- Digital transformation will change the big data landscape
With the adoption of online work or working from home, thanks to the COVID-19, digital transformation will drive the adoption of big data and analytics more than ever. The rise in online work will leave a larger trail of data than ever witnessed, forcing organizations to adopt a way of storing and analyzing it. As IaaS providers continue building data centres and receiving more users of their services, the amount of data will rise, and the need for big data solutions will be on a surge. The advancement of the Internet of Things (IoT), machine learning and artificial intelligence (AI) also calls for more data for algorithms. As we head to a new decade characterized by these three technologies, it remains to be seen how big data will improve things.
- Humans will continue playing a crucial role
Although artificial intelligence will play a bigger role in big data analytics, humans will remain important. According to Gartner, smarter and more responsible, AI will enable learning algorithms, shorter time value and interpretable systems. This means better days for big data and analytics. While AI will take over some areas that humans used to occupy, the latter will continue playing a critical role. Organizations will still require analytics tools to empower people to spot anomalies efficiently.
- Big data will help fight climate change
Climate change is now a leading threat to humanity, and its impacts can be seen worldwide. As such, agencies and intergovernmental bodies such as the United Nations Intergovernmental Panel on Climate Change (IPCC) are exploring all possible means to fight the menace. Big data will be crucial in this fight because it will show interesting insights about what is going on with the climate. With the help of machine learning, big data analytics will allow these organizations to learn patterns and changes that have occurred over time. With its potential to sift through large piles of data, machine learning will also be a critical component. Data from disparate sources will be collected and analyzed in one location to help make better decisions.
- Real-time analytics will gain more traction
Sports has proven to be the leading consumer of real-time analytics. An example is a scintillating clash between Roger Federer and Novak Djokovich in 2019, where live feed statistics related to the game proved the importance of real-time analytics in different areas. As many aspects of sports become digitized, data analytics will be important for fans who will not rely on the sometimes false information fed to them by the live commentators. This will be interesting to both the fans and players who will use the performance statistics to find areas where they need to improve.
- Predictive analytics will grow
Predictive analytics has proven useful for organizations that would want to know what the future holds for them. The growth in the adoption of this technology will continue as companies seek to forecast potential future trends. With the uncertainty brought about by the pandemic, the use of predictive analytics will increase as companies want to know how the future will look like.