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IBM: Data Warehousing and BI Analytics

4.5 stars
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This course introduces you to designing, implementing and populating a data warehouse and analyzing its data using SQL & Business Intelligence (BI) tools.

Data Warehousing and BI Analytics
6 weeks
2–3 hours per week
Progress at your own speed
Optional upgrade available

There is one session available:

After a course session ends, it will be archivedOpens in a new tab.
Starts Nov 28

About this course

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Today’s businesses are investing significantly in capabilities to harness the massive amounts of data that fuel Business Intelligence (BI). Working knowledge of Data Warehouses and BI Analytics tools are a crucial skill for Data Engineers, Data Warehousing Specialists and BI Analysts, making who are amongst, the most valued resources for organizations.

This course prepares you with the skills and hands-on experience to design, implement and maintain enterprise data warehouse systems and business intelligence tools. You’ll gain extensive knowledge on various data repositories including data marts, data lakes and data reservoirs, explore data warehousing system architectures, deepen on data cubes and data organization using related tables. And analyze data using business intelligence like Cognos Analytics, including its reporting and dashboard features, and interactive visualization capabilities.

This course provides hands-on experience with practice labs and a real-world inspired project that can be added to your portfolio and will demonstrate your proficiency in working with data warehouses. Skills you will gain include building data warehouses, Star/Snowflake schemas, CUBEs, ROLLUPs, Materialized Views/MQTs, reports and dashboards.

This course assumes prior SQL and relational database experience.

At a glance

  • Associated skills: Relational Databases, Data Lakes, Business Intelligence Tools, Snowflake Schema, Dashboard, Materialized View, SQL (Programming Language), Data Warehouse Systems, Business Intelligence, Star Schema, Data Warehousing

What you'll learn

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  • Describe the architecture, features, and benefits of data warehouses, data marts, and data lakes and identify popular data warehouse system vendors.
  • Design and populate a data warehouse, and model and query data using SQL to build CUBEs, ROLLUPs, and Materialized Views.
  • Analyze warehouse data using popular Business Intelligence (BI) tools such as Cognos Analytics to create reports and dashboards.
  • Demonstrate loading data into a data warehouse, writing aggregation queries, creating materialized query tables, and building an analytics dashboard.

Module 1: Data Warehouses, Data Marts, and Data Lakes

  • Data Warehouse Overview

  • Popular Data Warehouse Systems

  • Selecting a Data Warehouse System

  • IBM Db2 Warehouse (Optional)

  • Data Marts Overview

  • Data Lakes Overview

Module 2: Designing, Modeling and Implementing Data Warehouses

  • Overview of Data Warehouse Architectures

  • CUBEs, ROLLUPs, Materialized Views and Tables

  • Facts and Dimensional Modeling

  • Data Modeling using Star and Snowflake Schemas

  • Staging Areas for Data Warehouses

  • Verify Data Quality

  • Populating a Data Warehouse

  • Querying the Data

Module 3: Data Warehouse Analytics

  • Introduction to Analytics and Business Intelligence (BI) Tools

  • Cognos Analytics: Introduction and How to Sign Up

  • Navigating in Cognos Analytics

  • Creating a Simple Dashboard in Cognos

  • Advanced Capabilities in Cognos Analytics Dashboards

  • Accessing Your Warehouse with Cognos

Module 4: Final Assignment

Who can take this course?

Unfortunately, learners residing in one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. edX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.

This course is part of Data Engineering Professional Certificate Program

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Expert instruction
14 skill-building courses
Progress at your own speed
1 year 2 months
3 - 4 hours per week

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