Big Data Analytics

Jan 10, 2023

What it is and why it matters?

Big data analytics examines large amounts of data to uncover hidden patterns, correlations and other insights. With today’s technology, it’s possible to analyze your data and get answers from it almost immediately – an effort that’s slower and less efficient with more traditional business intelligence solutions.



History and evolution of big data analytics

The concept of big data has been around for years; most organizations now understand that if they capture all the data that streams into their businesses (potentially in real time), they can apply analytics and get significant value from it. This is particularly true when using sophisticated techniques like artificial intelligence. But even in the 1950s, decades before anyone uttered the term “big data,” businesses were using basic analytics (essentially, numbers in a spreadsheet that were manually examined) to uncover insights and trends.

Some of the best benefits of big data analytics are speed and efficiency. Just a few years ago, businesses gathered information, ran analytics and unearthed information that could be used for future decisions. Today, businesses can collect data in real time and analyze big data to make immediate, better-informed decisions. The ability to work faster – and stay agile – gives organizations a competitive edge they didn’t have before.



Why is big data analytics important?

Big data analytics helps organizations harness their data and use it to identify new opportunities. That, in turn, leads to smarter business moves, more efficient operations, higher profits and happier customers. Businesses that use big data with advanced analytics gain value in many ways, such as:

  1. Reducing cost.Big data technologies like cloud-based analytics can significantly reduce costs when it comes to storing large amounts of data (for example, a data lake). Plus, big data analytics helps organizations find more efficient ways of doing business.
  2. Making faster, better decisions.The speed of in-memory analytics – combined with the ability to analyze new sources of data, such as streaming data from IoT – helps businesses analyze information immediately and make fast, informed decisions.
  3. Developing and marketing new products and services.Being able to gauge customer needs and customer satisfaction through analytics empowers businesses to give customers what they want, when they want it. With big data analytics, more companies have an opportunity to develop innovative new products to meet customers’ changing needs.


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