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.
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This 0A039G: Advanced Machine Learning Models Using IBM SPSS Modeler (V18.2) 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.
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This IBM Predictive Modeling training course provides an overview of how to use IBM SPSS Modeler to predict a target field that describes numeric values. Students will be exposed to rule induction models such as CHAID and CR Tree. They will also be introduced to traditional statistical models such as Linear Regression. Students are introduced to machine learning models, such as Neural Networks. Business use case examples include: predicting the length of subscription for newspapers, telecommunication, and job length, as well as predicting insurance claim amounts.
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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.
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. http://www.ibm.com/training/terms
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This course gets those charged with administering Information Server v11.5 and its suite of many products and components started with the basic administrative tasks necessary to support Information Server users and developers.
The course begins with a functional overview of Information Server and the products and components that support these functions. Then it focuses on the basic administrative tasks an Information Server administrator will need to perform including user management, session management, and reporting management tasks. The course covers both the use of Information Server administrative clients such as the Administration Console and Metadata Asset Manager and the use of command line tools such as istool and encrypt.
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This 0E069G: IBM SPSS Modeler Foundations v18.2 course provides the foundations of using IBM SPSS Modeler and introduces the participant to data science. The principles and practice of data science are illustrated using the CRISP-DM methodology. The course provides training in the basics of how to import, explore, and prepare data with IBM SPSS Modeler v18.2, and introduces the student to modeling.
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. http://www.ibm.com/training/terms
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Master the art of text analytics with IBM SPSS Modeler: From Data to Insights in 1 course.
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 templates and Text Analysis packages to share with other projects and other users.
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. http://www.ibm.com/training/terms
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This 0G09BG: Advanced Statistical Analysis Using IBM SPSS Statistics v26 course provides an application-oriented introduction to advanced statistical methods available in IBM SPSS Statistics. Students will review a variety of advanced statistical techniques and discuss situations in which each technique would be used, the assumptions made by each method, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for predicting variables, as well as methods to cluster variables and cases.
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This course guides students through the fundamentals of using IBM SPSS Statistics for typical data analysis. Students will learn the basics of reading data, data definition, data modification, data analysis, and presentation of analytical results. In addition to the fundamentals, students will learn shortcuts that will help them save time. This course uses the IBM SPSS Statistics Base; one section presents an add-on module, IBM SPSS Custom Tables.
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This J1357G: IBM Planning Analytics: Analyze Data and Create Reports course is designed to teach analysts how to use IBM Planning Analytics to analyze data to discover trends and exceptions, create and customize reports and templates, and contribute data to plans. Through a series of lectures and hands-on activities, you will learn how use Planning Analytics Workspace and Planning Analytics for Microsoft Excel to create analyses, enter data, create custom views and dashboards, and build formatted reports and forms.
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This offering teaches Professional Report Authors about advanced report building techniques using relational data models, dimensional data, and ways of enhancing, customizing, managing, and distributing professional reports. The course builds on topics presented in the Fundamentals course. Activities will illustrate and reinforce key concepts during this learning 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.
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This course teaches experienced authors advanced report building techniques to enhance, customize, manage, and distribute reports. Additionally, the student will learn how to create highly interactive and engaging reports that can be run offline by creating Active Reports.
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.
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This O3201G: Fundamentals of IBM Watson Explorer Deep Analytics Edition oneWEX v12.0.x course is designed to teach students core concepts of IBM Watson Explorer Deep Analytics Edition oneWEX. Students will learn to identify the oneWEX platforms as well as the process flow and data flow of oneWEX projects.
Students will explore oneWEX tools, such as Content Miner and the Admin Console, while gaining hands-on experience in data acquisition and enrichment. Finally, students will be exposed to more advanced topics, such as Application Builder, Content Analytics Studio, and API usage.
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Learn to explore, summarize and interpret data like a pro.
This 0G51BG: Statistical Analysis Using IBM SPSS Statistics v26 course provides an application-oriented introduction to the statistical component of IBM SPSS Statistics. Students will review several statistical techniques and discuss situations in which they would use each technique, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for exploring and summarizing data, as well as investigating and testing relationships.
Students will gain an understanding of when and why to use these various techniques and how to apply them with confidence, interpret their output, and graphically display the results.
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This 0A069G: IBM SPSS Modeler Foundations v18.2 course provides the foundations of using IBM SPSS Modeler and introduces the participant to data science. The principles and practice of data science are illustrated using the CRISP-DM methodology. The course provides training in the basics of how to import, explore, and prepare data with IBM SPSS Modeler v18.2, and introduces the student to modeling.
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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 0A008G: Introduction to IBM SPSS Modeler and Data Science v18.x course provides the fundamentals of using IBM SPSS Modeler and introduces the participant to data science. The principles and practice of data science are illustrated using the CRISP-DM methodology. The course provides training in the basics of how to import, explore, and prepare data with IBM SPSS Modeler v18.1.1, and introduces the student to modeling.
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This O3268G: Fundamentals of IBM Watson Explorer Deep Analytics Edition oneWEX v12.0.x course is designed to teach students core concepts of IBM Watson Explorer Deep Analytics Edition oneWEX. Students will learn to identify the oneWEX platforms as well as the process flow and data flow of oneWEX projects.
Students will explore oneWEX tools, such as Content Miner and the Admin Console, while gaining hands-on experience in data acquisition and enrichment. Finally, students will be exposed to more advanced topics, such as Application Builder, Content Analytics Studio, and API usage.
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This B6259G: IBM Cognos Analytics: Author Reports Advanced v11.x course teaches experienced authors advanced report building techniques to enhance, customize, manage, and distribute reports. Additionally, the student will learn how to create highly interactive and engaging reports that can be run offline by creating Active Reports.
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This 2Z840G: InfoSphere MDM Workbench v11 course is designed for anyone who wants to get an understanding of how to use and customize the InfoSphere Master Data Management using the InfoSphere MDM Workbench. This course takes a participant through the process customizing both the Virtual and Physical MDM using the InfoSphere MDM Workbench. The focus of the course is on the core features of the Workbench: Creating a Physical MDM Addition, creating a Physical MDM Extension, creating a Physical MDM Behavior Extension, creating a composite service, deploying a Virtual MDM configuration, configuring the Virtual Data Model, creating a Virtual custom Composite View, creating a Virtual Callout Handler, generating an enterprise service interface using the Virtual data model and customizing a Hybrid implementation.
For each core area, the instructor will explain the high-level concepts, have the participants work with the feature and then demo and review the feature details. Heavy emphasis is put on exercises and activities, allowing course participants to apply the knowledge that they learn in the classroom, after course conclusion.
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.
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This 0A0U8G: Predictive Modeling for Categorical Targets Using IBM SPSS Modeler v18.1.1 course focuses on using analytical models to predict a categorical field, such as churn, fraud, response to a mailing, pass/fail exams, and machine break-down. Students are introduced to decision trees such as CHAID and CR Tree, traditional statistical models such as Logistic Regression, and machine learning models such as Neural Networks.
Students will learn about important options in dialog boxes, how to interpret the results, and explain the major differences between the models.
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This KM700G: IBM BigIntegrate for Data Engineers v11.5.0.2 course teaches data engineers how to run DataStage jobs in a Hadoop environment. You will run jobs in traditional and YARN mode, access HDFS files and Hive tables using different file formats and connector stages.
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This course is designed to introduce advanced parallel job development techniques in DataStage v11.5. In this course you will develop a deeper understanding of the DataStage architecture, including a deeper understanding of the DataStage development and runtime environments. This will enable you to design parallel jobs that are robust, less subject to errors, reusable, and optimized for better performance.
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.
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This course will step you through the QualityStage data cleansing process. You will transform an unstructured data source into a format suitable for loading into an existing data target. You will cleanse the source data by building a customer rule set that you create and use that rule set to standardize the data. You will next build a reference match to relate the cleansed source data to the existing target data.
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.
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This ZZ820G: InfoSphere MDM Architecture v11 course is designed for anyone who wants to get an understanding of the InfoSphere MDM Architecture (including the Virtual and Physical Hubs). This course walks you through the major components of the InfoSphere MDM and how each component interacts. You will learn how InfoSphere MDM responds once a service is invoked and the various configuration and extension points of a service. The course is used as an introduction to various components that make up the MDM Architecture and prepares you to identify how MDM will fit into their organization and what pieces may be customized to fit their business requirements.
The next courses that may be of interest to you include:
- Data Model and Service Mapping for the InfoSphere MDM Advanced Edition V10 (ZZ610)
- Customizing the InfoSphere MDM Advanced Edition V10 (ZZ640)
- IBM InfoSphere MDM Server Service Customization for MDM Server 9 (ZZ340)
- InfoSphere MDM Server User Interface Generator (DC560)
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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 and Physical implementation? Then this course is designed for you.
The IBM InfoSphere MDM Algorithms V11 course prepares you to work with and customize the algorithm configurations deployed to the InfoSphere MDM Probabilistic Matching Engine (PME) for a Virtual and Physical 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 you 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 you will feel comfortable customizing an algorithm for the PME for a Virtual and Physical MDM implementations.
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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.
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This offering provides Business and Professional Authors with an introduction to report building techniques using relational data models. Techniques to enhance, customize, and manage professional reports will be explored. Activities will illustrate and reinforce key concepts during this learning opportunity.
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
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This course provides authors with an introduction to build reports using Cognos Analytics. Techniques to enhance, customize, and manage reports will be explored. Activities will illustrate and reinforce key concepts during this learning opportunity.
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.
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This course provides authors with an introduction to build reports using Cognos Analytics. Techniques to enhance, customize, and manage reports will be explored. Activities will illustrate and reinforce key concepts during this learning opportunity.
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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.
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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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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 database administrators to perform basic database administrative tasks using Db2 11.1. These tasks include creating database objects like tables, indexes and views, and loading data into the database with Db2 utilities like LOAD and INGEST. Various diagnostic methods will be presented, including using db2pd command options, and monitoring with SQL statements that reference Db2 monitor functions. Students will learn how to implement automatic archival for database logs and how to recover a database to a specific point in time using the archived logs.
The course covers using EXPLAIN tools to review the access plans for SQL statements and adding indexes to improve SQL performance. We will cover the locking performed by Db2 and the effect the application isolation level has on locking and lock wait conditions. Students will learn how to implement database security, including adding a security administrator, SECADM user, and implement database roles to simplify security management. We will also describe implementing Db2 native encryption for a database.
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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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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.
