The 7 data trends that you did not expect would mark this decade: Predictive analysis, DataOps, Blockchain, Machine Learning… We will discover them for you!
The presence of data in every field you can think of is what turns out to be one reason why organizations are showing interest in data science. Also, the fact that data will remain an integral part of our lives into eternity serves to be another driver of data science.
That said, it is essential to keep up with the hottest trends in data science that could serve to be a boon to growing your business. Here are the top 10 data science trends for this decade.
1. Predictive analytics
For a company to prosper, knowing what the future may look like is essential. This is precisely where predictive analytics comes into play. Organizations rely heavily on their customers. Therefore, understanding their behaviours helps to make better decisions in the future. This technique is one of the most innovative ways to develop the best customer targeting strategies that will help retain older ones and get new ones.
2. Machine learning
Over the years, we have seen how automation has transformed the world. This is why machine learning has gained in importance like never before. In the coming years, there will be more automation, and therefore the increase in the number of organizations adopting machine learning will surely exceed the imagination.
Gone are the days when IoT was considered something that had limited applications. Nowadays, we live in a world where our smartphones can control appliances like TV, air conditioner, etc. All this is possible thanks to IoT. Google Assistant is another notable innovation in the IoT area. Therefore, companies looking to invest in this technology are not much of a surprise. This sheds light on how quickly the IoT industry will grow in the coming days.
Cryptocurrencies like Bitcoin, Litecoin, etc. They have become the talk of the world. All of these coins employ blockchain technology. Since the world is showing great interest in this field, its application will have a broad reach in the future.
5. Edge computing
Edge Computing is known for processing information faster and reducing latency, cost, and traffic. Organizations are not willing to give up this option for these characteristics alone. With this computing, the treatment of applications in real-time could not be better. There could be a significant shift from traditional methods to edge computing in the coming years.
Let’s face reality: the data pipeline has become more complex and therefore requires even more integration and governance tools. Well, DataOps is to the rescue! All tasks are covered, from collection to preparation and analysis, test automation, automated test implementation, and delivery to provide higher quality data and analytics. This trend will continue in the coming years.
7. Artificial intelligence
Whether it’s a small business or a tech giant, all of them have relied on AI in one way or another. All those complex tasks are no longer a concern because now we can rely on AI for them. Furthermore, reducing errors is another compelling reason why AI stands out. Now that we’ve relied so much on AI, there’s no going back!