Written by

Bernard Marr

Bernard Marr is a world-renowned futurist, influencer and thought leader in the fields of business and technology, with a passion for using technology for the good of humanity. He is a best-selling author of 20 books, writes a regular column for Forbes and advises and coaches many of the world’s best-known organisations. He has over 2 million social media followers, 1 million newsletter subscribers and was ranked by LinkedIn as one of the top 5 business influencers in the world and the No 1 influencer in the UK.

Bernard’s latest book is ‘Business Trends in Practice: The 25+ Trends That Are Redefining Organisations’

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What Is Real-Time Data Analytics (And Why It’s So Important)?

2 July 2021

If you want to compete in today’s digitally enabled world, you can no longer afford to ignore real-time analytics.

Companies across almost all industries are becoming more data-driven and learning how to turn their data into immediately actionable insight. Are you prepared for the real-time data analytics revolution?

Let’s talk about what real-time analytics is and why it’s so important to use the right information at the right time.

What Is Real-Time Data?

“Streaming data” or “real-time data” is dynamic data that is continuously generated from a variety of sources like sensors, cameras, social media feeds, and cameras. Examples of real-time data are e-commerce purchases, geo-location tracking, server activity, health data, website activity, weather events, and utility service usage.

When companies can process all that data as it’s coming in, they can near-instantaneously gain insight and understand exactly what’s going on with their customers or internal business processes – but data on its own doesn’t lead to business-building breakthroughs.

What Is Real-Time Data Analytics?

Real-time (streaming) analytics make sense of all the real-time data that flows into a company. When businesses can analyze data in real-time, they can generate insights while the data is in the stream, instead of storing and analyzing it in batches.

Traditionally, data analysis happens once the data has been captured and stored. Then any business insights are pushed out from storage. But real-time data analysis replaces that process, helping companies make more accurate decisions and take action significantly faster.

Why Is Real-Time Data Analytics Important?

Real-time analytics is a technique that analyzes data as it happens. It takes advantage of the fact that, for many applications, traditional batch analytics tools are actually working in the wrong direction – not just by analyzing data at a later time, but by actually waiting for data to arrive.

That data gap can cause lags in decision-making that can cost companies time, money, and energy.

Streaming data is almost always more profitable data. Companies know that most data has a short shelf life, so the faster they can turn information into insight, the more valuable all that data will be.

Wondering about the specific business benefits of streaming analytics? Companies can use real-time data analytics to:

  • Predict customer behaviors
  • Solve the technical problems associated with typical data batching processing
  • Scale faster
  • Make better business decisions
  • Act proactively to maximize customer satisfaction
  • Increase reaction time
  • Create more intelligent products and services
  • Improve and automate business processes

The Growing Importance of Real-Time Data Analytics

We are now living in a world where real-time and streaming data analytics are becoming increasingly important.

With the help of real-time data analytics, companies like Netflix have perfected the art of predicting their customers’ next favorite show….how will your company use the vast amount of available data to gain insight and make better business decisions?

Data Strategy Book | Bernard Marr

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