Big data analytics trends in 2022 – ResearchFox

In recent years, big data analytics has grown from a modest murmur to a roar. The big data analytics industry is expected to reach $103 billion by 2023, according to Wikibon statistics. Artificial intelligence, machine learning, and natural language processing are just a few of the technologies that have emerged because of the practical use of data science in numerous sectors. As more companies embrace data analytics to lower costs, enhance customer experience, and optimize current processes, this field is going to dominate in the years to come. ResearchFox has identified a few big data analytics trends to watch in 2022:

Human to drive AI Evolution:

Organizations that employ AI for data analytics have a better probability of success than those that don’t. However, one of the most significant barriers to AI adoption was the fear of job loss. People were fearful of losing their job and being replaced by robots because of technological advancements. While their worries were not entirely unwarranted because computers can work quicker, remove mistakes, and be more efficient, the actual promise of AI will only be realized when humans and machines work together. As AI evolves into more complex and accurate algorithms, human responsibilities are increasing its importance. This indicates that human engagement in processes is going to shift from a more boring, repetitive activity to a strategic role. Humans will be required to determine the best approach to scale current technology, while machines will do rote tasks.

Growing Cloud-based solutions:

Cloud-based technologies have become the mainstream, and this trend is continuing to grow. Several companies are preferring cloud-native analytics solutions to gain a competitive edge with streamlined analytics and business intelligence. As leading enterprises and small and medium enterprises have gone remote due to the onslaught of the pandemic, more cloud-based technologies have facilitated the shift, and helped companies to save costs associated with legacy tools and bottlenecks.

Growing BI Budget:

With all the foregoing projections, one thing is certain many firms are boosting their BI/big data budgets by up to 50%. This is especially happening in the retail, financial services, and technological sectors. Big data analytics in the retail industry produced $4.85 billion in 2020, according to Allied Market Research, and this figure is expected to rise to $25.56 billion by 2028.

Predictive Analytics:

By 2026, the global predictive analytics market is expected to reach $28.1 billion. Business intelligence and big data combine to form predictive analytics. Many businesses currently utilizing predictive analytics to improve their operations by implementing machine learning/artificial intelligence algorithms, data mining, and predictive marketing. The conventional approach has been transformed into a more contemporary, integrated approach thanks to digital transformation tools. As a result of the growing use of the internet, cloud technologies, and linked systems, businesses are compelled to invest more in predictive analytics.

Adoption of Business Intelligence Tools:

In 2022 and beyond, industries such as manufacturing, business services, consumer services, and retail are going to boost their use of business intelligence tools and technology. This is because these tools transform the way businesses approach data analytics. Business intelligence tools make big data more available to use as they decrease the level of computation and expertise required to interpret the data. Even if the users are not from the IT or data mining background, they can still execute the 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.

Data Universe:

Organizations 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 a quick and agile way to convert the growing volumes of data into insights and actions. With a central repository of structured and unstructured data, businesses are harnessing 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 soon.

Final Words

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

At ResearchFox, we take pleasure in anticipating industry changes and meeting our clients’ demands ahead of the curve. As a result, we can supply our clients with effective and result-oriented solutions while also considering the future of technological progress. These systems are fully adaptable to both existing and emerging green technology.

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