Course Syllabus

1.  Module 1: Introduction to IBM Cognos Analytics 11.2 – Overview of the Cognos Analytics platform, components (Portal, reporting, dashboards, AI), and architecture. Participants learn how Cognos 11.2 differs from earlier versions (new IBM Carbon UI, faster engine). The module covers system architecture, content storage, and user roles at a high level. A hands-on lab lets learners log into a Cognos 11.2 environment, explore the web portal, and run sample reports/dashboards.
2.  Module 2: Data Warehousing and Modeling Basics – Fundamentals of BI data modeling. Topics include data warehouse concepts, fact/dimension tables, star & snowflake schemas, and ETL basics. Learners also review how Cognos Framework Manager and Data Modules use these schemas. Real-world scenarios (e.g. sales or HR datasets) are introduced. In labs, students design a simple star schema and discuss best practices for data modeling.
3.  Module 3: Framework Manager (Metadata Modeling) – Introduction to IBM Cognos Framework Manager, the traditional metadata modeling tool. Learners create a metadata model by importing data sources (relational/OLAP) into FM, defining relationships, hierarchies, and business views. The concept of publishing packages to report authors is covered. Hands-on exercises guide participants through building a small FM model and generating a package for reporting. This module also touches on using dynamic query mode for performance.
4.  Module 4: Data Modules (Web-based Modeling) – Working with Cognos Data Modules, the web-based self-service modeling feature. Students learn how data modules combine multiple sources (databases, uploaded files, other modules) into a semantic layer. Topics include creating relationships, calculated columns, and reference hierarchies. Labs involve creating a data module from sample tables (e.g. combining an Excel file with a database table) and saving it in Team Content. The module highlights when to use data modules versus Framework Manager for metadata.
5.  Module 5: Report Authoring (Cognos Reporting) – Hands-on report building using the Cognos Analytics reporting tool (Report Studio). Learners cover list, crosstab, and chart reports. Tasks include inserting queries, formatting, adding totals, and basic prompts. Cognos Analytics reporting is a web-based report authoring tool for professional report authors. In labs, participants create a multi-query report against the previously built data module or package, then apply sorting, grouping and basic filters. The module also covers refreshing data and exporting reports.
6.  Module 6: Advanced Reporting Techniques – Enhancing Cognos reports with advanced features. Topics include using filters and prompts, master/detail (drill-through) reports, query calculations, and set operators. Learners practice conditional formatting, multiple blocks, and bursting (report distribution). Active Reports (offline interactive reports) are introduced. A lab exercise guides students in adding prompts to a report, configuring burst output, and creating an Active Report for mobile viewing.
7.  Module 7: Dashboarding and Data Visualization – Creating interactive dashboards and stories in Cognos. Learners use the Dashboards and Dashboards – Explorations tool to design layouts and visualizations. Tasks include building drill-down dashboards, adding widgets (maps, charts, filters), and connecting dashboard items to data. The course covers customizing dashboards (tabs, filters) and setting a default home dashboard. In exercises, students create an executive dashboard from example data, add navigation, and apply filters. Cognos dashboards can incorporate AI-assisted visuals, and learners explore features like auto-chart recommendations. (For example, dashboard courses teach creating dashboards with tabs/filters and using AI to “explore relationships in data”.)
8.  Module 8: Data Exploration, AI Assistance and Storytelling – Using Cognos Analytics for advanced data exploration. Topics include the AI-powered Exploration feature, Watson natural language query assistant, and storytelling (data stories). Participants learn to use exploration mode to automatically find data insights and patterns, and to use the AI Assistant to ask questions in natural language. Students build a simple data exploration and a data story (slideshow) summarizing key findings. This module emphasizes Cognos 11.2’s augmented analytics – for example, using Watson to analyze OLAP cubes and generate narrative insights.
9.  Module 9: Cognos Administration and Security – Basics of administering a Cognos Analytics environment. Topics include security administration (authentication, namespaces, security filters), user roles, and content access. Learners see how to configure dispatchers, content store, and scheduling. Performance tuning and monitoring concepts (e.g. query logging, cache settings) are introduced. In hands-on labs, participants create user groups, assign roles, and test report access. This module ensures learners understand how to deploy and secure Cognos for enterprise use.
10.  Module 10: Certification Exam Preparation and Capstone Review – Review of major Cognos Analytics topics aligned with the IBM Certified Developer exam. Key concepts from reporting, dashboards, and data modeling are reinforced. The instructor covers sample certification questions and test-taking strategies. A final hands-on project (capstone) integrates elements from previous modules – for example, building a data module, authoring a report and a dashboard on a BI scenario – to solidify learning. Participants leave prepared for the official IBM exam and equipped with practical skills for real-world BI solutions.

Key Features

  Instructor-led Live Sessions: Expert-led classes (online or onsite) with certified Cognos trainers guide the learning. Topics include data warehousing, ETL, Framework Manager, data modules, reporting, and analysis. The format supports interactive Q&A and hands-on coaching.

  Hands-On Labs: A remote lab environment is provided so participants can practice tasks (connecting to data sources, building models, designing reports/dashboards) on live Cognos 11.2. For example, some providers offer extended lab access even after course completion

  Real-World Case Studies: Each module uses practical BI scenarios (e.g. sales analysis, financial dashboards) so learners apply concepts in context. Course materials include exercises and example datasets tailored to business needs

  Comprehensive Curriculum: The course covers both fundamental and advanced features of Cognos 11.2. Topics span Cognos architecture, Framework Manager models, data modules, report authoring, interactive dashboards, AI-assisted analytics, and administration

  Certification Exam Preparation: The program aligns with the IBM Cognos Analytics Developer certification objectives. Key exam areas (dashboards, reporting, data modeling, security/performance) are reviewed, and sample questions are provided. For example, the Developer exam allocates roughly 22% to dashboards, 32% to reporting, and 21% to data/modeling (see table below).