Course Overview

This 3-day International Requirements Engineering Board (IREB) course prepares you for the Certified Professional for Requirements Engineering (CPRE) Foundation examination.

In order to successfully implement a change or project, it is essential to have a complete and accurate set of requirements. Various studies (including the Chaos Report by the Standish Group) have shown that success depends on the proper handling of requirements and stakeholder involvement.

To increase the chances of success, this is an important task for the Requirements Engineer (including Information/Business Analysts, Requirements Managers) and other stakeholders who have an interest in requirements (including Functional Application Management, testers). Global Knowledge offers a number of training courses and follows the international certification programme of the IREB: the Certified Professional for Requirements Engineering.

Course Objectives

The participant learns to delineate and formulate the scope in order to get and keep grip on the intended changes. To this end, he/she learns the necessity of involving the right stakeholders in the collection (elicitation), recording and evaluation of the requirements. Conflicts between requirements and stakeholder interests can be identified and resolved. The requirements engineer is after all the pivot between the business and the ICT for the realization of their objectives.

After the training the participant is familiar with the following:

  • the concepts and terms used in the field what the importance of requirements and the role of the stakeholder are
  • what techniques there are to collect (elicit), analyze, record and validate requirements
  • How requirements engineering can recognize and resolve problems and conflicts.
  • How requirements are managed during their life cycle

Course Content

The following topics are covered and skills are taught. The material is taught by specialists in the field and is frequently practised with practical assignments. In addition, the manner and type of questions that the participant may expect at the exam are trained.

  • Introduction and foundations: Importance of requirements, concepts and terms, characteristics of the Requirements Engineer, the 4 core activities of Requirements Engineering, etc.
  • System and system context: Scoping of system/project, context diagram, Quality Requirements (non-functionals), etc.
  • Requirements elicitation: Stakeholder selection, methods and techniques to elicit requirements from stakeholders, etc.
  • Requirements documentation: Modes of Requirements documentation, quality criteria of the Requirements documentation, etc.
  • Documentation of Requirements using Natural Language: Specification of Requirements in natural language (text), quality criteria of the individual Requirement,
  • Model based requirements documentation: Specification of requirements by means of models, UML modelling, ERD modelling, state diagrams, etc.
  • Requirements validation and negotiation: Check Requirements to see if the right solution is described, negotiate conflicting requirements, etc.
  • Requirements management: Managing Requirements during their life cycle, Change Control Board, etc.
  • Tool support: Properties of a RE tool, selection and implementation, etc. 

Course Overview

This 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.

Virtual Learning

This interactive training can be taken from any location, your office or home and is delivered by a trainer. This training does not have any delegates in the class with the instructor, since all delegates are virtually connected. Virtual delegates do not travel to this course, Global Knowledge will send you all the information needed before the start of the course and you can test the logins.

Course Objectives

Please refer to course overview

Course Content

Introduction to machine learning models • Taxonomy of machine learning models • Identify measurement levels • Taxonomy of supervised models • Build and apply models in IBM SPSS Modeler Supervised models: Decision trees – CHAID • CHAID basics for categorical targets • Include categorical and continuous predictors • CHAID basics for continuous targets • Treatment of missing values Supervised models: Decision trees – C&R Tree • C&R Tree basics for categorical targets • Include categorical and continuous predictors • C&R Tree basics for continuous targets • Treatment of missing values Evaluation measures for supervised models • Evaluation measures for categorical targets • Evaluation measures for continuous targets Supervised models: Statistical models for continuous targets – Linear regression • Linear regression basics • Include categorical predictors • Treatment of missing values Supervised models: Statistical models for categorical targets – Logistic regression • Logistic regression basics • Include categorical predictors • Treatment of missing values Supervised models: Black box models – Neural networks • Neural network basics • Include categorical and continuous predictors • Treatment of missing values Supervised models: Black box models – Ensemble models • Ensemble models basics • Improve accuracy and generalizability by boosting and bagging • Ensemble the best models Unsupervised models: K-Means and Kohonen • K-Means basics • Include categorical inputs in K-Means • Treatment of missing values in K-Means • Kohonen networks basics • Treatment of missing values in Kohonen Unsupervised models: TwoStep and Anomaly detection • TwoStep basics • TwoStep assumptions • Find the best segmentation model automatically • Anomaly detection basics • Treatment of missing values Association models: Apriori • Apriori basics • Evaluation measures • Treatment of missing values Association models: Sequence detection • Sequence detection basics • Treatment of missing values Preparing data for modeling • Examine the quality of the data • Select important predictors • Balance the data

Course Overview

This 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.

Virtual Learning

This interactive training can be taken from any location, your office or home and is delivered by a trainer. This training does not have any delegates in the class with the instructor, since all delegates are virtually connected. Virtual delegates do not travel to this course, Global Knowledge will send you all the information needed before the start of the course and you can test the logins.

Course Objectives

Please refer to course overview.

Course Content

Introduction to IBM SPSS Modeler • Introduction to data science • Describe the CRISP-DM methodology • Introduction to IBM SPSS Modeler • Build models and apply them to new data Collect initial data • Describe field storage • Describe field measurement level • Import from various data formats • Export to various data formats Understand the data • Audit the data • Check for invalid values • Take action for invalid values • Define blanks Set the unit of analysis • Remove duplicates • Aggregate data • Transform nominal fields into flags • Restructure data Integrate data • Append datasets • Merge datasets • Sample records Transform fields • Use the Control Language for Expression Manipulation • Derive fields • Reclassify fields • Bin fields Further field transformations • Use functions • Replace field values • Transform distributions Examine relationships • Examine the relationship between two categorical fields • Examine the relationship between a categorical  and continuous field • Examine the relationship between two continuous fields Introduction to modeling • Describe modeling objectives • Create supervised models • Create segmentation models Improve efficiency • Use database scalability by SQL pushback • Process outliers and missing values with the Data Audit node • Use the Set Globals node • Use parameters • Use looping and conditional execution

Course Overview

This course explores the IBM Planning Analytics Workspace, how to create dimensions, cubes, and business rules. Learners will also delve into loading and maintaining data, optimizing their business rules, and learn how to transfer data into a model.

This course also explains how to customize drill paths, using rules for advanced modeling, and converting currencies.

Finally, learners will learn how to create models for different fiscal requirements.

Virtual Learning

This interactive training can be taken from any location, your office or home and is delivered by a trainer. This training does not have any delegates in the class with the instructor, since all delegates are virtually connected. Virtual delegates do not travel to this course, Global Knowledge will send you all the information needed before the start of the course and you can test the logins.

Course Objectives

By the end of this course, learners should be able to:

  • Identify the TM1 position in a performance management system
  • Describe TM1 components and architecture
  • Manually create dimensions, import, and edit them
  • Construct and edit a cube
  • Identify data sources
  • Create processes to update and maintain a model
  • Review, disable, and enable auto-generated rules
  • Optimize rules using a SKIPCHECK statement
  • Troubleshoot rules and feeders
  • Link cubes with different dimensions
  • Use Planning Analytics as a data source
  • Push data to a cube
  • Create a drill process and drill assignment rules
  • Utilize a lookup cube and attributes in rules
  • Create rules for currency conversion
  • Use Planning Analytics to reduce maintenance
  • Use discreet time dimensions
  • Implement a continuous time dimension model

Course Content

Overview of IBM Planning Analytics • Modeling in IBM Planning Analytics: overview • IBM Planning Analytics: data tier • In-memory data storage • Calculating versus caching data • Important files in TM1

Create dimensions • What is a dimension? • What are weights? • Time dimensions • Member attributes • Hierarchies

Load and maintain data • What is TurboIntegrator? • Defining data sources and process parameters in TurboIntegrator • Validate and run processes • TurboIntegrator chores

Add business rules • What are rules? • How do you create a rule? • Review rule processing • Use a rule to override aggregation • Use a function in a rule

Optimize rule performance • Understanding consolidations and sparsity • Optimize your rules using SKIPCHECK • Using feeder statements • Inter-cube feeders • Feeding string rules • Trace cell values and feeders

Transfer data into your model • Link cubes with different dimensions • Review TurboIntegrator • Dealing with data • Use IBM Planning Analytics as a data source • Tips for scripting in TurboIntegrator

Customize drill paths • View related data • Create a drill path

Use rules for advanced modeling • Describe a virtual cube • Utilize a lookup cube • Use relative spreading and a spread profiles cube • Use attributes in rules

Convert currencies • Converting currency: overview • Review control cubes

Model for different fiscal requirements • Understanding time • Discrete time dimensions • Continuous time dimensions • Develop a continuous time model

Course Overview

This 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.

Virtual Learning

This interactive training can be taken from any location, your office or home and is delivered by a trainer. This training does not have any delegates in the class with the instructor, since all delegates are virtually connected. Virtual delegates do not travel to this course, Global Knowledge will send you all the information needed before the start of the course and you can test the logins.

Course Objectives

At the end of the course, participants will be able to :

  • Use Planning Analytics Workspace
  • Use Planning Analytics for Microsoft Excel
  • Create analyses,
  • Enter data,
  • Create custom views and dashboards,
  • Build formatted reports and forms.

Course Content

  • Understanding IBM Planning Analytics data
  • Creating books
  • Creating and saving views
  • Changing the way data is displayed
  • Displaying specific members by using sets
  • Adding calculations to views
  • Highlighting exceptions by using conditional formatting
  • Entering data
  • Experimenting with data by using sandboxes
  • Working with spreadsheets online by using websheets
  • Formatting for reporting
  • Exploring data by using visualizations
  • Creating dashboards
  • Examining performance by using scorecards
  • Exporting data
  • Introduction to IBM Planning Analytics for Microsoft Excel
  • Creating websheets
  • AI Forecasting
  • Apps and Plans
  • Decision Optimization Overview

Course Overview

This course provides a high-level overview of the IBM Cognos Analytics Data Module tool and its underlying architecture to provide learners with the skills necessary to master data modeling using the web-based, self-service capabilities of IBM Cognos Analytics Data Modules. Learners will explore the essential steps in building data modules, from understanding the purpose and workflow of data modeling to creating, refining, and optimizing data structures. The course covers various topics, including relationship joins, data enrichment with calculations and filters, creating navigation paths, and managing data security.

Learners will gain hands-on experience through exercises that enhance their ability to create and customize data modules, ensuring consistency and usability for reporting, dashboarding, and exploration purposes.

By the end of this course, learners should be proficient in developing data modules that integrate multiple data sources, support business analysis, and facilitate informed decision[1]making within the IBM Cognos environment.

Virtual Learning

This interactive training can be taken from any location, your office or home and is delivered by a trainer. This training does not have any delegates in the class with the instructor, since all delegates are virtually connected. Virtual delegates do not travel to this course, Global Knowledge will send you all the information needed before the start of the course and you can test the logins.

Course Objectives

After completing this course, learners should be able to:

  • List several options for data modeling in Cognos Analytics
  • Explain the data modeling workflow
  • Explain how to use AI to discover related tables
  • Describe relationships and relationship joins
  • Create and manage custom tables
  • Describe how to create calculations and filters
  • Describe how to create Navigation Paths
  • Explain how to relink a Data Module
  • Create and use column dependencies

Course Content

Course Introduction

Unit 1. Data Modeling in Cognos Analytics

Unit 2. Create a Data Module

Unit 3. Modify and Refine a Data Module

Unit 4. Create Relationship Joins

Unit 5. Customize Data Modules using Filters and Calculations

Unit 6. Group Data and Create Navigation Paths

Unit 7. Share a Data Module

Unit 8. Advanced Functionality in Data Modules

Course Overview

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.

Virtual Learning

This interactive training can be taken from any location, your office or home and is delivered by a trainer. This training does not have any delegates in the class with the instructor, since all delegates are virtually connected. Virtual delegates do not travel to this course, Global Knowledge will send you all the information needed before the start of the course and you can test the logins.

Course Objectives

At the end of the course, participants will be able to :

  • Install and configure IBM Cognos Analytics
  • Implement security
  • Monitor and schedule tasks
  • Create data sources
  • Manage and deploy content in the IBM Cognos portal and administration.

Course Content

Introduction to IBM Cognos Analytics administration 

  • IBM Cognos Analytics components 
  • Administration workflow 
  • IBM Cognos Administration 
  • IBM Cognos Configuration  

Identify IBM Cognos Analytics architecture 

  • Features of the IBM Cognos Analytics architecture 
  • Examine the multi-tiered architecture, and identify logging types and files 
  • Examine IBM Cognos Analytics servlets 
  • Performance and installation planning 
  • Balance the request load 
  • Configure IBM Cognos Analytics  

Secure the IBM Cognos Analytics environment 

  • Identify the IBM Cognos Analytics security model 
  • Define authentication in IBM Cognos Analytics 
  • Define authorization in IBM Cognos Analytics 
  • Identify security policies 
  • Secure the IBM Cognos Analytics environment

Administer the IBM Cognos Analytics server environment 

  • Administer IBM Cognos Analytics servers 
  • Monitor system performance 
  • Manage dispatchers and services 
  • Tune system performance, and troubleshoot the server 
  • Audit logging 
  • Dynamic cube data source administration workflow  

Manage run activities 

  • View current, past, and upcoming activities 
  • Manage schedules  

Manage content in IBM Cognos Administration 

  • Data sources and packages 
  • Manage visualizations in the library 
  • Deployment 
  • Other content management tasks  

Examine departmental administration capabilities 

  • Create and manage team members 
  • Manage activities 
  • Create and manage content and data 
  • Manage system settings 
  • Manage Themes, Extensions, and Views 
  • Share services with multiple tenants

Course Overview

Students will explore IBM Cognos Analytics report authoring and different report object types (list, crosstab, chart, visualization, etc.). They will also create and format reports using grouping, headers, footers, and other formatting options. Also covered is the ability to focus reports by filtering data and using prompts. Students will learn to add value to reports using calculations and additional report-building techniques as well as how to enhance reports with advanced formatting and exceptional data highlighting.

Virtual Learning

This interactive training can be taken from any location, your office or home and is delivered by a trainer. This training does not have any delegates in the class with the instructor, since all delegates are virtually connected. Virtual delegates do not travel to this course, Global Knowledge will send you all the information needed before the start of the course and you can test the logins.

Course Objectives

  • Introduction to IBM Cognos Analytics – Reporting
  • Examine data tables and list reports
  • Create crosstab reports
  • Create visualization reports
  • Focus reports using filters
  • Focus reports using prompts
  • Extend reports using calculations
  • Customize reports with conditional formatting
  • Drill-through definitions
  • Enhance report layout
  • Use additional report building techniques

Course Content

Introduction to IBM Cognos Analytics Reporting

  • Examine IBM Cognos Analytics
  • Reporting and its interface
  • Explore different report types
  • Create reports in preview or design mode
  • Create a simple, sorted, and formatted report
  • Examine dimensionally modeled and dimensional data sources
  • Explore how data items are added queries
  • Examine personal data sources and data modules


Examine data tables and list reports

  • Create a data table
  • Group, format, and sort list reports
  • Describe options for aggregating data
  • Create a multi-fact query
  • Create a report with repeated data
  • Create crosstab reports
  • Format and sort crosstab reports
  • Create complex crosstabs using drag and drop functionality
  • Create crosstabs using unrelated data items

Create visualization reports

  • Understand visualization categories
  • Create and customize visualizations
  • Understand client-side visualizations
  • Create enhanced map visualizations

Focus reports using filters

  • Create filters to narrow the focus of reports
  • Examine detail and summary filters
  • Determine when to apply filters on aggregate data

Focus reports using prompts -Identify various prompt types

  • Use parameters and prompts to focus data
  • Search for prompt types
  • Navigate between pages

Extend reports using calculations

  • Create calculations based on data in the data source
  • Add run-time information to the reports
  • Create expressions using functions

Customize reports with conditional formatting

  • Create multilingual reports
  • Highlight exceptional data
  • Show and hide data
  • Conditionally render objects in reports

Drill-through definitions

  • Introduction to drill-through definitions
  • Navigating to related data
  • Introduction to bookmark references

Enhance report layout

  • Force page breaks in reports
  • Format data and report objects
  • Modify existing report structures

Use additional report building techniques

  • Enhance report design with report objects
  • Add objects to reports
  • Convert a list to a crosstab
  • Reuse objects within the same report
  • Share layout components among separate reports
  • Choose options to handle reports with no available data

Course Overview

This course teaches Professional Report Authors about advanced report building techniques using relational data models, and ways of enhancing, customizing, and managing professional reports. The course builds on topics presented in the Fundamentals course. Attendees will participate in interactive demonstrations and exercises that illustrate key concepts while learning how to use advanced features in the product builds on topics learned in the Fundamentals course.

Virtual Learning

This interactive training can be taken from any location, your office or home and is delivered by a trainer. This training does not have any delegates in the class with the instructor, since all delegates are virtually connected. Virtual delegates do not travel to this course, Global Knowledge will send you all the information needed before the start of the course and you can test the logins.

Course Objectives

  • Create advanced queries
  • Create reports based on query relationships 
  • Examine dimensional concepts 
  • Create advanced dynamic reports
  • Design effective Prompts
  • Create additional advanced reports
  • Examine the report specification 
  • Distribute reports through bursting 
  • Enhance user interaction with HTML 
  • Examine custom controls

Course Content

Unit 1: Create query models

  • build query models and then connect them to the report layout
  • edit an SQL statement to author custom queries
  • add filters and prompts to a report using the query models 

Unit 2: Create reports based on query relationships

  • create reports by joining queries
  • combine data containers based on relationships from different queries

Unit 3: Introduction to dimensional reporting concepts and dimensional data in reports 

  • List and describe the data model types 
  • Describe the OLAP data structure and elements 
  • Differentiate between report authoring styles 
  • use members to build reports 
  • identify and use sets and tuples in reports 

Unit 4: Dimensional report context

  • understand report context
  • root members 
  • default members 
  • current members
  • default measures 
  • current measures 

Unit 5: Focus your dimensional data 

  • understand how relational data sources behave 
  • understand how dimensional data sources behave 
  • create efficient queries 
  • understand filtering techniques 
  • use dimensional objects and functions 
  • create slicers and prompts 

Unit 6: Calculations and dimensional functions 

  • understand the different types of dimensional functions within Cognos Analytics 
  • create reports utilizing dimensional functions 
  • use calculations within reports 

Unit 7: Create advanced dynamic reports

  • filter reports on session parameter values 
  • create dynamic headers and titles that reflect report data
  • create a customer invoice report 

Unit 8: Design effective prompts

  • control report displays using prompts 
  • specify conditional formatting values using prompts 
  • create sorted and filtered reports based on prompt selection

Unit 9: Examine the report specification and distribute reports 

  • work with the report specification 
  • report specification flow 
  • considerations when modifying a report specification 
  • Create custom toolbox and template objects 
  • distribute reports using bursting
  • create burst keys
  • identify report recipients and data items using burst tables
  • distribute reports using email and the IBM Cognos Analytics portal 

Unit 10: Enhance user experience with HTML and Custom Controls 

  • create interactive reports by using HTML 
  • Include additional information with tooltips 
  • Send emails by using links in a report
  • understand custom controls 
  • AMD models
  • adding a custom control
  • using JavaScript files 

Unit 11: Advanced techniques

  • understand advanced features 
  • booklet and reference reports 
  • table of contents 
  • tabbed reports
  • classes and class extensions 
  • global parameters
  • create a report binder

Course Overview

This course provides a high-level overview of the IBM Cognos Analytics v12 Data Module tool and its underlying architecture to provide learners with the skills necessary to master data modeling using the web-based, self-service capabilities of IBM Cognos Analytics v12 Data Modules.

Learners will explore the essential steps in building data modules, from understanding the purpose and workflow of data modeling to creating, refining, and optimizing data structures. The course covers various topics, including managing relationships, advanced features and performance optimization, data enrichment with calculations and filters, creating groups and navigation paths, and managing data security.

Learners will gain hands-on experience through exercises that enhance their ability to create and customize data modules, review and modify column properties, creating calculations, filters and data groups, and adding column dependencies. These hands on activities ensure learners practice consistency and usability for reporting, dashboarding, and exploration purposes.

By the end of this course, learners should be proficient in developing data modules that integrate multiple data sources, support business analysis, and facilitate informed decision-making within the IBM Cognos v12 environment.

Course Objectives

After completing this course, learners should be able to:

  • Describe the data modeling workflow, including identifying sources, enriching the module, and testing it.
  • Navigate the Cognos Analytics v12 Data Modules user interface and upload a source file.
  • Demonstrate how to create, edit, and optimize relationships in Cognos Analytics v12, including utilizing the Null Safe option and configuring cardinality for accurate data integration.
  • Organize data modules by hiding, renaming, or removing fields.
  • Use SQL to create a new table by writing and validating a custom query.
  • Configure custom sorting for a specified column and validate its application in reports or dashboards.
  • Utilize the Enhanced Expression Editor to create a custom calculation combining fields from two tables.
  • Design a navigation path and validate functionality in dashboards.
  • Configure row-level security filters, assign permissions, and utilize security definitions.
  • Configure advanced data module functionalities, including column dependencies, bridge tables, and summary tables.
  • And more

Course Content

  • Course Introduction
  • Unit 1: Data Modeling in Cognos Analytics v12
  • Unit 2: Creating Data Modules
  • Unit 3: Managing Relationships
  • Unit 4: Reviewing and Organizing Data Modules
  • Unit 5: Advanced Features and Performance Optimization
  • Unit 6: Customizing Data Modules with Filters and Calculations
  • Unit 7: Grouping Data and Creating Navigation Paths
  • Unit 8: Organizing and Sharing Data Modules
  • Unit 9: Advanced Functionality in Data Modules