This KM423G: IBM InfoSphere DataStage v11.x – Advanced Data Processing course is designed to introduce you to advanced parallel job data processing techniques in DataStage v11.5. In this course you will develop data techniques for processing different types of complex data resources including relational data, unstructured data (Excel spreadsheets), and XML data. In addition, you will learn advanced techniques for processing data, including techniques for masking data and techniques for validating data using data rules. Finally, you will learn techniques for updating data in a star schema data warehouse using the DataStage SCD (Slowly Changing Dimensions) stage. Even if you are not working with all of these specific types of data, you will benefit from this course by learning advanced DataStage job design techniques, techniques that go beyond those utilized in the DataStage Essentials course.
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This 0A079G: Introduction to Machine Learning Models Using IBM SPSS Modeler v18.2 course provides an introduction to supervised models, unsupervised models, and association models. This is an application-oriented course and examples include predicting whether customers cancel their subscription, predicting property values, segment customers based on usage, and market basket analysis.
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This course is an intermediate course designed to teach Collaboration and Deployment users object and asset management, security, shared resource usage, automation, and interaction with IBM SPSS Modeler Gold. Students focus on the makeup of the content repository and its objects. They will learn how to manage repository objects, the logical hierarchy structure, and how to import, export, and promote objects for use in multi-repository environments. Students will become familiar with the components of jobs and the mechanisms to set up, order, and relate job steps. Scheduling, parameters, job monitoring, job history, and event notification are discussed. Finally, the role of Collaboration and Deployment Services in Modeler Gold is discussed, addressing Real Time Scoring, Analytic Data View, and Model Management.
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This course provides participants with introductory to advanced knowledge of how to model metadata for predictable reporting and analysis results using IBM Cognos Cube Designer. Participants will learn the full scope of the metadata modeling process, from initial project creation, to publishing a dynamic cube, and enabling end users to easily author reports and analyze data.
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The InfoSphere MDM Application Toolkit course introduces students to the Business Process Manager (BPM) and the Process Designer to create processes that will use MDM data and services.
This course has a heavy emphasis on exercises and takes a participant through creating a process to search and update a customers address. The search, get and update services are performed against the InfoSphere MDM.
If you are looking to get an introduction to how BPM and MDM can work together using the MDM Application Toolkit, then this course is for you.
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Do you want to find match member records, link member records, and perfect a search algorithm for your InfoSphere MDM Virtual implementation?
Then this course is designed for you. The InfoSphere MDM Virtual Module Algorithms V.11 course prepares students to work with and customize the algorithm configurations deployed to the InfoSphere MDM Probabilistic Matching Engine (PME) for Virtual MDM implementations. The PME is the heart of all Matching, Linking, and Searching for entities (Person, Organization, etc) that exist in InfoSphere MDM. This course has a heavy emphasis on the exercises, where the students will implement the customization discussed in the course to perform matching, linking, and searching on fields not provided by the default implementation.
At the end of this course, it is expected that students will feel comfortable customizing an algorithm for the PME for Virtual implementations.
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This course is designed to teach participants how to identify components and sub-components of the IBM Cognos Analytics architecture and how to use tools and techniques to provide a foundation to troubleshoot issues. Through lecture and interactive exercises participants will identify IBM Cognos Analytics components, examine how these components interact with Java, and will explore logging to assist when troubleshooting issues.
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This course is designed to guide report authors in building on their expertise with IBM Cognos Analytics by applying dimensional techniques to reports. Through interactive demonstrations and exercises, participants will learn how to author reports that navigate and manipulate dimensional data structures using the specific dimensional functions and features available in IBM Cognos Analytics.
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This course teaches database administrators how to plan, implement and manage Db2 11.1 databases using the High Availability Disaster Recovery HADR) feature. The lectures cover the processing performed for a Db2 Primary and Standby Db2 database. The Db2 database configuration options that define and control the HADR function are covered. The option to define and operate multiple HADR standby databases will be explained. The course also covers the special considerations for allowing read only access by applications to a HADR Standby database. Students will learn the Db2 commands like TAKEOVER, START HADR and STOP HADR that are used to control HADR primary and standby database activity. The monitoring for HADR status of the primary and standby databases using the db2pd commands will be presented. The course also presents usage of HADR with Db2 pureScale databases.
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In this 2M803G: IBM Information Analyzer Essentials v11.5 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.
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This course teaches how to build QualityStage parallel jobs that investigate, standardize, match, and consolidate data records. Students will gain experience by building an application that combines customer data from three source systems into a single master customer record.
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This course teaches you to perform, basic and advanced, database administrative tasks using Db2 11.1. 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).
The lab demonstrations are performed using DB2 LUW 11.1 for Linux. For some lab tasks, students will have the option to complete the task using a DB2 command line processor, or using the graphical interface provided by IBM Data Server Manager.
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.
