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Data, analytics and AI predictions for 2023 | TechTarget
Source: techtarget.com
Article summary:
1. Expect more M&A activity in 2023 as vendors look to tell more unified, end-to-end and comprehensive stories.
2. Data sharing with trust and governance will be a heavy focus in 2023, with governance having greater ties to data quality and data observability.
3. Automation will greatly influence employee decisions to stay or move on, and businesses that oppose automation will have a hard time attracting and keeping the best workers.
Article analysis:
The article "Data, analytics and AI predictions for 2023" by TechTarget provides a comprehensive overview of the expected developments in the field of data, analytics, and artificial intelligence in the coming year. The author predicts an increase in M&A activity, a focus on data sharing with trust and governance, a reduction in data management costs, efficiency and productivity gains made through augmented AI experiences, automation affecting employment and retention, a focus on data as a product and data mesh, and real-time technology going mainstream.
While the article provides valuable insights into the potential future of these technologies, it is important to note that some claims are unsupported or lack evidence. For example, the prediction that there will be a significant decrease in costs associated with handling and managing large-scale data collected from various sources due to cutting-edge automation and AI/ML technologies lacks evidence to support this claim. Additionally, while the author notes that there may be risks associated with automation affecting employment and retention, they do not explore counterarguments or present both sides equally.
Furthermore, the article may have biases towards promoting certain technologies or companies. For instance, the author mentions specific acquisitions such as Qlik/Talend and Confluent/Flink as examples of M&A activity to watch out for without providing any other examples or exploring potential downsides of such mergers. Additionally, while discussing data mesh as a platform purposely built as a distributed data architecture that incorporates various components such as storage and consumption, analytics, centralized governance, security and standardized interoperability - it is important to note that this concept has been promoted by certain companies such as ThoughtWorks.
Overall, while the article provides valuable insights into potential developments in the field of data analytics and AI for 2023 - it is important to approach these predictions with caution given potential biases towards promoting certain technologies or companies without exploring counterarguments or presenting both sides equally.
Topics for further research:
Criticisms of data mesh as a distributed data architecture
Potential downsides of M&A activity in the tech industry
Counterarguments to the claim that automation will significantly affect employment and retention
Evidence supporting the prediction of reduced data management costs through automation and AI/ML technologies
Alternative predictions for the future of data analytics and AI in 2023
Companies promoting data mesh as a platform and their potential biases