So here are a few steps you need to follow into building a data warehouse:
Defining Business Requirements:
- Aligning department goals
- Discovering your future needs and current needs by diving deep into your data
- Creating a disaster recovery plan in the case of system failure
Setting Up Physical Environments:
- Data warehouses typically have three primary physical environments — development, testing, and production
- You need a way to test changes before they move into the production environment.
- Running tests can often introduce breakpoints and hang your entire server. That's definitely not something you want happening in your production environment.
- Data modeling is the process of visualizing data distribution in your warehouse. Think of it as a blueprint.
- Data modeling is probably the most complex phase of data warehouse design.
- Data modeling typically takes place at the data mart level and branches out into your data warehouse.
Extract, Transfer, Load (ETL) Solution:
- You want optimal speeds, good visualization, and the ability to build an easy, replicable, and consistent data pipeline between all of your existing architecture and your new warehouse.
- For most businesses, ETL will be your go-to for pulling data from systems into your warehouse.
I hope this will be helpful.
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