Top six big data analytics trends to expect in 2022

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Big data analytics is that quiet murmur that has turned into an uproar in the past few years. According to Wikibon statistics, the big data analytics market will reach $103 billion by 2023. The practical application of data science in various industries has given rise to technologies such as artificial intelligence, machine learning, and natural language processing, which are rapidly changing the way we work.

As more companies embrace data analytics to lower costs, enhance customer experience, and optimise current processes, this field will dominate in the years to come. Here’s a quick rundown of the top six big data analytics trends to expect in 2022.

Predictive Analytics

The global predictive analytics market is set to reach $28.1 billion by the end of 2026. Predictive analytics is the practical result of business intelligence, and big data. Many companies already use predictive analytics for applying machine learning/artificial intelligence algorithms, and conducting data mining and predictive marketing to optimise their processes. These digital transformation technologies have altered the legacy approach into a more modern, integrated approach. Thus, rising internet proliferation, cloud technologies, and connected systems will compel businesses to invest in predictive analytics.

Humans to Drive AI Evolution

Enterprises that use AI for data analytics have higher chances of succeeding than their counterparts that don’t. However, one of the biggest impediments in adopting AI was the fear of job loss. People looked at technology with the paranoia of losing their jobs and being replaced by bots. While their fears weren’t necessarily unfounded because machines can work faster, eliminate errors, and are more efficient, the true potential of AI can only be unleashed when machines and humans coexist.

That is why human roles will be crucial to evolve AI into more sophisticated, accurate algorithms. This means that human involvement in processes will pivot to a strategic role from more mundane, repetitive work. Humans will still be needed to decide the best way to scale existing technologies, while machines will take over rote work.

Higher Adoption of Business Intelligence Tools

Industries, including manufacturing, business services, consumer services, and retail, will increase the adoption of business intelligence tools and technologies in 2022 and beyond. This is because these tools transform the way organisations approach data analytics.

Business intelligence tools make big data more available for use as they decrease the level of computation and expertise required to interpret data. Even if users are not from the IT or data mining background, they can still execute analytical functions such as exploring data sets or performing data-mining tasks. The only prerequisite required is to know how best to use these tools.

Growing Cloud-Based Solutions

As leading enterprises and small and medium enterprises go remote due to the onslaught of the pandemic, more cloud-based technologies are facilitating this shift, and helping companies save costs associated with legacy tools and bottlenecks.

Cloud-based technologies have become mainstream and this trend will continue. Several companies will prefer cloud-native analytics solutions to gain a competitive edge with streamlined analytics and business intelligence.

Growing BI Budget

With all the predictions mentioned earlier, one thing is clear: many businesses will increase their BI/big data budget by as much as 50 percent. This is particularly true for the retail, financial services, and technology sectors. According to Allied Market Research, big data analytics worldwide in the retail sector generated $4.85 billion in 2020, and this number is projected to increase to $25.56 billion by 2028.

Welcome Data Universe

Organisations today are dealing with a humongous amount of data, which has given rise to the data universe. The data universe comprises data management architectures such as data fabric, data lakehouse, and data mesh. These architectures are touchstone examples of how industries are finding quick and agile ways to convert the growing volumes of data into insights and actions. With a central repository of structured and unstructured data, businesses can harness more data, from more touchpoints, in relatively lesser time while fostering collaboration among teams. They are the next-gen of data infrastructure that is set to make data warehouses obsolete in the near future.

Embracing change is the only way for businesses to flourish in the future, remain competitive, and grow in this rapidly changing technological landscape.

Naren Vijay is Executive Vice President, Lumenore.

Views are personal and do not represent the stand of this publication.