big data in mobile app dev

We all know how Big Data is being used to improve business practices, predict user behaviors and boost decision-making processes; however, it might come as some surprise that mining and interpreting large scale data is now also helping to shape and enhance some of the world’s biggest and most popular mobile applications and processes. 

Examples of how Big Data changes sectors – particularly security and banking

Data has been used across the banking and IT security sectors for many years to help predict and prevent security breaches, including:

  • Monitoring activity in the financial markets
  • Predictive analysis
  • Network analytics to catch illegal traders
  • Credit card fraud detection
  • Identifying and preventing money-laundering activities
  • So-called Know Your Customer technologies

By studying and interpreting Big Data from several sources, security specialists have been able to improve their understanding of high-risk sectors and write Artificial Intelligence (AI) systems capable of identifying suspect behavior. 

Big Data gives developers greater insights into users, and user behavior and variations of this same tech are now filtering their way down into the most common apps we use every day on our handheld devices. 

Entertainment, media, and communications software – our most popular apps 

In today’s uber-connected world, it’s somewhat inevitable that we all have our go-to apps that we use daily to stay in touch with friends and family or catch up on their latest news. Apps like Facebook, Instagram, Twitter, and WhatsApp have become such a staple part of everyday life that it’s almost impossible to imagine a time without them. 

Couple that with the massive user base of perennial favorites like streaming media apps such as Spotify, Netflix, and YouTube, and it’s easy to see just how much data these respective companies can gather about their users – and make no mistake, gather they do. Let’s just look at YouTube as one single example among many:

  • YouTube attracts a staggering 122 million active users every day
  • The platform reports equally bewildering figures for the amount of content streamed daily – currently, 1 billion hours of video are watched around the world per day
  • Every minute of every day, 500 hours of new content is uploaded to the YouTube servers

With so much digital activity and insight to their users, it’s perhaps inevitable that these titans of social media, communications, and streaming content are coming to rely heavily on Big Data to improve their services and, in turn, stay top of the tree compared to their rivals. From the biggest players right down to independent apps production firms like Make IT Simple, app developers are coming to rely on user data to dictate the direction of their services. 

Examples of where Big Data is being used in our most popular apps include:

  • Serving bespoke content aimed precisely at different user groups
  • Monitoring, measuring, and interpreting the respective performance of different types of content
  • Making intuitive recommendations based upon previous interactions or viewing habits

If you remain in any doubt about how Big Data can be used to power apps and content provision, just think of the way Spotify seemingly knows what new music might interest you – or how Amazon’s Prime service somehow seems to hit the nail on the head each time with books, shows or music you might like. This same capturing and interpreting of data happens across the board in all your most-used apps – from Facebook to Netflix, Twitter to LinkedIn.