The following is the Top 10 data and analysis technology trends in 2021 From Gartner recommended by recordtrend.com. And this article belongs to the classification: Gartner, artificial intelligence, Data industry.
Trend 1: more intelligent, more responsible and more scalable AI
With the increasing influence of artificial intelligence (AI) and machine learning (ML), enterprises are required to apply new technologies to develop more intelligent, less data required, more moral responsibility and more flexible AI solutions.
Trend 2: composable data and analysis
The open and containerized analysis architecture makes the analysis function more flexible.
Trend 3: data structure is the foundation
Data structure uses analysis to continuously monitor the data pipeline. Data structure uses the continuous analysis of data assets to support the design, deployment and utilization of various data, thus reducing the integration time by 30%, deployment time by 30%, and maintenance time by 70%.
Trend 4: from big data to small data and wide data
The extreme business changes brought about by the new crown pandemic make ml and AI models based on a large amount of historical data less relevant.
Trend 5: xops
The goal of xops (including dataops, mlops, modelops, and platformops) is to use Devops best practices to achieve efficiency and economies of scale, and to ensure reliability, reusability, and repeatability.
Trend 6: engineering decision intelligence
Engineering decision intelligence is not only suitable for single decision, but also suitable for decision sequence, grouping them into business process, even including emergency decision.
Trend 7: data and analysis as core business functions
D & A is no longer a secondary activity, but a core business function.
Trend 8: charts connect everything
Gartner predicts that by 2025, graphics technology will be used for 80% of data and analysis innovation, up from 10% in 2021, promoting rapid decision-making across the organization.
Trend 9: the rise of expanding consumption
Today, most business users are using predefined dashboards and manual data exploration, which can lead to wrong conclusions and flawed decisions and operations.
Trend 10: edge data and analysis
By 2023, data and analysis leaders will have more than 50% primary responsibility, including creating, managing, and analyzing data in marginal environments.
More reading: Gartner: India’s total it expenditure will reach 94 billion US dollars in 2020 Gartner: SWOT analysis of Alibaba cloud services Artificial intelligence projects of enterprises will double in 2020 Gartner: AI enhancement will create US $2.9 trillion of business value Gartner: enterprises will deploy 4 AI / ml projects on average in 2019 Gartner: current situation and future of artificial intelligence Gartner: global IT expenditure will increase by 1.1% in 2019 Gartner: 47% enterprises plan to increase investment in Internet of things Total public cloud revenue in the Middle East and North Africa will reach nearly $3 billion in 2020, up 21% Gartner: by 2023, 10% of workers will try to cheat AI overlord Gartner: the leading trend of AI maturity curve in 2019
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