Data Warehousing Certification Training Course

Data Warehousing Certification Training Course Course

Edureka’s self-paced course delivers a balanced mix of theory and hands-on tooling across the data warehousing lifecycle. The capstone project ties modules together into a cohesive, job-ready skill se...

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Data Warehousing Certification Training Course on Edureka — Edureka’s self-paced course delivers a balanced mix of theory and hands-on tooling across the data warehousing lifecycle. The capstone project ties modules together into a cohesive, job-ready skill set.

Pros

  • Comprehensive coverage of both modeling and ETL tools
  • Real-world assignments using Talend and Tableau
  • Capstone project reinforces end-to-end pipeline skills

Cons

  • Limited focus on streaming data and cloud-native warehouses
  • Assumes some prior SQL and database knowledge

Data Warehousing Certification Training Course Course

Platform: Edureka

Instructor: Unknown

What will you learn in Data Warehousing Certification Training Course

  • Grasp core data warehousing concepts: subject orientation, time variance, and integration.

  • Design and implement dimensional models using star and snowflake schemas.

  • Handle Slowly Changing Dimensions (Types I–III) and maintain historical data.

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  • Build end-to-end ETL pipelines with Talend, including extraction, transformation, and load.

  • Model data with ERWin and generate metadata for reporting.

  • Create BI dashboards and visualizations in Tableau to derive insights.

Program Overview

Module 1: Data Warehouse Fundamentals

⏳ 3 hours

  • Topics: OLTP vs. OLAP, Data Marts, Operational Data Store, warehouse architecture.

  • Hands-on: Sketch your own warehouse architecture and identify key components.

Module 2: Dimensional Modeling & SCD

⏳ 4 hours

  • Topics: Fact vs. dimension tables, hierarchies, star and snowflake schemas, Slowly Changing Dimensions.

  • Hands-on: Model a customer sales schema and implement SCD Type II in ERWin.

Module 3: Normalization & Schema Design

⏳ 3 hours

  • Topics: Normal forms, galaxy schemas, metadata management.

  • Hands-on: Normalize a sample dataset and map to appropriate schema types.

Module 4: ETL Development with Talend

⏳ 6 hours

  • Topics: Talend components, data extraction, transformation functions, job orchestration.

  • Hands-on: Build a Talend job to ingest CSV and database sources into staging.

Module 5: BI Visualization with Tableau

⏳ 5 hours

  • Topics: Connecting Tableau to warehouses, building dashboards, filters, calculated fields.

  • Hands-on: Create interactive dashboards tracking sales trends and KPIs.

Module 6: Capstone Project

⏳ 4 hours

  • Topics: End-to-end pipeline orchestration, from source ingestion to dashboard delivery.

  • Hands-on: Deliver a complete mini-project: ingest raw data, model it, load into warehouse, and build a Tableau dashboard.

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Job Outlook

  • Data engineers, ETL developers, and BI analysts command salaries from $90K–$130K USD.

  • Expertise spans industries: finance, healthcare, retail, and tech.

  • Skills in Talend, ERWin, and Tableau are highly sought after for enterprise analytics roles.

  • Career paths include Data Architect, Analytics Engineer, and BI Consultant.

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  • What Is Data Management – Learn how proper data management underpins efficient data warehousing, analytics, and decision-making processes.

FAQs

Do I need to know SQL before starting this course?
Basic SQL knowledge is helpful but not mandatory. The course introduces queries during modeling and ETL. Tools like Talend simplify extraction and transformation tasks. SQL is used mainly for schema design and reporting. Beginners can learn SQL in parallel to strengthen understanding.
How is this course different from learning just Tableau or Talend separately?
This course combines modeling, ETL, and visualization in one pipeline. It shows how tools work together in real-world workflows. Tableau is applied directly to warehouse data models. Talend connects transformation logic with reporting dashboards. End-to-end learning is more valuable than tool-specific training.
Will this course prepare me for cloud-based warehouses like Snowflake or BigQuery?
The course focuses on fundamentals and on-premise tools. Core modeling and ETL concepts are universal across platforms. Transitioning to Snowflake/BigQuery requires only minor adjustments. Skills in dimensional modeling and SCD apply equally in the cloud. Cloud-native courses can be taken afterward for specialization.
Can data warehousing knowledge help in data science careers?
Warehousing ensures clean, structured data for analytics. Data scientists rely on reliable pipelines for insights. Understanding schemas improves dataset preparation. Business analysts benefit from consistent reporting dashboards. It creates a strong foundation before applying machine learning.
What career roles can I apply for after completing this course?
ETL Developer or Data Integration Specialist. BI Analyst or Reporting Consultant. Data Engineer working on pipelines and modeling. Data Architect for larger-scale solutions. Analytics Engineer bridging data and business teams.

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