Security News > 2020 > November > 7 big data goals for 2021: AI, DevOps, hybrid cloud, and more
In 2021, corporate big data leaders will be looking to improve data quality and turnaround of big data projects, as well as performance in meeting business objectives.
Big data continues to enter corporate networks at torrential rates, with the amount of poor data that companies obtain or use costing the US economy an estimated $3.1 trillion annually.
More effort needs to be made to screen data as it comes in, and to properly clean and prepare data before it is added to corporate data repositories.
As the need grows for more data to be pulled together from disparate sources, an over-arching hybrid cloud architecture that includes cloud and on-prem platforms should be formalized, and enterprise security and governance should be uniformly applied throughout.
As more vendors simplify AI solutions, there has been growth in citizen AI, where business units develop their own AI and big data applications.
News URL
Related news
- How AI Is Changing the Cloud Security and Risk Equation (source)
- Google Cloud Cybersecurity Forecast 2025: AI, geopolitics, and cybercrime take centre stage (source)
- Microsoft Fixes AI, Cloud, and ERP Security Flaws; One Exploited in Active Attacks (source)
- Data Governance in DevOps: Ensuring Compliance in the AI Era (source)