Data Warehouse Development Process
Specific aspects of Data Warehouse Development Process
Created by Inf Sid, Last Updated 22-Oct-2019, Language:English
Description
Data is the new asset for the enterprises. And, Data Warehouse store the data for better insights and knowledge using Business Intelligence. Development of an Enterprise Data Warehouse has more challenges compared to any other software projects because of the
Challenges with data structures
The way data is evaluated for it's quality
Complex business rules/validations
Different development methods (various SDLC models like Water Fall model, V model, Agile Model, Incremental model, Iterative model)
Regulatory requirements for various domains like finance, telecom, insurance, Retail and IME
Compliance from third party governing bodies
Extracting data for various visualization purposes
In this course, we talk about the specific aspects of the Data Warehouse Development process taking real time practical situations and how to handle them better using best practices for sustainable, scalable and robust implementations.
Requirements
- Basics of Data Warehouse Concepts
- Terms and terminologies used in a Data Warehouse and Business Intelligence projects
What Will I Get ?
- Understand various stages in Data Warehouse development process
- Various processes like Waterfall model, V model and Agile methods
- Specific aspects of Data Warehouse development process
- Importance of the various phases and the practicality of each phase
- Overview of various issues and Project Management issues to be considered in the Data warehouse and Business Intelligence projects
Course Content
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Introduction
2 Lectures
00:07:37
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Welcome and Thank you!
Preview00:06:00 -
Practical Exercises, Documents and Material
Preview00:01:37
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Different Categories of Data Warehouse Implementations
1 Lectures
00:04:59
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Different Categories of Data Warehouse Projects
Preview00:04:59
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Keywords/Terms used in this course
5 Lectures
00:20:11
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Data warehouse and Business Intelligence Glossary Part 1
Preview00:07:13 -
Data warehouse and Business Intelligence Glossary Part 2
00:04:24 -
Additional Information on all the related keywords for the DW/BI projects
00:01:15 -
What are Functional Requirements?
00:02:52 -
What are Non Functional Requirements?
00:04:27
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Methodologies used for Data Warehouse Software Development
2 Lectures
00:08:12
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The Software Development Process
00:04:39 -
What are the widely used methodologies for Enterprise Data Warehouse Set up?
00:03:33
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Waterfall Model
11 Lectures
00:43:07
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What is the Waterfall Model and what are the different phases involved?
00:02:20 -
What are the different phases in Waterfall model?
00:01:43 -
What is the Requirements phase?
00:06:12 -
What Is The Importance Of The Analysis Phase And How IT Plays A Part In This?
00:02:22 -
What are the activities done during the Design phase?
00:07:45 -
What are the activities done during the Coding phase?
00:03:48 -
What are the activities done during the Testing phase?
00:03:08 -
What are the activities in Operations and Maintenance Phase?
00:04:26 -
Follow the POC (Proof of Concept) model for better results
00:04:26 -
What are the advantages of using the Waterfall Model?
00:02:59 -
What are the disadvantages of using the Waterfall Model?
00:03:58
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V Model
3 Lectures
00:20:10
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What are the different activities in the Verification phase?
00:12:00 -
What are the different activities in the Validation phase?
00:06:06 -
What are the advantages of the V Model?
00:02:04
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Agile Model
5 Lectures
00:23:37
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Iterative Model
00:10:40 -
Incremental Model
00:03:16 -
Agile Model
00:02:23 -
What are the advantages of Agile Model?
00:05:04 -
What are the disadvantages of Agile Model?
00:02:14
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Other SDLC Models
1 Lectures
00:01:33
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What are the other SDLC Models?
00:01:33
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Which model to choose for the available models?
1 Lectures
00:04:24
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Which is the best model?
00:04:24
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Practical Implementation Steps
1 Lectures
00:02:12
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What are the practical implementation steps for the project?
00:02:12
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Project Planning
6 Lectures
00:17:13
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Defining the scope for the requirements
00:06:01 -
Determining the goals and objectives of the project
00:02:26 -
The Implementation Strategy
00:02:06 -
Resource Identification and Alignment
00:03:37 -
Project Deliverable and Timeline
00:01:35 -
Summary - Quick Recap
00:01:28
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Requirements
8 Lectures
00:35:18
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What are needed?
00:02:10 -
Who provides the inputs?
00:02:59 -
Who gathers the requirements?
00:01:15 -
How to perform the interviews to gather the requirements?
00:04:06 -
Common questions which are usually asked during the Interviews
00:10:35 -
Common questions which Business can ask IT
00:08:53 -
Review of existing documents and resources
00:00:45 -
Analyze the existing sources
00:04:35
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Design
7 Lectures
00:17:35
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Design of the logical data model
00:01:32 -
Data Architecture
00:02:15 -
Data Architecture - How the data is organized and structured for various phases
00:05:25 -
Technical Architecture
00:01:04 -
Technical Architecture - The Hardware and Software part
00:04:07 -
Delivery Framework
00:01:01 -
Design the ETL process and functions
00:02:11
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Build and Develop
5 Lectures
00:08:22
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Infrastructure SetUp
00:01:47 -
Data Warehouse/RDBMS Setup
00:00:46 -
ETL Setup
00:02:49 -
OLAP and Reporting Setup
00:00:58 -
Testing the data flow
00:02:02
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Deploy
1 Lectures
00:03:00
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Versioning, Deployment and Production Release
00:03:00
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Maintenance and Operations
1 Lectures
00:04:26
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What are the activities done during the maintenance and operations?
00:04:26
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Review of the completed tasks
3 Lectures
00:13:45
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What went Right? and What went Wrong?
00:04:35 -
Scoping and De-Scoping
00:02:33 -
Application Usage Review
00:06:37
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Production Support and Maintenance
1 Lectures
00:07:46
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Support and Maintenance
00:07:46
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Final Note
1 Lectures
00:01:34
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Final note on the course and how to get in touch with me
00:01:34
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Inf Sid
Data Management Consultant
Business Intelligence Consultant and Trainer with 16+ years of extensive work experience on various client engagements. Delivered many large data warehousing projects and trained numerous professionals on business intelligence technologies. Extensively worked on all facets of data warehousing including requirement gathering, gap analysis, database design, data integration, data modeling, enterprise reporting, data analytics, data quality, data visualization, OLAP. Has worked on broad range of business verticals and hold exceptional expertise on various ETL tools like Informatica Powercenter, SSIS, ODI and IDQ, Data Virtualization, DVO, MDM.
