Why each professional has a role to play in Data Science

Written by Gabriel Nyamu

Gabriel Nyamu is a lead Consulting Director with InQuest Research & Consulting and he has vast experience in HR Strategy, Business Processes, Enterprise Systems and project management skills. He is a well accomplished and seasoned Life and Business Coach. Gabriel blends well with his exceptional strategic leadership, people management, business processes, analytical skills and expertise in Business Technologies within an ERP ecosystem hence providing an integrated training and consulting value.

March 26, 2018

In a normal job setup, employees are required to regularly report on their daily engagements in an attempt to assess their progress. Am almost sure only a few use self-developed platforms to record daily activities/engagements and present progress reports. Majority of the organizations rely on already made platforms/templates. This can be challenging at times especially if new complicated features have to be added to the template. This would call for software re-engineering of the current platform to accommodate the changes. This would be expensive and time-consuming. An in-depth understanding of data science techniques among the employees/professionals would act as the best remedy for creating dynamic systems that can accommodate these requirements.

Data Science

Data science in itself is the art of carefully storing raw facts, retrieving them, deducing meaningful information from the data and creating a story out the major findings from the data. This data story forms the basis of tabling recommendations and influencing decisions of an organization. In the long term, it leads to the optimization of business operations alongside increasing employee productivity.

Advancement in Data Management Technologies (MS Excel)

With the evolution of technology, there is a wide range of computer applications that help in data management. Nevertheless, I would recommend the most affordable and easy to learn the tool. In that regard, Microsoft Excel is one of my favourites due to the following reasons: It does not need a very strong background in computing and mathematics, it can automate repetitive tasks thus increases employee productivity.

Equipping yourself with the MS Excel tricks and skills will guarantee a well-formatted data model which will, in turn, save data retrieval time. The column row structure of excel ensures that data can be entered and retrieved with ease. Other capabilities include the design of an interactive user-friendly platform commonly known as dashboards which will help you report findings from the data like a real professional. The most interesting thing with MS Excel is the fact that you can automate tasks and present data visualizations differently at any specific time. Advanced MS Excel features like charting, pivot tables help in bringing a pictorial view of the raw facts on the ground.

The features of MS Excel are quite extensive, but with a three full-day training program, you can learn the best way to structure your data (Data Modelling). Once you have a good data model, an analysis will be straight forward. This will then be followed by an implementation of a project which will help your role in data science.

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