Specific aspects of Data Warehouse Development Process

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Data Warehouse Development Process

10 Aug , 2017  


  • Basics of Data Warehouse Concepts
  • Terms and terminologies used in a Data Warehouse and Business Intelligence projects

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.

Who is the target audience?
  • Freshers/Engineering Graduates who are looking for placements
  • Software Engineers from different technology background who want to explore the Data Warehouse and Business Intelligence development process
  • Software Engineers who are already part of any Data Warehouse and Business Intelligence Projects
  • Project Mangers
  • Non IT professionals who like to learn how data is handled in enterprises
  • Technology experts and Team Leaders
  • Architects and Data Modelers
  • Data Scientists and Big Data Experts who want to understand the practical Data Warehouse Process
  • Database Administrators who want to explore the DWH/ETL/BI areas
  • Mainframe developers who want to switch their carrier into the Data Warehouse stream



Specific aspects of Data Warehouse Development Process




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