Data and Value are interwoven. Data is a gold mine today due to the value derived from it.
The concept of big data has evolved over the years; most organizations now understand the business of analysing data from different streams so they can apply analytics and get significant value from it. In the early 1950s, decades before anyone uttered the term “big data,” businesses were using basic analytics for manual examination to expose insights and trends.
According to SAS, big data analytics brings to the table, speed and efficiency. Whereas a few years ago a business would have gathered information, run analytics and unearthed information that could be used for future decisions, today that business can identify insights for immediate decisions. The ability to work faster – and stay agile – gives organizations a competitive edge they didn’t have before.
Hence, the continuous need for Data Analysts in competitive industries.
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.
- Cost reduction. Big data technologies such as Hadoop and cloud-based analytics bring significant cost advantages when it comes to storing large amounts of data – plus they can identify more efficient ways of doing business.
- Faster, better decision making. With the speed of Hadoop and in-memory analytics, combined with the ability to analyze new sources of data, businesses are able to analyze information immediately – and make decisions based on what they’ve learned.
- New products and services. With the ability to gauge customer needs and satisfaction through analytics comes the power to give customers what they want. Davenport points out that with big data analytics, more companies are creating new products to meet customers’ needs.
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