If you’ve been following InterWorks over the years, you know we love a good metaphor for data and analytics concepts. Our newest metaphor might just be our freshest one yet. We call it the Data Laundry Cycle. I’ll give a quick explanation of how it works, followed by a more detailed guide that you can download for free.
What Is the Data Laundry Cycle?
Imagine data like a closet full of clothes. When data is dirty, disorganized or inaccessible, it’s like a pile of wrinkled clothes. When it’s clean, organized and available, you can easily pick out info that presents your business at its finest. That all sounds great, but how do you make it happen? The basic premise goes something like this:
Source Systems (Dirty Laundry): Raw data is like dirty laundry. You have different formats, qualities and sources, just like your clothes have different colors, fabrics and levels of dirtiness.
ETL Solutions (Laundromat): Much like a laundromat helps you sort, wash, dry and fold your clothes, ETL solutions help you extract, ingest, transform, clean and organize your data.
Production Data Warehouse (Organized Closet): When clothes are clean and sorted, you arrange them in your closet. When data is clean and sorted, you arrange it in an accessible and trusted data warehouse.
Dive Deeper with Our Free Guide
Of course, this is all an incredibly simplified view of how to go from convoluted source data to sparkling insights, but it’s important to know the basics before delving deeper. Speaking of which, you can indeed delve deeper via our free Data Laundry Cycle Guide, which you can download here.
What will you find here? You’ll see more context for the above steps, but the big takeaway is a detailed map of common data challenges, recommendations for improving them and the potential outcomes/benefits as a result.
You can download the guide for free below but know that our team is always ready to talk through your specific data challenges and can provide a wealth of expertise and relevant solutions to help you prepare your data for organizational success. Just give us a shout!
