Advanced Data Warehousing Course and Certification

Course Schedule and Upcoming Batches

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Classes Start
Time (IST)
Price (INR)
Price (USD)
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5 Weeks
9:00 AM- 1:00 PM

This course is open for Enrollment and Payment.

In case you want to Register now and take up this course later, you can register by clicking on " Register" section.

If you have any query, you can call/mail or send your query by clicking on " Send a Query" section.

About the Course

This course is designed to give a learner the Advanced level knowledge on Data Warehousing and Data Integration activities. This course will provide them the knowledge to create Architecture and Design for world class BI & Data Warehousing systems.

Most of the training courses in market are focused on Data Warehousing and ETL tools now days; tools are no doubt necessary to start a career in ETL/DWH but the next logical step for any DWH practitioner should be to grow as an Architect or a Designer. This training uncovers the best industry practices, knowledge and processes around Data Warehousing Architecture & Design.

Course Objective

After completion of this course, you will be able to:

  1. Gain understanding of all Data Warehousing concepts.
  2. Learn Data Warehousing strategy and critical factors.
  3. Learn about Data Warehousing building blocks and Master Data Management.
  4. Gain a good understanding of Data Warehousing Architecture and about major Architecture frameworks.
  5. Learn about Data Warehousing components & systems and how they function together.
  6. Learn about end to end system flow of Data Warehousing systems.
  7. Learn about Data Warehousing Design components and how to create a Data Warehousing Design.
  8. Learn advanced topics like Data Governance,Data Profiling, Data Quality,Metadata, Tool Selection etc
  9. Learn about Data Warehousing Success and Risk factors and Best Practices .
  10. Gain an understanding about Data Warehousing Organization Structures , Data Warehousing Roles and responsibilities.
  11. Get a one on one guidance from us regarding the career.
  12. Get a customized career roadmap.

Why is it the right course for you?

If you aspire to become a world class Architect ,Project Manager or Designer in Data Warehousing space then this is the right course for you. This course will help you equip with an overall understanding of Data Warehousing Architecture. This will enable you to start taking complex assignments in Data Warehousing space.


You need to be familiar with Data Warehousing domain. You need to have a basic understanding of Database concepts. Experience in Data Warehousing is desirable but not necessary.

Course Curriculum

Section A : Introduction

1) Introduction to Data Warehousing

Data Warehouse Definitions, Value of Datawarehouse, Reasons for building Data warehouse, Reasons for NOT building.

2) Data Warehousing Strategy

Business Purpose, Business usage, Enterprise or line of business? When are we done? Where to start? Where to start in BI? Where to start in Data warehousing?

3) Critical Factors

Project Phasing, Effort to create a central enterprise data vocabulary. Effort to model a Data warehouse repository. Stepwise approach, Research, Strategic alignment ,Focus or limited scope. Value,Metrics,Goals, Executive support,Business sponsor,Data management ,Data quality, Performance usage,Flexible framework ,How to start DWH and BI.

4) What is the difference between Business Intelligence, Data Warehousing, Analytics and Big Data

In this module you will get a clear idea about the distinctions between BI, Data Warehousing, Analytics and Big Data and learn how these Data Science technologies co-exists together.

5) Framework of Business Intelligence and Data Science Study

In this module you will learn about various discipline of data sciences and how are they interlinked together. You will also learn about various learning and job related opportunities and how can you transition yourself for next generation roles.

Section B : Data Warehousing Basics

  1. Difference between a Database, Datawarehouse, Datamart, OLTP and OLAP
  2. Dimension, Fact, Hierarchies, Types of dimensions
  3. Normalization, Schema, Star Schema, Snowflake Schema, Galaxy Schema
  4. Metadata
  5. Data and Dimensional Modeling
  6. ETL, Extract , Transform and Loading techniques. Source , Processing and Target Stages.

Section C : Building Blocks of Data Warehousing

1) Data

Corporate data ,Data quality,Data standards ,Data Components,Data Architecture,Data Model , Build or buy Data Model?

2) Some Basic Structures

Dimensions, Dimensional Data Model, Facts ,Star, Snowflake, Bus Architecture, OLAP, ODS, ETL, Data Mart, Granularity ,De-Normalization, Enterprise Data Warehouse

3) Master Data Management

Master Data, Deciding What to Manage ,Why to Manage Master Data? ,How to Create and maintain a Master List?

Section D : Architecture

1) Business Architecture

Performance, Stakeholders, Processes, Business Rules, Business Information

2) Organization Architecture

  • People- roles, skills
  • Action- Goals, Results, RACI
  • Information flow- Decision, execution,communication
  • Structure- Reporting structure, dependencies

3) Data Architecture

Concept, Collection, Storage, Distribution, Access, Application, Documentation

4) Datawarehousing Architecture Views

  • From IT Infrastructure Perspective
  • From Data Flow Perspective
  • From Business Usage Perspective
  • From BI Application Development Perspective

5) Major Datawarehousing Architectures

  • Bill Inmon's Corporate Information Factory( CIF) or hub and spoke/centralized/top down approach
  • Inmon's BI2.0, DW2.0
  • Ralph Kimball's Dimensional Bus Metrix system or bottom up approach
  • Hybrid of Bill inmon and Ralph Kimbal
  • Comparison between Bill Inmon and Ralph Kimball Architectures and Project Management approaches
  • Virtualization or Federated Architecture
  • Forrester Data Architecture
  • Gartner's Data Service Layer or Logical Data warehouse
  • Zachman Framework
  • In-memory processing (such as SAP Hana)
  • Large scale parallel processing (such as hadoop)
  • Data Lakes
  • Architecture Comparison and strategy for choosing the best Architecture

Section E: Datawarehousing Systems and Components

1) Source systems

2) Data Acquisition

  • Data Profiling
  • CDC System
  • Extract System
  • Data staging area
  • ODS

3) Data Processing system

  • Cleansing
  • Error Recording/handler
  • Redundancy removal
  • Standardization
  • Sorting and Filter system
  • Slowly Changing Dimension handler
  • Surrogate Key System
  • Late Arriving Data Handler
  • Reconciling Handler
  • Metadata builder
  • Housekeeping System
  • Batch v/s online query system
  • Big Data processing system

4) Data Loading system

  • One time load system
  • Reference Table builder
  • Dimension Builder
  • Hierarchy builder
  • Surrogate key generator
  • Miscellaneous reference/dimension generator
  • Fact Table Builder
  • Summary Builder

5) Datawarehousing Management components

  • Scheduler
  • Backup & Recovery
  • Monitoring
  • Issue escalation and resolution systems
  • Security system
  • Version Control system
  • Compliance manager
  • Infrastructure & Server Management system
  • Upgrade policies
  • Support
  • Batch run window

Section F: Datawarehousing Design and Development

1) Types of development models

2) Development Stages

3) Designing Datawarehousing Systems

  • Datawarehousing Design flow
  • Requirements
  • High level plan as per the requirement
  • Tool selection
  • Guidelines and Checklists
  • Estimation
  • Detailed Plan
  • Architecture design
  • Data design
  • Detailed design specifications
  • Development environments
  • Development steps
  • Reviews and Quality
  • Testing
  • Deployment
  • Maintenance
  • Enhancements
  • CR

Section G: Datawarehousing Essentials

  • Wrinkle of time
  • Feedback loop from Datawarehousing to OLTP
  • Direct access to Datawarehousing
  • Indirect access to Datawarehousing
  • Security Considerations
  • Return on investment Considerations
  • Success factors
  • Risk factors
  • Datawarehousing project failure reasons
  • Best practices of Datawarehousing

Section H: Roles and responsibilities

  • Team
  • Senior expertise
  • Leadership
  • Project sponsor
  • Business executive sponsor
  • IT executive sponsor
  • Data Steward
  • Steering committee
  • Project manager
  • DW Architect
  • Data Modelers
  • Business Analyst
  • Subject Matter expert
  • ETL programmer
  • DBA
  • BI Programmer
  • Testers
  • Trainer
  • Support
  • Big Data programmer
  • Analytics experts
  • Career Roadmap for a BI professional

Course Duration

Online Classes : 20 Hours

There will be ten instructor led interactive online classes during the course. Each class will be of approximately two hours. If you miss a class then you can reschedule it in a different batch or you can also access Class video recordings anytime.

Assignment Work : 20 Hours

Assignments will be given to learners to be completed during the course duration.

Course Work : 40 Hours

Study material of 40 hours or more will be given as a course work to be completed.

Exam : 1 Hour

A proctored exam of 1 hour will be conducted for final assessment.

Course Features

  • Live Classes

    Live Instructor Led classes from Industry Experts. Option to choose from Online or Classroom Lectures. Case studies from real life projects.

  • Ongoing Research

    Research team works hard to bring out the latest innovations and best practices of course subjects. Courses are evolving continuously; they never get stale.

  • Be More Productive

    Get work related tips and perform your work more efficiently. Once you know the tricks of trade, you become more productive.

  • Industry Experts

    Classes are conducted by Industry Experts. Learners gain from world class curriculum and extensive experiences of Trainers as well.

  • Easy Reschedule

    Have you missed a class? Don't worry !!, You can watch the class videos or you can also request for a reschedule. We will invite you for next class for Free.

  • Learning Material

    Learners get unlimited access to online and offline materials. Don't worry if you miss any class, we will be providing you a repeat class online or offline.

  • Learning Support

    Learners are encouraged to ask online and offline questions. Our team of Trainers makes it a priority to answer these questions.

  • Money-back Guarantee

    If you are not satisfied with the quality then take full refund within the seven days of first class. No questions will be asked.

  • Career Support

    Learner's resume is reviewed and a one-to-one discussion is arranged with an expert to advice on career roadmap and job opportunities. For details, visit Career Centre


Certificate of Participation

A certificate of participation will be awarded after participating in the training program. The name of certificate is "BIWHIZ CERTIFICATE OF PARTICIPATION ON DATA WAREHOUSING".

Certification after Completion

A certification will be issued after assessment of assignments, course work requirements, projects and a written test as per the course curriculum. After successfully completing all the requirements and passing the written test, a certification will be issued. The name of the certification is "BIWHIZ CERTIFICATION ON DATA WAREHOUSING".

Certificate Issuing Authority

BIWHIZ is part of the company "Business Intelligence Consultant and Services LLP". Certificates are issued by "Business Intelligence Consultant and Services LLP". This is a registered company with Ministry of Corporate Affairs, Government of India.

Sample Exam Questions

This sample is only for illustrative purpose and only basic level questions are displayed here. Actual exam questions may be completely different with different format as well. Please contact your coordinator to know more about prevailing exam format.

Data Warehousing is?

Choose one.

  1. A Technology
  2. A Process of creating Data Warehouse
  3. Set of Tools
  4. ETL

What is MDM?

Choose one.

  1. Part of Datawarehouse
  2. Centralized database for Master lists
  3. An ETL process
  4. Source System

Which Architecture is best?

Choose one.

  1. Bill Inmon
  2. Ralph Kimball
  3. In-Memory
  4. Can't say

Which is not a must for DWH?

Choose one.

  1. Surrogate Key
  2. Scheduler
  3. Source
  4. Data Mart

What is a DWH deliverable?

Choose one.

  1. Report
  2. Dashboard
  3. Scorecard
  4. Data Mart

What is Wrinkle of time?

Choose one.

  1. Data Change propagation strategy
  2. Expansion of Time dimension
  3. Summarization based on Time
  4. Removing Time dimension

Frequently Asked Questions

  1. Is it necessary to have an experience in Datawarehousing/ETL before starting this course?

    It is not necessary that you should have a prior experience, however we recommend that you should be aware of this domain. You can also take up Beginner's course before starting on Advanced course.

  2. I am already working in ETL for long time and I have a good command on ETL Tools, I think I do not need to take up this course?

    If you think that you can work on Design and Architecture parts of Data warehousing and have good experience and knowledge on those then you can skip this course, however if you have good knowledge on coding and ETL tools but still not doing design then you can enroll for this course to get knowledge on Design and Architecture skills.

  3. Why Certification is included in the course?

    This is to make sure that a learner has understood the course content and BIWHIZ has verified the knowledge level of the Learner. Certification is the proof that you have achieved a certain level of expertise on course and any authorized organization can verify that with us.

  4. What if I am not able to clear the Certification exam in first attempt?

    You can take extra attempts for free.

  5. What is the learning support and would it be available after completing the course as well?

    You can raise your queries and doubts during and post training period. All queries will be resolved by BI experts.

  6. Do you help in career related issues as well, like reviewing resume, mentoring for my career growth?

    Yes, we have a panel of BI/DWH experts who will guide and mentor you; please check Career Centre for more details.

  7. I heard that BI/DWH is dying and Big data is going to replace all BI/DWH technologies very soon, why should I still learn DWH?

    It is a myth that Big Data will kill all existing BI/DWH technologies. All these technologies are going to co-exist together as there are specific use cases for each of these technologies. Slowly all ETL tools will start incorporating access to Big Data as well. In case you are interested only for Big Data or Analytics, we run those courses too.

  8. Will you sell my data to Recruitment/marketing companies or will you use it for Recruitment or any other activities not related with Training?

    NO, Never. Your details are highly confidential and safe with us. But If you are willing to accept any such calls then you can inform us in advance with a specific need and we will contact only for those specific requirements. For a detailed privacy policy please check Terms, Conditions & Privacy Policy.

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