Enterprise AI and algorithmic processes require perfect synchronisation and agility. This is where DataOps comes in the picture – as a single point of contact when something goes out of sync.
Implementing Master Data Management in a small company or startup and a large organisation is two completely different things.
DataOps has already gotten the epithet “enterprise data management for the AI era”.
It’s been several weeks since our first Speaker spotlight, and already we’ve had more marvellous speakers come onboard at the special edition of the Data 2030 Summit. T
The United Arab Emirates have really earned their prime spot at the Data & AI global map. Data and AI investments in the UAE have been on an increasing course for the last several years.
Although data governance initiatives are usually started to fulfil external regulations and requirements, it’s so much more than security and compliance. It’s fundamental business hygiene that helps us do our business in an effective and efficient way.
DataOps is enterprise data management for the AI era. It’s one of the fundamental pillars of a modern data management strategy.
With recent economic disruptions and technology advances, data sources continue to rise significantly producing ever more transactional and interactional data. The lack of unified omnichannel experience is due to poor data management.
Although the energy industry has been somewhat slow to catch up with the advances in data management, the course has certainly shifted.
One overlooked, but a much-needed feature of online events are roundtable discussions, as they provide a more powerful, focused and valuable online learning experience for attendees.
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