Cooking shows are very popular, and many of them show creative, talented chefs whipping up delicious and innovative dishes with confidence and skill. What fewer of the shows explore is the prep work that is done in advance to allow those talented chefs to move through their tasks with ease and without distracting barriers to their progress.
In restaurants around the world, that kind of work is done by people known as “prep cooks.” They are in charge of the daily tasks that make possible the innovation and creativity most people notice when they sit down for some fine dining. Prep cooks chop vegetables, grind or cut up meat, and mix ingredients together to form bases and staples that can be pulled into many different meals as the chef’s imagination takes hold.
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While the prep cook may not get the glory or their own cooking show, their role is crucial to the success of the chef. In the data world, this same relationship is necessary for truly innovative, groundbreaking applications of data. Any company hoping to get their data into the hands of their most creative team members should make sure there is a “prep cook” laying it out in a way that is user-friendly and accessible.
What happens without data prep?
Without ongoing, regular data prep, databases become inaccessible, cumbersome, and sometimes unusable. Companies hire data scientists with the hope that they will put all of their (often expensively-collected) data to good use by using it to create more efficient systems, revolutionize processes, and otherwise make the business more effective.
However, the reality is that data scientists are spending most of their time just trying to get a handle on the data in the first place. They’re calling from department to department to track down the data they need. They’re editing spreadsheets to make the headings readable. They’re finding out there is no metadata to help them make sense of the information in front of them. Overall, 80% of the average data scientist’s time is spent trying to find, clean, and reorganize their data while only 20% is spent actually analyzing it and finding ways to put it into use.
What can a “prep cook” do for data?
With so much of a typical data scientist’s time going to data management and “janitorial” tasks, data preparation has the potential to truly transform the way they spend their time and direct their attention. Those insights and innovations that they were hired to produce can become much more likely and frequent if they are handed materials in a way that is accessible, usable, and convenient.
Data prep allows for just this arrangement. The data prep cooks spend time making sure that all of the data is getting collected and, once collected, that it is going into a well-organized, accessible storage system. This work is certainly less exciting and flashy than analyzing data and using it to come to new conclusions and recommendations, but without the prep work, those insights and innovations are much less likely to happen.
When a restaurant brings in a star chef to energize their brand and drive customers to line up around the block, they make sure that the chef has all of the tools necessary to do an amazing job. They don’t let the chef waste their talent and time on washing carrots. Instead, they put supports in place to ensure that the chef can focus on what matters most: using the ingredients to create something new and exciting. If data is approached in the same way, data scientists will be free to spend their time creating new and exciting insights as well.
As Director of Enterprise Analytics, James helped Thomson Reuters establish data management capabilities and an enterprise-wide analytics competency.
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