DATA SCIENCE vs. DATA ANALYTICS vs. BIG DATA

There’s no denying that data has become one of the most asset of every organization today- and this is the reason why data science professionals are looking to attain data science certifications- because every company wants to make the most of data that it’s been collecting for years.

With the inception of digital technology and economy, a few opportunities have opened for data science professionals in the data science careers space. From data analysts to data scientists and data visualizer, every role in the data science career plays a primary part- and therefore data science careers are gaining importance every day.

Ranging from data analytics, data engineering, data mining and data analytics, every function of data science work on a single platform but perform different jobs are performed. However, if you are looking for a data science career as a data science professional, then data science certifications will add a surefire advantage in your portfolio!

Data Science, Big data and data analytics- what do these terms mean?

There is a common misconception that data science, data analytics and big data are same. But these terms are just interconnected to each other. There are many data science certifications available in the market today focusing on data scientist qualifications and aspiring data science professionals as well. One looking for guidance to enter data science space can step into an exciting world of data science certifications to learn everything from scratch.

While big data refers to data deluge coming in various types viz. semi-structured, unstructured and structured data. Big data is generated through several digital channels including internet, social media, e-commerce websites and mobile among others and has impacted numerous sectors in today’s scenario.

On the other hand, data science refers to the dicing and slicing of the myriad chunks of data as well as identifying insightful trends and patterns by leveraging this technology. Technical experts with data scientist qualifications have become an imperative part of every organization today as every company is on the lookout to invest in advanced analytics tools and techniques to unlock the maximum potential of data they have been gathering for years.

Whereas, data analytics offers operational insights to execute into the complex business functions and strategies. Per Forbes, Hadoop market and big data analytics are going to earn more than $95bn by 2022- which says a lot about constantly emerging data science field and need of data scientist qualifications in the employees.

With the rising demand of advanced tools and techniques, specialists with data scientist qualifications are also on the high demand. However, if you’re a budding data scientist looking to get a role in data science space, there are certain skillsets that you need to focus on-

· Analytical Skills

· Statistics

· Hadoop

· Java

· Statistical language skills

· SQL Database

· Mathematics and Statistics

· Artificial Engineering among many others.

To become a data scientist or work in similar space, in addition to all these competencies, you will also be required to have good communication skills. With all the information provided above, we hope there won’t be any problem to decide which career option to go for!