Data Management & Warehousing

What is a Data Warehouse?

A Data Warehouse is a digital library that gathers data from various places. It organizes and stores this data so you can easily find and analyze it later. Imagine you're working for an online store. The data warehouse could have data from your ordering system, web logs, and customer service feedback. Data Analysts use tools like Tableau to query this big digital library. Data Scientists write code to perform deeper analysis, often involving AI.

This is a field that's really been upended by Hadoop, big data techniques, ELT and ETL, cloud computing etc.

Challenges and Complexities

Running a data warehouse is not easy; it's like being a librarian for a library that never stops growing. You need to make sure all the 'books' (data) use the same 'language' (format) and none are 'damaged' (corrupted).

ELT and ETL

Data often comes in raw and messy. You have to clean and transform it before it enters the data warehouse. This transformation can be ELT (Extract, Load, Transform) or ETL (Extract, Transform, Load), depending on when you clean it. How do I actually make sure that a column in one data source is comparable to a column from another data source and has the same set of data, at the same scale, using the same terminology? How do I deal with missing data? How do I deal with corrupt data or data from outliers, or from robots and things like that? These are all very big challenges. Maintaining those data feeds is also a very big problem.

Scaling Concerns

As your digital library grows, making space for new data and keeping everything organized can get challenging. This is a big concern for data warehouses, especially for large organizations.