Technically Speaking

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The Experts You Need in a Big Data Team

Many articles explain the benefits of big data so that many businesses are now aware that they should get on board in time. However, not many explain how to assemble a big data team: this is the focus of this piece.

Many articles explain the benefits of big data so that many businesses are now aware that they should get on board in time. However, not many explain how to assemble a big data team: this is the focus of this piece.

Starting with Big Data

You collect the data, you have cloud infrastructure to process that data (even in real-time), but you need a team to train the machine learning at first, or to interpret the data mathematically and in a business way.

This is why you need a good team. Depending on the level of your business, you scale that team, however, the team composition remains. Maybe you add more data scientists, or maybe you add more business analysts, but here are the main roles:

The Data Scientist

Glassdoor ranked data scientist as the #1 job in the United States for three years running with a median base salary of 110,000$. This is not random because you need a data scientist in your company.

At the moment, software is not enough to do big data and a human supervising both the collection, the preparing, and the results of the data processing is irreplaceable. The data scientist advises you how to properly collect and prepare the data, and then looks at the results of the processing and interprets them.

The data scientist, as the name implies, provides the science part in the whole big data process. He must be rigorously trained and experienced, as his out-of-the-box critical thinking and problem-solving skills are crucial for the big data process. Any errors or deviation from the correct procedures can lead to false insight.

The Coder

Python and R are the most used programming languages for data science. If your operation is larger, you need many coders that are proficient in these languages that can program the requests of the data scientists.

For smaller operations, your data scientist may have enough coding capabilities so that he assumes both jobs and run simple scripts. However, if the operation is larger, these are two crucial jobs so that data is processed correctly.

The coder is the technical part of the staff, “the engineer” if you wish, and he is also essential to the team as any minor coding error may affect the validity of the results.

The Business Analyst

Even if the data is properly collected, prepared, processed, and analyzed, the results may still be of no actual use to the company. This is where the business analyst comes in. He presents to the decision-maker only those results that are useful insight.

A data scientist can interpret the data in a mathematical way, but does not usually know the business well enough to decide which result is of value to the company.

The business analyst’s job is to use the properly processed results after the data scientist has performed his duties. He is the final filter before the decision-maker acts.

The Decision-Maker

The decision-maker makes the final decision and acts upon that insight. It is self-evident that his role is crucial as he also manages the team itself most of the time.

Final Words

A team that works closely together and touches both the technical, the scientific, and the business side of big data can lead the decision-maker to game-changing decisions. In order to assemble a team wisely, you need to check for background experience, as well as results of their work and references from previous engagements.

So good luck and start scouting. If you need advice, Bigstep is here to guide you through this whole process.

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