Data analysis is a complex process with many steps to take and many things to consider to make it right. It starts with collecting the data and storing it in an appropriate form for further processing. Next there has to be the right infrastructure for the analysts of your data to work in and to be productive. The so-called ETL (extract, transform, and load) workflows has to be fast and reliable too. Finally, you should implement data quality assurance policies and automate their compliance to make sure that the analysis is correct and meaningful.
As you can see, this is a sophisticated process that can quickly get out of hands. Luckily, with the right team at your disposal, you can overcome this challenge and start gaining value from your data.
