IBM

This offering covers the fundamental concepts of installing and configuring IBM Cognos Analytics, and administering servers and content, in a distributed environment. In the course, participants will identify requirements for the installation and configuration of a distributed IBM Cognos Analytics software environment, implement security in the environment, and manage the server components. Students will also monitor and schedule tasks, create data sources, and manage and deploy content in the portal and IBM Cognos Administration.

This course is designed as the starting point for any technical specialist working with the InfoSphere MDM Virtual module. This course walks you through the major components of the InfoSphere MDM Virtual module, the data model, the matching engine and how customization can be implemented. You will learn how to invoke the InfoSphere MDM interactions and the various configuration and extension points of a service. The course is also used as an intro to various components that make up the MDM Architecture and prepares you to identify how the MDM will fit into their organization and what pieces may be customize to fit their business requirements. This course has a heavy emphasis on the exercises, where you will deploy a new MDM configuration, invoke interactions, walk through the default matching algorithm, and create a custom handler and composite view. At the end of this course, it is expected that you will feel comfortable implementing a new Virtual configuration data model, invoking interactions and creating customization to the Virtual MDM

This course teaches you to perform, basic and advanced, database administrative tasks using DB2 10.5 for Linux, UNIX, and Windows. These tasks include creating and populating databases and implementing a logical design to support recovery requirements. The access strategies selected by the DB2 Optimizer will be examined using the DB2 Explain tools. Various diagnostic methods will be presented, including using various db2pd command options. Students will learn how to implement automatic archival for database logs and how to plan a redirected database restore to relocate either selected table spaces or an entire database. The REBUILD option of RESTORE, which can build a database copy with a subset of the tablespaces, will be discussed. We will also cover using the TRANSPORT option of RESTORE to copy schemas of objects between two DB2 databases. The selection of indexes to improve application performance and the use of SQL statements to track database performance and health will be covered. This course provides a quick start to DB2 database administration skills for experienced relational Database Administrators (DBA)

This course is designed to teach you how to: Perform advanced monitoring using the Db2 administrative views and routines in SQL queries. Manage the disk space assigned in Database Managed Storage (DMS) and Automatic Storage table spaces, including the activities of the rebalancer. Use SQL queries and Db2 commands to check the high water mark on table spaces and to monitor the rebalance operation. Utilize the REBUILD option of RESTORE, which can build a database copy with a subset of the tablespaces using database or tablespace backup images. Plan and execute the TRANSPORT option of RESTORE to copy schemas of objects between two Db2 databases. Create incremental database or tablespace level backups to reduce backup processing and backup image storage requirements. Implement automatic storage management for table spaces and storage groups or enable automatic resize options for DMS managed table spaces to reduce administration requirements and complexity. Describe the various types of database memory including buffer pools, sort memory, lock memory and utility processing memory. Adjust database or Db2 instance configuration options to improve application performance or processing efficiency. Implement Db2 Self Tuning Memory management for specific database memory areas.

This course presents advanced models available in IBM SPSS Modeler. The participant is first introduced to a technique named PCA/Factor, to reduce the number of fields to a number of core factors, referred to as components or factors. The next topics focus on supervised models, including Support Vector Machines, Random Trees, and XGBoost. Methods are reviewed on how to analyze text data, combine individual models into a single model, and how to enhance the power of IBM SPSS Modeler by adding external models, developed in Python or R, to the Modeling palette.

This course explores different options for customizing and extending the features of IBM Case Manager including developing widgets

Learn how to create document and folder classes and properties, and how to create event subscriptions on those classes to run automated actions. 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 modelers how to build a complete model in IBM Planning Analytics using the Architect tool. Through a series of lectures and hands-on exercises, students will learn how to set up and verify dimensions, cubes, and views, manually enter data into these structures, and define the data that users can see. Students will also learn how to transfer data into the IBM Planning Analytics model, including the use of Turbo Integrator scripts to perform data transfer. In addition, the course outlines how to customize drill paths, convert currencies, model for different fiscal requirements, and deploy IBM Planning Analytics applications to the web.

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.

This course is for administrators that maintain IBM FileNet Content Manager environments, and need to learn: How to monitor the system logs and enable trace logging to troubleshoot issues. How to use auditing to trace object activity. 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 provides participants with introductory to advanced knowledge of metadata modeling concepts, and how to model metadata for predictable reporting and analysis results using Framework Manager. Participants will learn the full scope of the metadata modeling process, from initial project creation, to publishing of metadata to the Web, enabling end users to easily author reports and analyze data.

This course provides training to new administrators on the fundamental tasks of installing and configuring IBM Cognos Analytics, and administering servers and content in the environment. In the course, participants will install and configure the IBM Cognos Analytics software, implement security, and manage the server components. Students will also monitor and schedule tasks, create data sources, and manage and deploy content in the portal and IBM Cognos Administration.

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 provides students with an introduction to the skills and knowledge needed to administer a Db2 12 for z/OS system.

This course is for those who administer and maintain an IBM Enterprise Records system. You work with a fully functioning IBM Enterprise Records system to practice the skills required for system configuration, administration, and system maintenance.

This course is designed to aid programmers who are working with IBM’s InfoSphere BigInsights. Writing programs that extract data from unstructured text can be a daunting task. You will learn how to create annotators through the use of IBM’s Annotation Query Language (AQL). Analyzing data using Apaches Hadoop normally requires that MapReduce programs be written. You will learn how to use Jaql to create high level programs that are decomposed into Hadoop MapReduce programs. People familiar with the Hadoop technology are aware of other open source products that are used in this environment. This course will give you a foundation to program using the Apache Pig language. There is also overview of ZooKeeper, HBase, and Hive. One of the capabilities of the BigInsights Web Console is the ability to simplify the invocation of Hadoop applications. This course shows how to publish a text analytics application from the BigInsights development environment to a BigInsights server.

This course (formerly: Introduction to IBM SPSS Text Analytics for IBM SPSS Modeler (v18)) teaches you how to analyze text data using IBM SPSS Modeler Text Analytics. You will be introduced to the complete set of steps involved in working with text data, from reading the text data to creating the final categories for additional analysis. After the final model has been created, there is an example of how to apply the model to perform churn analysis in telecommunications. Topics include how to automatically and manually create and modify categories, how to edit synonym, type, and exclude dictionaries, and how to perform Text Link Analysis and Cluster Analysis with text data. Also included are examples of how to create resource tempates and Text Analysis packages to share with other projects and other users.

This course trains : The skills that are needed to configure a workflow system to support FileNet workflow applications. The skills that are needed to configure an IBM Content Navigator desktop for workflow.