Trusted Data Analytics for Effective Decision-Making

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In 2006, Tampa Bay (then Devil) Rays’ Manager Joe Maddon had an idea. He had noticed in his pregame sabermetrics and analytics review, that David Ortiz, the Red Sox slugger, had a tendency to hit the ball to the right side of the field much more than to the left. He placed his shortstop to the right of second base when Ortiz was batting, and with that, analytics “officially” entered baseball. The proof was in the pudding, as Ortiz’s batting average for the three years prior was above .300, and as more and more teams began to utilize the Ortiz shift, his average went down significantly, all the way to .265.

Three Components of Analytics

Data Collection

There is a three part process of correctly using analytics. The first part, is collection of the data. This needs to be planned well, with the determination of the most useful data vs. the difficulty in achieving it. Asking this question before starting will ensure you aren’t wasting your valuable time, and you are being the most efficient possible. Try to use automation where possible (Imagine going through each pitch manually!). And ensure that the data is as accurate as can be, because stages 2 and 3 will be primarily based upon 1.

Data Analysis

Once you have the data, its time to read it correctly. Just like we all learned how to read English, data is a language of its own. Data analysis consists of taking the data, presumably in graph/table form, and finding key takeaways of the data itself. And if you are presenting to your team, it is best to select the most important data that can be used productively.

Implementing Change

All of this can be useless unless you use the data to improve our existing processes. Once you collect the data, and analyze what is and isn’t working, the logical next step is to improve upon the areas that need to be fixed, and emphasize the areas the data is showing positive results. And now the pitcher can focus on throwing the cleanup a curveball high and inside.

Why the Sudden Surge in Data Analytics Use?

The data we are now privy too is unprecedented, and easy to access. Every company uses data in order to analyze their business processes, and more and more BI Tools are being created to assist. Additionally, regulations now force companies to ensure they know what they are doing with their data, especially sensitive personal data.

Where does Come In?

Many companies do data discovery and analytics. But at, we actually use those analytics to ensure that the data collection is done accurately, turning “Analytics” into “Trusted Analytics”. Our AI and Machine Learning systems crawl and locate all repositories, including ones you didn’t even know existed, giving you a fully accurate map of the data and its lineage.

Time to make a home-run decision.

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