Five skills needed to work in big data

March 21, 2018

As in most technical fields, a degree and experience are beneficial for career growth in data analytics.

A fundamental knowledge of technology, programming, and statistics is necessary for someone to succeed in this field, but an understanding of business and people skills is also important.

Rachel Coleman, MS, faculty in Capella University’s School of Business and Technology, shares five skills she recommends data analytics professionals have to help them succeed.

1. Business background

“Understanding basic business principles is essential to providing meaningful and applicable analytical services,” Coleman says. Data analysts can draw on both their understanding of business concepts and their industry-specific knowledge to present data that drives an enterprise forward.

2. Communication

“Soft skills,” specifically related to communication, are valuable in data analytics. “A good analytics professional will need to be able to clearly communicate analysis, results, and recommendations to technical and non-technical audiences at various levels of an organization,” says Coleman.

New to the field? Take a Deep Dive into Data Analytics.

3. Technical know-how

It’s important for an analytics professional to have skills in sourcing and processing data using the latest tools. A solid understanding of data structures and data architecture is also needed. According to Coleman, “Data analysts should have expertise in programming languages such as Java, SAS, R, Python, and Hadoop.”

4. Statistical knowledge

An understanding of applied statistical modeling and data mining techniques will be important to providing predictive and classification models. “Applying statistics to algorithms within big data allows for variation to be accounted for when making assumptions about the data,” says Coleman. Sampling, hypothesis testing, and predictive models are all forms of statistical analysis that can be applied to big data. Techniques such as clustering, bootstrapping, multivariate analysis, time series analysis, and many others are used in data analysis. Statistics can help transform data into knowledge.

5. Innovative outlook

Analytics is a creative field. It requires professionals who can leverage vast amounts of data to provide useful information for solving real-world problems. The discovery of new data streams continues to grow at a rapid pace. Therefore, innovative ways to process this big data will be needed. The use of big data will become a key basis of competition and growth for most businesses. Innovators in this field will be in high demand.

“Data scientists or big data professionals will be hired by industries that consume a vast amount of data,” says Coleman. “These types of industries will have a need for analytics within cloud computing, analysis of sensory data, customer insights, consumer and market research, digital analytics, and customer profiling, just to name a few. Analysts who can demonstrate these five skills will be well positioned to succeed in the field.”

Capella offers the following certificate, bachelor’s, master’s, and doctoral degree programs in data and analytics:

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