Guidelines for creating Data Architecture

Author: Omid Vahdaty 30.8.2020​

In this blog I will share my methodology for data architecture

High level guidelines 

  1. Product Discovery: Talk to the management team, understand the product, Type of users, and Type of features.
  2. Data Mapping: Map all the operational data tables, granularity level and foreign keys to other tables. Assume there will  be 3rd party data sources such as GA (free or 360), Firebase analytics etc.
  3. Hypnotize : Generate a list of  desired granularity, dimensions, metrics, measures, attributes, based on business questions created by product and marketing teams.
  4. Create a draft Data Architecture that is layer (Ingestion, transformation, modeling, presentation). read this blog about Big Data Architecture.
  5. Gap Analysis: confirm with the stakeholders that data exists to generate the above data architecture.
  6. Implement the data architecture.


I put a lot of thoughts into these blogs, so I could share the information in a clear and useful way.
If you have any comments, thoughts, questions, or you need someone to consult with,

feel free to contact me via LinkedIn:

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