The Future of Big Data: 5 Predictions from Experts for 2020-2025

Big data has been growing rapidly for a decade and shows no signs of slowing down. It is mostly internet-related, including social media, search queries, text messages, and media files. Another huge chunk of data is produced by Internet of Things (IoT) devices and sensors. These are the key drivers of the global data market growth, which has already reached $49 billion according to Statista. Everything in the world is now based on information, and this is pushing companies to seek out big data experts who can quickly collect data and apply complex processing . But will this continue, and what will the future of big data be? In this article, we present expert opinions and five predictions about the future of big data.

1. Big data will continue to grow in volume and migrate to the cloud

Most experts agree that the volume of data generated will grow exponentially in the future. IDC, in its Data Age 2025 report for Seagate, predicts that the global database will reach 175 zettabytes by 2025. For example, in 2013, 4.4 zettabytes of global data were produced.

What convinces experts of such rapid growth? Firstly, the growing number of Internet users who do everything online, users work on the Internet, conduct business correspondence, make purchases and use social networks.

Second, billions of connected devices and embedded systems that create and collect data every day around the world.

When companies gain the ability to store and analyze

massive amounts of data, they will be able to create and manage 60% of the world’s big data in the near future. However, internet users also play an important role. The same IDC report notes that 6 billion users, or 75% of the world’s population, will interact with online data every day by 2025. In other words, every connected user will interact with data every 18 seconds.

Such large data sets are difficult to manage in terms of storage and processing. Until recently, complex big data tasks were solved using open source ecosystems such as Hadoop and NoSQL. However, open source technologies require manual configuration and troubleshooting, which in turn can be difficult for most companies. Cloud storage has become the solution — companies have started migrating data to the cloud to be more flexible.

AWS, Microsoft Azure, and Google

Cloud Platform have transformed the way big data is stored and processed. Previously, when companies wanted to run data-intensive applications, they had to physically grow their own data centers. Now, with a pay-as-you-go model, cloud services provide flexibility, scalability, and ease of use.

This trend will continue in the 2020s, but with some adjustments:

1. Hybrid environment : Many companies cannot store sensitive information in the cloud, so they store a certain amount of data on local servers, and move the rest of the data to the public cloud.
2. Multi-cloud environment. Some companies prefer cloud infrastructure to cover special needs of their business, which allows to unite into a single integrated space the infrastructure deployed in-house and several public clouds.