Big data analytics trends to watch out for in 2020

According to industry analyst Doug Laney, big data has grown exponentially in recent years in terms of volume, velocity and variety. As a result, new technology has caused trends in big data. Throughout this article, we explore some of the upcoming trends in big data analyticsfor 2020.

Top data analytics trends in 2020

In-memory computing

Although in-memory computing was relevant in 2019, this technology is expected to be used more widely in the new decade due to reduced costs in the technology. In-memory computing means storing your data in RAM (random-access memory) and processing in parallel. In short, you can run tasks in multiple computers at the same time which reduces processing time.

IMC can be helpful for organizations who need to analyze huge volumes of customer data as it will help them to save time and resources.

IoT merger with data analytics

The Internet of Things (IoT) is a collaboration of electronic devices that all communicate with one another. This is an amazing technological innovation that has increased global connectivity by securing all digital machines to a single network.

The benefits of merging the IoT technology with data analytics tools, especially in businesses delivering digital products and services, will be a reduction in operating times and costs. With different tools connected to a single network, the chance of manual errors in replicating or transferring data will also be reduced.

Automated data analytics

Data analysis will soon be performed with very little or no human intervention. 2020 will bare witness to many businesses automating their business operations which will result in faster and more efficient data analytics.

Machine learning in data analytics

The progress made in the field of machine learning has resulted in a large-scale integration of it into data analytics. According to Gartner.com, more than 40% of big data analysis across industries is supposed to be enhanced through machine learning techniques. Machine learning can expedite the data analysis process and increase a business’s efficiency.

Augmented analytics

Augmented analytics is one of the major sectors of data analytics and combines machine learning and AI techniques to transform the way data is developed, processed and analyzed. Hence, Analyticsinsight.net predicts augmented analysis market will grow from $ 4.8 billion in 2018 to $18.4 billion by 2020, at a rate of 30.6% per annum. The major factors driving this growth are the increase in the volume of business data and the growing demand for crucial business insights from customer data.

Conversational analytics and Natural Language Processing

Another trend expected to take over in 2020 is the use of voice or Natural Language Processing (NLP) in generating analytical insights. NLP can simplify complex analytical platforms for general use and easily analyze complex data combinations. It can also be used for predictive analytics, automating business processes and customer services.

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