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Data Analytics, Big Data and Data Science

Why is now the right time to know about Data Analytics, Big Data and Data Science?

We officially live in a data-driven environment. Already taking the technology by storm, the data generation rate is even more than the human birth rate. With every next step, the world is moving towards a digital economy, and it wouldn’t be an exaggeration if we clinch that data will largely form our tomorrow.

If data storage, and generation are concepts still elusive to you, getting acquainted to them will help you subsist in the corporate sector for long.

Data Analytics, Big Data, and Data Science are the terms you may have come across yet failed to draw clear distinctions to. A clear understanding of these terms is essential if one opts to pursue a career in any of them, say experts at Jaro Education. With its ability to capsize the traditional methods of data storage, we need to know what comprises the blanket term of data technology today.

Questions arise regarding their underlying differences, and how great a career can each of them promise? Here’s all what you need to know:

Data Analytics:

The science of examining raw data, data analytics applies algorithms to derive insights. It supports the purpose of drawing conclusions from the information provided. Data is categorized, stored, and analyzed to study trends, and draw inferences accordingly.

  • Industries majorly using data analytics: Healthcare, travel, energy management and gaming
  • Skills requirement: Programming skills, statistical skills, mathematics, data wrangling skills, machine learning skills and data intuition
  • Data analyst aggregate salary: $60,476, annually

Data Science:

Data science is commonly deemed as the future of Artificial Intelligence. It is predicted that by 2020, more than 80 % of the data will be unstructured. Therefore, in order to process, cleanse, analyze and draw meaningful insights from both unstructured, and structured data, data scientists are highly sought after in the industry.

  • Industries majorly using data science: Internet searches, digital advertisements and search recommendations
  • Skills requirement: SAS and/or R language in-depth knowledge, python coding, Hadoop platform, SQL database/coding and experience in handling unstructured data
  • Data Scientist aggregate salary: $113,436, annually

Big Data:

When traditional means cannot handle the extensive amounts of data from large sources, big data comes into mainframe. Aggregating data from distinct resources, it allows better decision making, and process automation.

  • Industries majorly using big data- Retail, communication and financial services
  • Skills requirement: Analytical skills, creativity, mathematics, statistical skills, computer science and business skills
  • Big data specialist aggregate salary: $62,066, annually

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