3. Analytics for decision making. By 2023, Gartner predicts, one-third of large companies and corporations will have analysts specializing in decision intelligence on their staff. The mathematical foundation for designing, modeling, coordinating, executing decisions, as well as methods for tracking and adjusting decision models in the context of business results, are already being created today. They will be used in complex adaptive systems that combine traditional rule-based analysis methods with advanced methods such as AI and machine learning. This allows users who do not have deep technical knowledge to change the logic of decision making without involving programmers.
4. X-analytics: X-analytics is a term coined by Gartner as an umbrella term for different types of content, structured and unstructured, pulled from different sources. During the pandemic, AI and X-analytics have played a critical role in mining thousands of scientific articles, news sources, social media posts, and clinical trial data to help healthcare providers and others predict the spread of the disease, assess its potential, find new treatments, and identify cambodia whatsapp data populations. Gartner says that by 2025, AI will be able to analyze any type of content, which will drive major innovation and transformation for 75% of Fortune 500 companies. According to Rita Sallam, research vice president at Gartner, the adoption and impact of X-analytics will be expanded by the development of AI in the cloud. This opens up a variety of use cases, such as image and video analytics for supply chain optimization, weather analysis, or traffic management.
5. Metadata is the “new hot thing.” Organizations that use active metadata, machine learning, and data fabrics to dynamically connect, optimize, and automate data management processes will reduce data delivery times by 30% by 2023. AI techniques are used to recommend best practices, automatically discover metadata, or automate control monitoring, among other things. This is made possible by a concept Gartner calls the “data fabric.” It defines a data fabric as something that uses continuous analytics of existing, discoverable, and inferred metadata assets to support the design, deployment, and consumption of integrated and reusable data objects, regardless of the deployment platform or architectural approach.