Data Science vs. Big Data vs. Data Analytics

Are you looking to invest in a data career but you’re confused where and how to start over? Undeniably, data is already ruling the world and it is present everywhere. At present, we all are facing unprecedented growth with tons of data generated every millisecond resulting in the concept of big data.

We’re all living in an era that is filled with data, it is everywhere. Today, data is one of the biggest assets of an organization. Although, the prediction was earlier (2015) made by Forbes stating that “The total Data market is expected to nearly double in size, growing from $69.6B in revenue in 2015 to $132.3B in 2020.” And with the rise of the digital economy, the various landscape has opened to the big data world.

Data science, big data and data analytics all work under the same platform, however, all perform differently. Most candidates often get confused with the terms surrounded by data. Data science broadly covers topics such as mathematics, statistics, data mining, machine learning, and data analytics that explains how analyzing big data takes place.

Let us see what these terms mean:

Data Science

Data science involves processing, cleaning and analyzing large volumes of data, this data can be structured or unstructured. It is said that almost 90% of data scientist spend their time cleaning the data. The skills involved mathematics, statistics, machine learning, programming in R and Python, problem-solving skills, intuitively capturing data, and prediction of the company’s business can be forecast based on the data. In short, data science is a broader term used for the techniques that are involved in bringing in positive insights and information from the data collected.

With an exponential rise in the technology demand data science certifications is the next big thing for an IT professional to master. Data science skills should be your top priority to upgrade. As the demand for a data science professional upsurge, data science certifications can prepare for the jobs of future.

Big Data

“Big data is high-volume, and high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation,” says Gartner.

Data Analytics

The techniques used to derive meaningful information including conclusions from the already existing data is called data analytics. A combination of the mechanical and algorithm process is being followed to extract insights from raw data.

Several organizations have included big data in the product development to ensure that they are able to take up an effective decision. In simple terms, data analytics is a process that allows the use of effective patterns and technologies for the data that is recorded using machine learning techniques, predictive modeling, mathematics, and statistics.

Since big data is being used in almost all the industry today, organizations are cherry picking candidates skilled in new age technologies. Certified Big data professionals will be chosen over professionals without any credentials or certifications.

With competition at a rapid pace, it is never too late to upskill and upgrade one’s skills. Moreover, employers, these days are skeptical about the expertise, thus, demonstrating it through credible certification can be helpful.