Gartner Report: Top data and analytics trends for 2021
As the world reluctantly expands, data and analytics growth is expected to continue into the current year.
By having a deeper view of the market, data and analytics assist companies in being ahead of its competitors. Without data analytics, it’s fair to say that many enterprises will go deaf and blind. Companies and organizations have begun to use this cutting-edge technology to expand their operations. As a result, some analysts claim that by 2024, a 5-fold rise in data analytics infrastructure will be feasible.
According to Gartner, “Gartner, Inc. identified the top 10 data and analytics (D&A) technology trends for 2021 that can help organizations respond to change, uncertainty and the opportunities they bring in the next year. “The speed at which the COVID-19 pandemic disrupted organizations has forced D&A leaders to have tools and processes in place to identify key technology trends and prioritize those with the biggest potential impact on their competitive advantage,” said Rita Sallam, distinguished research vice president at Gartner.
D&A leaders should use the following 10 trends as mission-critical investments that accelerate their capabilities to anticipate, shift and respond.”
Here are some of the Gartner’s top data and analytics trends for 2021:
Smarter, faster, and more scalable AI
According to Gartner, by the end of 2024, 75% of companies will have moved from piloting to incorporating AI, resulting in a 5 times increase in streaming data and analytics facilities. Present methods are fraught with difficulties. Models based on vast quantities of historical data that were once accurate could no longer be relevant.
However, AI revolutions will allow new learning algorithms like reinforcement learning, interpretable learning like explainable AI, and powerful infrastructures like edge computing and new types of chips.
Another trend that has arisen during the pandemic is decision intelligence, a field of AI that offers a structure for best practices for designing, modelling, implementing, and tracking decision procedures and frameworks.
By 2023, over a third of large organizations, according to Gartner, will rely on analysts to provide decision intelligence, such as decision modelling.
Augmented Data Management
To simplify and develop processes, augmented data management employs machine learning and artificial intelligence (AI). It also transforms metadata from auditing, background, and reporting into a source of power for complex systems.
Wide samples of operational data, such as actual requests, output data, and schemas, may be analyzed by augmented data management products. An augmented system can modify operations and optimize configuration, protection, and productivity using existing use and workload data.
X analytics describes a variety of structured and unstructured data, such as text, video, and audio analytics, in which the data variable is represented by the letter ‘X.’
X analytics, when combined with AI and other automated techniques, can play a crucial role in developing strategies for future emergencies and natural disasters by allowing for detection and prediction.
Cloud is a given
Public cloud platforms will be needed for 90% of data and analytics innovation by 2022. As data and analytics migrate to the cloud, data and analytics practitioners struggle to cope to match the right resources to the right use cases, resulting in needless governance and deployment overhead.
In the case of data and analytics, the question is no longer how much a service costs, but rather how well it can meet the workload’s performance criteria beyond the list price. When transitioning to the cloud, data and analytics leaders can prioritize workloads that can benefit from cloud technologies and concentrate on cost optimization.