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Searching for the Holy Grail of Data Analytics

By Raphael Wieland

Last summer, I joined Whittaker Associates as an industry analyst intern. Most of the work I did then consisted of researching targeted industries and the trends within those industries. After I was well-acquainted with what the client wanted, I would generate leads to later be researched by our research team. What I enjoyed most about my job last summer was learning about all kinds of different cutting edge industries and what exactly was happening within them.

This summer, I am happy to return to Whittaker Associates in a different role. During this internship, I am primarily working on a project to improve WALTER’s (Whittaker Associates’ Lead Tracker database) functionality and to find ways to better use the hundreds of data points we have collected in the database. Although this quest for the “Holy Grail” is an ambitious, long-term goal, we are also working on shorter term projects. Even if we don’t find the Grail, by the end of the summer we will still have plenty of tangible insights into how WALTER can be improved.

As part of my quest for the Holy Grail, I am taking a Data Analytics course form CUNY. What I hope to get out of this course is a better understanding of how we can use data analytics to create an indexed list of companies in WALTER. During the ten week bridge course, I will become acquainted with SQL, Python, and R. SQL (Structured Query Language) is a language designed for managing data held in a relational database. Learning SQL will allow me to handle the data in WALTER without using that pretty Dutch-orange graphical user interface. Python is a high-level, general purpose, object oriented programming language. It boasts clean, readable syntax which allows for more compact programs. R is a language designed for statistical computing and graphics.

Starting in August, I will apply what I’ve learned from this course to WALTER to help create more value in what we do.

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