IBM

This is a self-paced online course. The average amount of time to complete this course is 40 hours. Once you receive your access information, you will have 60 days  to complete this course. Please do not make travel arrangements for this course. After you receive confirmation that you are enrolled, you will be sent further instructions to access the course. This introductory course, Programming with IBM InfoSphere MDM Collaborative Edition V10.1, is a must for those wanting to learn how to setup their environment and begin programming with MDM CE. Using IBM's Implementation Methodology Approach (use cases), the developer will have first hand experience building a solution that will ncorporate the functionalities of the MDM CE product. This course will provide the developer with an initial understanding of the MDM CE Object Data Model and migrate towards programming a solution and finally understand the Best Practices for programming with MDM CE product. The self-paced format gives you the opportunity to complete the course at your convenience, at any location, and at your own pace. The course is available 24 hours a day. Once you have accessed the course, instructor help is available via the course forum Monday through Friday; questions will be responded to within 24 hours. If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course.

This offering provides analysts with an introduction to create dashboards with Cloud Pak for Data, and create dashboards and reports using the Cognos Analytics add-on.

In this course, students will develop the skills necessary to administer one or more Informix database servers.  They will learn how to configure and utilize a database server instance, configure and test client connectivity, configure and manage memory and disk usage, plan and implement system maintenance tasks, and configure the server for optimal Online Transaction Processing (OLTP) or decision support (DS) utilization. If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course.

This course is designed to teach the you about the Streams Processing Language. It will begin with the basic concepts of InfoSphere Streams and the basic Streams Processing Language operators used in a Streams program. You will learn how to access data from an external source using the Source type operators and write an output stream using the Sink type operators. You will then learn how and when to use the various Stream operators, like the Functor, Punctor, Aggregation, Sort, Join, Split, Barrier, Delay, and Switch operators. Lab exercises will use the InfoSphere Streams IDE that is based upon Eclipse as the development and testing environment, but the you will get the opportunity to invoke the compilation of a Streams program from the command line as well. In the labs you will be given the choice to develop the applications using the SPL Graphical Editor, introduced in Version 3, that allows drag and drop or the original SPL Editor that is text based. The second half of the course shows how to control the placement of processing elements and the debugging capabilities of the Streams Processing Language. You will learn about consistent regions and how to use them to process tuples at-least-once. You will be introduced to the various toolkits supplied with InfoSphere Streams and work with data mining and database toolkits in a lab. Finally, you will be shown how to extend the Streams Processing Language through the development of user-defined functions and both generic and non-generic primitive operators. Both C++ and Java non-generic primitive operators are covered. If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course.

This course is designed to introduce the student to some of the additional capabilities and the administration of IBM Big SQL. IBM Big SQL allows you to access your HDFS data by providing a logical view to it. You can use the same SQL that was developed for your data warehouse data on your HDFS data. This course covers Big SQL security using row and column access controls, impersonation, and data federation. The course also covers some of the best practices, performance tuning, and monitoring techniques, YARN integration and also includes an optional unit to explore a Big SQL installation.  If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course.

Learn how to use IBM® BigInsights® Text Analytics, an information extraction system, to extract information from unstructured and semi-structured documents. Using IBM BigInsights Text Analytics you can create extractors using a visual web interface. The visual extractors are then automatically translated into Annotation Query Language (AQL) rules to extract structured information from unstructured and semi-structured documents. You can apply Text Analytics to big data at rest in IBM BigInsights and big data in motion in IBM Streams.

This course is designed to introduce you to the capabilities of BigSheets. BigSheets is a component of IBM BigInsights through the Analyst and the Data Scientist module. It provides the analyst the ability to be able to visualize and analyze data stored on the HDFS using a spreadsheet type interface without any programming. If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course.

This course is designed to introduce the student to the capabilities of IBM Big SQL. IBM Big SQL allows you to access your HDFS data by providing a logical view to it. You can use the same SQL that was developed for your data warehouse data on your HDFS data. This course provides context on why you would use Big SQL followed by how to use Big SQL to access your data. It also covers what Big SQL is, how it is used, and the Big SQL architecture. The course also covers how to connect to Big SQL, create tables with a variety of data types, load data in, and run queries against the data. The course also shows how to use Big SQL with other components of the Hadoop ecosystem. If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course. 

This training course is for those who want a foundation of IBM BigInsights. This course consists of two separate modules. The first module is IBM BigInsights Overview and it will give you an overview of IBM's big data strategy as well as a why it is important to understand and use big data. It will cover IBM BigInsights as a platform for managing and gaining insights from your big data. As such, you will see how the BigInsights have aligned their offerings to better suit your needs with the IBM Open Platform (IOP) along with the three specialized modules with value-add that sits on top of the IOP. Along with that, you will get an introduction to the BigInsights value-add including Big SQL, BigSheets, and Big R. The second module is IBM Open Platform with Apache Hadoop. IBM Open Platform (IOP) with Apache Hadoop is the first premiere collaborative platform to enable Big Data solutions to be developed on the common set of Apache Hadoop technologies. The Open Data Platform initiative (ODP) is a shared industry effort focused on promoting and advancing the state of Apache Hadoop and Big Data technologies for the enterprise. The current ecosystem is challenged and slowed by fragmented and duplicated efforts between different groups. The ODP Core will take the guesswork out of the process and accelerate many use cases by running on a common platform. It allows enterprises to focus on building business driven applications. This module provides an in-depth introduction to the main components of the ODP core --namely Apache Hadoop (inclusive of HDFS, YARN, and MapReduce) and Apache Ambari -- as well as providing a treatment of the main open-source components that are generally made available with the ODP core in a production Hadoop cluster. IBM BigInsights v4 itself is built upon the ODP core and these other main open-source components.The relationships between the IBM Open Platform with Apache Hadoop and the BigInsights add-ons is covered briefly in Unit 1 – pro. If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course.

IBM Open Platform (IOP) with Apache Hadoop is the first premiere collaborative platform to enable Big Data solutions to be developed on the common set of Apache Hadoop technologies. The Open Data Platform initiative (ODP) is a shared industry effort focused on promoting and advancing the state of Apache Hadoop and Big Data technologies for the enterprise. The current ecosystem is challenged and slowed by fragmented and duplicated efforts between different groups. The ODP Core will take the guesswork out of the process and accelerate many use cases by running on a common platform. It allows enterprises to focus on building business driven applications. This module provides an in-depth introduction to the main components of the ODP core --namely Apache Hadoop (inclusive of HDFS, YARN, and MapReduce) and Apache Ambari -- as well as providing a treatment of the main open-source components that are generally made available with the ODP core in a production Hadoop cluster. If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course.

You will have an overview of IBM's big data strategy and review why it is important to understand and use big data. It will cover IBM BigInsights as a platform for managing and gaining insights from your big data. As such, you will see how the BigInsights have aligned their offerings to better suit your needs with the IBM Open Platform (IOP) along with the three specialized modules with value-add that sits on top of the IOP. You will also get an introduction to the BigInsights value-add including Big SQL, BigSheets, and Big R. The participant will be engaged with the product through interactive exercises. If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course.

This course will teach you how to utilize the IBM InfoSphere Optim Solutions - Test Data Management, Data Privacy, and Data Growth for Archiving - for Distributed Platforms. You will learn how to create "right-sized" test data environments with the Test Data Management Solution; how to privatize confidential data with the Data Privacy Solution; and how to archive retired data with the Data Growth Solution. This course focuses on the technical aspects of the Optim Solutions and is intended for technical audiences. You learn the basics of how the Solutions work through hands on exercises illustrating how the technology applies to business scenarios. This course does not include information on how to install and configure the Optim technology. If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course. 

In this course, you will learn how to use the IBM InfoSphere suite to analyze data and report results to business users. Information discovered during analysis will be used to construct data rules. This course will also explore techniques for delivering data analysis results to ETL developers and demonstrate how to develop more meaningful meta data to reflect data discovery results. An information analysis methodology and a case study will be used to guide exercises

In this course, students will learn the basic concepts of data management with Informix 12.10.  They will learn how to create, manage, and maintain tables and indexes; how the Informix Optimizer works; and how to use the SET EXPLAIN feature to determine query effectiveness. If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course.

This course enables the student to acquire the skills necessary to administer an IBM Streams system. The course covers creating Streams domains and instances, using ZooKeeper in a high availability environment, viewing the state of Streams domain and instance services, stopping and starting processing elements, viewing the jobs and processing elements that are running, and a variety of other topics. In addition it covers defining resource tags, adding a resource to a Streams domain and instance, setting the access control list for security objects to give permission to users to work with those objects, and submitting and cancelling Streams jobs. If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course.

This course enables students to acquire the skills necessary to use the Information Governance Catalog to analyze metadata stored within the Information Server Repository. The emphasis is on how metadata gets captured within the repository and how to explore and analyze the metadata it contains. If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course.

IBM Stewardship Center for Information Server v11.5 provides event notification with workflow and remediation. Business users can be notified and respond to Information Server events, when they occur. These events include data quality exceptions occurring in Information Server products such as DataStage and Information Analyzer. These events also include catalog edits to governance categories and terms occurring within the Information Governance Catalog. If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course.

In this course students learn how the Information Governance Catalog is used to govern information assets through the development of a governance catalog of categories and terms. This catalog documents information assets and governance policies and rules that implement the high-level strategy and objectives of a governance program. If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course.