My story with data
I'm a data professional because I enjoy the field. From a young age my hobbies had me organizing data, and my earliest jobs I always found ways to provide value to my employer with the organization and analysis of information. My first 'database' was in Cardfile, organizing my dad's record collection. Professionally I and teams I have led have developed data collection and deep analysis tools and systems for clients such as the Department of Water Resources, Pacific Gas & Electric, and the United States Department of Defence.
The Process of your Data Transformation
Your organization has likely evolved into having a whole lot of data, and no real good way to gain insights from it. We've gained much in our ability to store data, and we have tons of it. You may even have been sold into the 'data lake' concept... and not found any benefit.
Your data probably needs organization and cleaning. You might have a data swamp.
Step One
Inventory
An inventory of your data should also identify processes that are creating data gaps. These should be fixed in concurrence, and all opportunities to fill those gaps implemented.
Step Two
Extract, Transform, Load
Extract data from any source in your company, transform it to fit in a structured and normalized data warehouse, and load it to the warehouse.
Now our ETL process can include a preliminary step: Clean
Step Three
Analyze
From simple summaries to machine learning, your data holds insights to your business that will either catch you up to your competitors, or provide you with a competitive edge. Either way, you need it.