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The Data Warehousing and BI Certification Training is designed to provide learners with a comprehensive understanding of data warehouse concepts, business intelligence tools, and implementation strategies. This course is ideal for data engineers, business intelligence professionals, and IT professionals looking to master data modeling, ETL processes, data integration techniques, and BI reporting. Achieving this certification enhances career opportunities in data analytics and business intelligence.
Instructor led live online Training (Weekday/Weekend)
Master Data Warehousing and BI: Learn data warehouse design, ETL workflows, BI integration, and data visualization.
Career Growth: Gain a globally recognized certification in data warehousing and business intelligence.
Hands-on Labs: Work on real-world projects using data warehousing and BI tools.
In-Demand Skills: Learn data modeling, extraction, transformation, and loading (ETL), along with BI reporting and dashboards.
Globally Recognized Certification: Showcase your expertise in data warehousing and business intelligence to employers worldwide.
The Data Warehousing and BI Certification Training validates your ability to design, implement, and optimize data warehouse solutions and create business intelligence reports using modern data technologies.
1. Data Engineers working on data warehouse design and ETL development. 2. Business Intelligence Professionals integrating data for analytics and reporting. 3. ETL Developers looking to streamline data processing workflows. 4. Beginners looking to start a career in data warehousing and business intelligence.
1. Comprehensive curriculum covering data warehouse fundamentals and BI tools. 2. Hands-on practice with real-world data scenarios. 3. 24/7 expert support for technical guidance.
What is Data Warehousing?, Definitions by W.H. Inmon [Top-Down Design], Ralph Kimball [Bottom-Up Design], Inmon Vs Ralph Kimball, Data Warehousing Tools, Schema Modeling Tools, CA, ERwin, Dell Toad Data Modeler, Oracle Data Modeler, ETL Tools: Informatica Power Center, Talend DI Open Studio, IBM Data Stage, SAS, Data Warehousing categories. What is BI - Business Intelligence?, BI Definition, BI Tools, Classification of BI Tools.
Relational Vs Analytical. What are - OLTP, OLAP, OLAP categories - MOLAP, ROLAP, HOLAP, Data Warehouse Vs Data Mart, Dependent and Independent Data Mart, Data Warehouse Architecture, Source System, ETL Extraction, Transformation. What is a cube?, Benefits of cube?, How to create the cube?, How to deploy a cube?, How to create a report using a cube?
DIMENSION TABLE - What is a Dimension Table?, Dimension table categories, FACT TABLE - What is Fact Table?, Fact Table Granularity, Fact Table categories.
What is Data Normalization?, Data Normalization Rules - 1NF, 2NF, 3NF, Data De-Normalization, Dimensional Modeling - What is DM?, Principles, Benefits, Type and Technique.
Source System Understanding, Future Data Requirement and Understanding, Designing and Developing Dimension Table, Designing and Developing Fact Table Designing and Developing ER Model With ERwin, Designing and Developing Entity Relationship Modeling.
Open source ETL Talend DI Open Studio -Difference between Licensed and Open Source ETL Tools, What are Licensed and Open Source ETL Tools, Working with ETL Transformation in Talend Open DI Studio.
Building ETL Project Talend DI Open Studio, Understanding the Data Source System which will be a future Data Requirement, Identify Business Requirement Gathering, Building the ETL Talend Technical Design Document, Building an ETL Project.
Data Visualization BI Tool : Tableau 9.x-Introduction to Data Visualization with Tableau, Exploring Data Visualization with Tableau. What is Data Visualization?, Exporting Data and Working With Tableau.
Building Data Visualization BI Project With Tableau 9.x, BI Reporting Understanding, Report and Dashboard Template Document, Tableau Design and Development Database Source Connection.
An Integrated Data Warehousing & BI Project, Developing a Data Warehouse and BI Project, Source System understanding today's data that will be the future data requirement, Identify the Business Requirement Gathering, Report and Dashboard Template Document, Designing and Developing Models, Designing and Developing the Staging Area, Finalizing the Dimension Modeling Type, Designing and Developing Dimension Modeling.
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