There has been a rapid improvement in the field of Big Data. This is because of the significance of data in business processes. The beauty with technology is that it is constantly evolving for the better.

A business that is concerned about remaining relevant in the 21st Century should be adaptable and abreast of what is happening. Big Data can enhance and improve the decision-making process in an organization. There were some bold predictions that were made a couple of years that are yet to come true. You might be wondering what 2020 has in store for Big Data. Here are some predictions you should know about as we approach the New Year.

Real-Time Analytics

In the past, organizations depended on information generated in a week before making a decision. As technology improves, businesses will be able to process information in real-time. The attention will be diverted to live streaming technologies to support business processes. You don’t have to wait for a day in order to make an important decision. Information is accessed as soon as it becomes available. This was not possible just a few years ago.

The potential for live data streaming extends beyond companies that are tech-related. The technology can come in handy in the field of Machine Learning and Artificial Intelligence. There is a constant update with a stream of data that allows for real-time functionalities. It is predicted that the expenditure on real-time analytics is expected to increase by four times in 2020.

Innovative Revenue

Data is crucial for decision making in any organization. Companies are willing to pay for information as long as it is relevant and will aid with the decision making process. Businesses are able to make critical decisions for the future enterprise. That is why it is predicted that that data management companies are expected to gain from the paradigm shift in demand for data. It is predicted that close to 90% of large enterprises will be making money from offering data as a service. This doesn’t mean that such organizations haven’t been generating revenue by offering data as a service. The only difference is there is bound to be an increase in revenue.

Access to Data Anywhere and Anytime

There have been an increase in data sets and real-time access is crucial. Organizations will want to reduce costs and improve efficiency. Experts predict that there will be an increase in spending on Big Data via the cloud. There is a desire for more cloud-based solutions to improve accessibility. This will also reduce costs and promote wide availability of data.

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Digital Maturity

Artificial intelligence has the potential of changing how we perceive and interact with technology. Such systems will require a constant stream for them to be functional. The success of artificial intelligence has partly been made possible because of Big Data. It could be a system that completely relies on GeocodeAPI for it to function. Without the data, such a system won’t be functional.

Technical Morals

A lot of companies have come under fire because of improper management of personal data. Facebook was recently fined heavily because of the privacy breach which allowed for political manipulation. Stakeholders have recognized the challenges that come with managing Big Data. One such challenge is security and keeping personal information private. For a business, you’re supposed to be the custodian of your customers’ information. There is bound to be stricter guidelines when it comes to collecting and managing data.

Data Scientists Becoming a Necessity

It is predicted that the majority of big corporations will have the role of Chief Data Officer (CDO). Companies that are technology-based have already invested in artificial intelligence in one way or another. It makes sense to have someone at the helm to provide the needed leadership when it comes to managing Big Data. There are some organizations that might already have a department to oversee Big Data in the company.

Clean Data

One of the challenges with scraping is getting clean data that is useful. It doesn’t matter if it is structured or unstructured. A data scientist will spend more than 60% of their time cleaning and making data presentable. There are newer and better algorithms being developed to help with cleaning data. It is predicted that quick and efficient systems for cleaning of data will become available among data scientists in 2020.

To conclude, it will not be possible to predict every major moment in the field of Big Data. Technology is disruptive and it won’t come as a surprise when you see rapid changes in the industry in 2020.