For decades, data management mainly meant gathering, storing, and occasionally accessing it. That has all changed in recent years, as companies seek essential information from the enormous amounts of data being generated, accessed, and stored in various locations, ranging from corporate data centers to the cloud and the edge. As a result, data analytics has become a must-have skill, aided by modern technologies such as artificial intelligence (AI) and machine learning, and its importance will grow in 2022.
Let’s take a look at four key big data analytics trends for 2022.
Artificial intelligence (AI) and machine learning (ML) are two more trending technologies that will dominate the big data and analytics landscape in 2022. According to a press release by Gartner, AI will be integrated into roughly 60% of big data and analytics systems by 2022. This AI integration will help to automate and improve decision-making processes, as well as improve data analysis accuracy. AI will assist enterprises in more successfully analyzing massive data sets and uncovering patterns and insights that might otherwise go unnoticed.
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AI and machine learning will help firms in a variety of fields, such as finance, healthcare, marketing, and so on, enhance their performance to a large extent by boosting efficiency and profitability while lowering costs.
According to a recent Facts and Factors report, the global predictive analytics industry is expected to reach USD 22.1 billion by 2026.
Predictive analytics is a valuable application of big data and business intelligence (BI). Various big data analytics elements are being successfully used by several organizations to foresee potential future trends.
Business intelligence (BI) tools have become more widely used in recent years across a variety of industries, including consumer services, manufacturing, technology, and business services. It will do so in the following years as well. According to the latest survey by Beroe, Inc., the worldwide BI industry is anticipated to reach USD 30.9 billion by 2022. Big data analytics, demand for data-as-a-service, and self-service BI capabilities are the main drivers of this movement.
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Despite the fact that there are numerous big-data analytic tools on the market, the challenge of massive data processing capabilities persists. Quantum computing arose as a result of this. The use of quantum mechanics in computation has expedited the processing of massive volumes of data. It also improves security and privacy. Since the quantum bits of the Sycamore processor, which can solve a problem in 200 seconds, are employed to make these decisions, it is more efficient than traditional computing.
Edge computing is still in its infancy, and it will take a lot more tuning before it can be adopted by businesses. Because of the rapid market trend, it will become a component of every corporate operation.
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Umme Sutarwala is a Global News Correspondent with OnDot Media. She is a media graduate with 2+ years of experience in content creation and management. Previously, she has worked with MNCs in the E-commerce and Finance domain
