7 Key Members of Every Big Data Team Posted on : Feb 17 - 2018

Now that the age of Big Data is upon us, businesses all over the world use information collected by analyzing data to make important strategic decisions, allowing them to spot opportunities to gain an advantage over the competition they would have otherwise missed. If you want to take full advantage of what Big Data can offer your business, having a team of highly skilled professionals with diverse skills is essential.

In the last few years, highly distinct roles have emerged among those who work with Big Data. While all of those team members work towards the same objectives, the way they each do it will be different. Here is an overview of the seven main members you’ll need to put together a successful and highly efficient Big Data team.

1. Software Engineers

Software engineers play a key role in your Big Data team by creating the software that allows you to collect the actual data. They work to put together both the back and front end of systems responsible for collecting and processing data. While applications running on desktop PCs are still highly popular in some industries, most software being developed now is made to run on mobile devices or in a web browser.

Software engineers are able to use their knowledge and experience to not only create the software applications themselves, but also provide valuable advice on how your company chooses technology and how it implements these choices.

2. Statisticians

Statisticians keep your Big Data team running by using math to collect, analyze and interpret the data other team members have acquired during the course of their duty. They’re also very good at determining which method to use to collect data for a specific purpose.

Statisticians commonly use programming languages like Stata and Perl, although it’s common for them to be familiar with other ones as well. Their contributions are especially valuable if your company needs to collect data through methods like surveys, field experiments and focus groups.

3. Data Hygienists

When dealing with Big Data, it’s rare that all of the information contained in a data set is accurate, relevant and useful. For this reason, your team will need someone to “clean” the data and refine it, ensuring that it’s suitable for use during its entire lifecycle. For example, a data hygienist could look over the data set to ensure that values denoting time or currency are all logged in same manner.

They can make adjustments manually or use a variety of software tools to automate part of the process. By making sure your data is stored and presented in a uniform manner, data hygienists help prevent errors that can cause serious problems further in the data’s lifecycle. View More