power, money and valuable IT center floor space.

    If you live in the mainframe space, virtualization is an established technology that you've been working with for many years. If not, this might be a new way of thinking about your server environment. Either way, most of us will be managing our databases on virtual servers running on a more dynamic infrastructure in the near future.

    2. The Information Explosion

    As IT becomes ever more prevalent in nearly every aspect of our lives, the amount of data generated and stored continues to grow at an astounding rate. According to IBM, worldwide data volumes are currently doubling every two years. IDC estimates that 45GB of data currently exists for each person on the planet: that's a mind-blowing 281 billion gigabytes in total. While a mere 5 percent of that data will end up on enterprise data servers, it is forecast to grow at a staggering 60 percent per year, resulting in 14 exabytes of corporate data by 2011.

    Major industry trends such as the move towards packaged ERP and CRM applications, increased regulatory and audit requirements, investment in advanced analytics and major company mergers and acquisitions are all contributing to this explosion of data, and the move towards instrumenting our planet (see trend #1 above) is only going to make things worse.

    As the custodians of the world's corporate data, we are at the sharp end of this particular trend. We're being forced to get more inventive with database partitioning schemes to reduce the performance and operational impact of increased data volumes. Archiving strategies, usually an afterthought for many new applications, are becoming increasingly important. The move to a 64-bit memory model on all major computing platforms allows us to design our systems to hold much more data in memory rather than on disk, further reducing the performance impact. As volumes continue to increase and new types of data such as XML and geospatial information are integrated into our corporate data stores (see trend #5), we'll have to get even more inventive.

    3. Hardware Assist

    OK, so this is not a new trend: some of the earliest desktop PCs had the option to fit coprocessors to speed up floating point arithmetic, and the mainframe has used many types of supplementary hardware over the years to boost specific functions such as sort and encryption. However, use of special hardware is becoming ever more important on all of the major computing platforms.

    In 2004, IBM introduced the zAAP (System z Application Assist Processor), a special type of processor aimed at Java workloads running under z/OS. Two years later, it introduced the zIIP (System z Integrated Information Processor) which was designed to offload specific types of data and transaction processing workloads for business intelligence, ERP and CRM, and network encryption. In both cases, work can be offloaded from the general-purpose processors to improve overall capacity and significantly reduce running costs (as most mainframe customers pay according to how much CPU they burn on their general-purpose processors). These "specialty coprocessors" have been a critical factor in keeping the mainframe cost-competitive with other platforms, and allow IBM to easily tweak the overall TCO proposition for the System z platform. IBM has previewed its Smart Analytics Optimizer blade for System z (see trend #9) and is about to release details of the next generation of mainframe servers: we can expect the theme of workload optimization through dedicated hardware to continue.

    On the distributed computing platform, things have taken a different turn. The GPU (graphics processing unit), previously only of interest to CAD designers and hard-core gamers, is gradually establishing itself as a formidable computing platform in its own right. The capability to run hundreds or thousands of parallel processes is proving valuable for all sorts of applications, and a new movement called CPGPU (General-Purpose computation on Graphics Processing Units) is rapidly gaining ground. It is very early days, but many database operations (including joins, sorting, data visualization and spatial data access) have already been proven and the mainframe database vendors won't be far behind.

    4. Versioned/Temporal Data

    As the major relational database technologies continue to mature, it's getting more and more difficult to distinguish between them on the basis of pure functionality. In that kind of environment, it's a real treat when a vendor comes up with a major new feature, which is both fundamentally new and immediately useful. The temporal data capabilities being delivered as part of DB2 10 for z/OS qualify on both counts.

    Many IT systems need to keep some form of historical information in addition to the current status for a given business object. For example, a financial institution may need to retain the previous addresses of a customer as well as the one they are currently living at, and know what address applied at any given time. Previously, this would have required the DBA and application developers to spend valuable time creating the code and database design to support the historical perspective, while minimizing any performance impact.

    The new temporal data support in DB2 10 for z/OS provides this functionality as part of the core database engine. All you need to do is indicate which tables/columns require temporal support, and DB2 will automatically maintain the history whenever an update is made to the data. Elegant SQL support allows the developer to query the database with an "as of" date, which will return the information that was current at the specified time.

    With the ongoing focus on improving productivity and reducing time-to-market for key new IT systems, you can expect other databases (both IBM and non-IBM) to implement this feature sooner rather than later.

    5. The Rise of XML and Spatial Data

    Most relational databases have been able to store "unstructured" data such as photographs and scanned images for a while now, in the form of BLOBS (Binary Large OBjects). This has proven useful in some situations, but most businesses use specialized applications such as IBM Content Manager to handle this information more effectively than a general-purpose database. These kind of applications typically do not have to perform any significant processing on the BLOB itself - they merely store and retrieve it according to externally defined index metadata.

    In contrast, there are some kinds of non-traditional data that need to be fully understood by the database system so that it can be integrated with structured data and queried using the full power of SQL. The two most powerful examples of this are XML and spatial data, supported as special data types within the latest versions of both DB2 for z/OS and DB2 for LUW.

    More and more organizations are coming to rely on some form of XML as the primary means of data interchange, both internally between applications and externally when communicating with third-parties. As the volume of critical XML business documents increases, so too does the need to properly store and retrieve those documents alongside other business information. DB2's pureXML feature allows XML documents to be stored natively in a specially designed XML data store, which sits alongside the traditional relational engine. This is not a new feature any more, but the trend I've observed is that more organizations are beginning to actually make use of pureXML within their systems. The ability to offload some XML parsing work to a zAAP coprocessor (see trend #3) is certainly helping.

    Nearly all of our existing applications contain a wealth of spatial data (customer addresses, supplier locations, store locations, etc): the trouble is we're unable to use it properly as it's in the form of simple text fields. The spatial abilities within DB2 allow that data to be "geoencoded" in a separate column, so that the full power of SQL can be unleashed. Want to know how many customers live within a 10-mile radius of your new store? Or if a property you're about to insure is within a known flood plain or high crime area? All of this and much more is possible with simple SQL queries. Again, this is not a brand new feature but more and more organizations are beginning to see the potential and design applications to exploit this feature.

    6. Application Portability

    Despite the relative maturity of the relational database marketplace, there is still fierce competition for overall market share between the top three vendors. IBM, Oracle and Microsoft are the main protagonists, and each company is constantly looking for new ways to tempt their competitor's customers to defect. Those brave souls that undertook migration projects in the past faced a difficult process, often entailing significant effort and risk to port the database and associated applications to run on the new platform. This made large-scale migrations relatively rare, even when there were compelling cost or functionality reasons to move to another platform.

    Two trends are changing this and making porting projects more common. The first is the rise of the packaged ERP/CRM solution from companies such as SAP and Siebel. These applications have been written to be largely database agnostic, with the core business logic isolated from the underlying database by an "I/O layer". So, while there may still be good reasons to be on a specific vendor's database in terms of functionality or price, the pain of moving from one to another is vastly reduced and the process is supported by the ERP solution vendor with additional tooling. Over 100 SAP/Oracle customers are known to have switched to DB2 during the past 12 months for example, including huge organizations such as Coca-Cola.

    The second and more recent trend is direct support for competitor's database APIs. DB2 for LUW version 9.7 includes a host of new Oracle compatibility features that makes it possible to run the vast majority of Oracle applications natively against DB2 with little or no change required to the code. IBM has also announced the "DB2 SQL Skin" feature, which provides similar capabilities for Sybase ASE applications to run against DB2. With these features greatly reducing the cost and risk of changing the application code to work with a different database, all that is left is to physically port the database structures and data to the new platform (which is a relatively straightforward process that is well supported by vendor tooling). There is a huge amount of excitement about these new features and IBM is expecting to see a significant number of Oracle customers switch to DB2 in the coming year. I'm expecting IBM to continue to pursue this strategy by targeting other databases such as SQL Server, and Oracle and Microsoft may well return the favor if they begin to lose significant market share as a result.

    7. Scalability and Availability

    The ability to provide unparalleled scalability and availability for DB2 databases is not new: high-end mainframe users have been enjoying the benefits of DB2 Data Sharing and Parallel Sysplex for more than 15 years. The shared-disk architecture and advanced optimizations employed in this technology allow customers to run mission-critical systems with 24x7 availability and no single point of failure, with only a minimal performance penalty. Major increases in workload can be accommodated by adding additional members to the data sharing group, providing an easy way to scale.

    Two developments have resulted in this making my top 10 trends list. Firstly, I'm seeing a significant number of mainframe customers who had not previously taken advantage of data sharing begin to take the plunge. There are various reasons for this, but we've definitely moved away from the days when DB2 for z/OS data sharing customers were a minority group huddling together at conferences and speaking a different language to everyone else.

    The second reason that this is set to be big news over the next year is DB2 pureScale: the implementation of the same data sharing shared-disk concepts on the DB2 for LUW platform. It's difficult to overstate the potential impact this could have on distributed DB2 customers that run high volume mission critical applications. Before pureScale, those customers had to rely on features such as HADR to provide failover support to a separate server (which could require many seconds to take over in the event of a failure) or go to external suppliers such as Xkoto with their Gridscale solution (no longer an option since the company was acquired by Teradata and the product was removed from the market). pureScale brings DB2 for LUW into the same ballpark as DB2 for z/OS in terms of scalability and availability, and I'm expecting a lot of customer activity in this area over the next year.

    8. Stack 'em high...

    For some time now, it has been possible for organizations to take a "pick and mix" approach to their IT infrastructure, selecting the best hardware, operating system, database and even packaged application for their needs. This allowed IT staff to concentrate on building skills and experience in specific vendor's products, thereby reducing support costs.

    Recent acquisitions have begun to put this environment under threat. Oracle's previous purchase of ERP vendors such as Peoplesoft, Siebel and JD Edwards had already resulted in big pressure to use Oracle as the back-end database for those applications (even if DB2 and other databases are still officially supported). That reinforced SAP's alliance with IBM and the push to run their applications on DB2 (again, other databases are supported but not encouraged).

    Two acquisitions during the past 12 months have further eroded the "mix and match" approach, and started a trend towards single-vendor end-to-end solution "stacks" comprising hardware, OS, database and application. The first and most significant of these was Oracle's acquisition of Sun Microsystems in January 2010. This gave the company access to Sun's well-respected server technology and the Solaris OS that runs on it. At a single stroke, Oracle was able to offer potential customers a completely integrated hardware/software/application stack.

    The jury is still out on the potential impact of the second acquisition: SAP's purchase of Sybase in May 2010. Although the official SAP position is that the Sybase technology has been purchased for the enhanced mobile and in-memory computing technologies that Sybase will bring, there is the possibility that SAP will choose to integrate the Sybase database technology into the SAP product. That will still leave them dependent on other vendors such as IBM for the hardware and operating system, but it would be a major step forward in any integration strategy they may have.

    Older readers of this article may see some startling similarities to the bad old days of vendor lock-in prevalent in the 1970s and 1980s. IBM's strategy to support other vendor's database APIs (see trend # 6) is in direct contrast to this, and it will be interesting to see how far customers are willing to go down the single vendor route.

    9. BI on the Mainframe

    The concept of running Business Intelligence applications on the mainframe is not new: DB2 was originally marketed as a back-end decision support application for IMS databases. The ability to build a warehouse within the same environment as your operational data resides (and thereby avoid the expensive and time-consuming process of moving that data to another platform for analysis) is attractive to many customers.

    IBM is making significant efforts to make this an attractive proposition for more of their mainframe customers. The Cognos tools have been available for zLinux for a couple of years now, and the DB2 for z/OS development team have been steadily adding BI-related functions to the core database engine for years. Significant portions of a typical BI workload can also be offloaded to a zIIP coprocessor (see trend # 3), reducing the CPU costs.

    More recently, IBM unveiled its Smart Analytics System 9600 - an integrated, workload balanced bundle of hardware, software and services based on System z and DB2 for z/OS. It has also begun to talk about the Smart Analytics Optimizer - a high performance appliance-like blade for System z capable of handling intensive BI query workloads with minimal impact to CPU.

    IBM is serious about BI on the mainframe, and is building an increasingly compelling cost and functionality case to support it.

    10. Data Governance

    Ensuring that sensitive data is properly secured and audited has always been a concern, but this has received more attention in recent years due to legislation such as Sarbanes-Oxley, HIPAA and others. At the same time, there has been an increasing focus on data quality: bad data can result in bad business decisions, which no one can afford in today's competitive markets. There has also been an increasing awareness of data as both an asset and a potential liability, making archiving and lifecycle management more important.

    All of these disciplines and more and beginning to come together under the general heading of data governance. As our database systems get smarter and more self-managing, database professionals are increasingly morphing from data administrators to data governors. A new generation of tools is being rolled out to help, including Infosphere Information Analyser, Guardium and the Optim data management products.

    Additional Resources

    IBM's Smarter Planet initiativeIBM's zIIP Home PageDatabase operations using the GPUDB2 10 for z/OSpureXMLDB2 9.7: Run Oracle applications on DB2 9.7 for Linux, Unix, and WindowspureScaleIBM Smart Analytics OptimizeIBM Smart Analytics System 9600IBM Data governance

    » See All Articles by Columnist Julian Stuhler


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

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

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

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

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

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

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

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

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

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

    Related items:

    Hadoop Sharks Smell Blood; Take Aim at Status Quo

    Hadoop Distros Orbit Around Solr

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



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