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Creating more efficient data and AI organization

In this case, proper data management is one of the foundations of a data-driven organization. But managing data in a business can be very difficult. As these new technologies come along, the burden of parenting and data inheritance grows, unless they are integrated or blocked.

The fragmentation of architecture is the subject of a major data center (CDO), not only because of silos but also the various future tools and cloud tools that many organizations use. In addition to the lack of adequate information, these issues include capturing data agencies — as well as learning machines and analytics that assist — speed and the scale needed to deliver what they want.

To understand how data management and technology-dependent interventions are changing in the midst of such challenges, MIT Technology Review Insights analyzed 351 CDOs, analytics controllers, cognitive controllers (CIOs), technical controllers (CTOs), and other modern leaders. We also held in-depth discussions with several other tech leaders. Here are the main results:

  • Only 13% of organizations are very successful in providing their services. A select group of “best performers” provides test results for the entire company. They are doing well because of their interest in overseeing building and construction management, which enables them to “improve democracy” and benefit from machine learning.
  • A technology-enabled partnership creates a working environment. The CDOs surveyed in this study show a critical need to improve democracy and MLs. Pushing the edges with advanced knowledge technologies will help end users to make informed business decisions – identifying the strong cultural values ​​of knowledge.
  • ML’s business performance is limited due to the difficulty of running their end-to-end life. Multiplying cases of ML use is extremely difficult in many organizations. The biggest problem, according to 55% of respondents, is the lack of central storage space and access to ML types.
  • Businesses need cloud platforms that support data management, analytics, and machine learning. The organizations’ most advanced corporations over the next two years have fallen into three areas, all supported by the implementation of cloud platforms: streamlining data management, promoting data analysis and ML, and enhancing the use of all types of businesses, including migration and instability.
  • Open standards are crucial to future architecture. If the interviewees are able to create a new business model for their business, the most important opportunity in the existing architecture is to receive more open source and open source form.

Download the entire report.

This was created by Insights, the hand of material contained in the MIT Technology Review. It was not written by the authors of the MIT Technology Review.

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