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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

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.

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