If you’re experiencing any of the 10 problems below, chances are your data isn’t ready to support meaningful decision making…
Problem: Your data extracts or reports take more than 1 minute to run.
Start with data base tuning, or check out cloud database hosting, like Microsoft Azure.
Problem: You can’t combine data from multiple sources, so the scope of your analysis is limited.
Conformed dimensions standardize values across systems so you can easily link your data sets together.
Problem: You need an analyst to help people figure out what data is stored where.
Keep track of your data flows by using a self-documenting markup language for business intelligence (see BIML).
Problem: Your SQL queries look like a tangled mess.
Use dimensional data modeling to simplify queries. Move messy logic upstream as you load the data warehouse.
Problem: You need help from IT to figure out how to connect all your data sources.
Consolidate your data into a single technology platform, creating a single source of truth.
Problem: Your SQL queries are full of cleanup tasks (CASE, COALESCE, ISNULL, etc.)
Move the cleanup process into your data warehouse’s ETL (extract, transform, load) process.
Problem: Data that spans departments takes more than 10 minutes to combine.
Centralize and automate raw data collection into a single repository (data lake) before feeding it into your data warehouse.
Problem: You frequently argue over which system/department has the right number.
Create accountability with a data governance process that assigns ownership to key data sets.
Problem: You’re paranoid that your data is out of date
Automate the monitoring process to detect missing data, invalid data, and out of control processes.
Problem: The thought of your key data person quitting gives you a panic attack.
Stan is a senior business intelligence architect at Xerva, a BI consulting and DWaaS (Data Warehouse as a Service) company based in Orem, UT. He has been building business intelligence and data science solutions for 20 years, having worked at PricewaterhouseCoopers, HP, Sharp Analytics, and a number of startup companies.