Aligning the enterprise data migration strategy with broader enterprise objectives is vital in facilitating digital transformation. IBRS looks into the interplay between data portability and data mobility in their roles in successful data migration.
Discover strategies to effectively manage large language models (LLMs) in your enterprise and optimise your AI solution for better outcomes.
AI-infused information management tools are already in the market and more are expected. However, AI will not solve the issues that are crushing information management teams and leaving organisations exposed to increasingly fractured information governance practices.
As users take more control of what information they share through utilising ad blockers, disposable emails, and even limiting the data which they reveal whilst using digital services, is zero party data the best way to ensure enterprises still acquire valuable user information for marketing and other data-driven business decisions?
A growing amount of IT research discusses how artificial intelligence (AI) tools may support effective information management (IM), often through process automation. This is valid. But so is the inverse proposition, that effective IM supports productive use of AI and reduces its risks. Do not assume there is a one-way street: examine how enhancing IM practices now may support current and future AI initiatives.
Assurance of data integrity is the key to surviving a cyber incident. How do you increase your probability of success?
There are frequent calls for yet another ICT policy, often overlapping existing ones. A holistic view – an ICT policy framework – can reduce the effort to create and maintain policies, and deliver benefits through increased compliance.
What makes Tim Berners-Lee’s Solid project capable of bringing changes in the way we interact with the internet? IBRS explores how this affects control over personal information and its implications for organisations.
Google’s announcement of sunsetting Universal Analytics in favour of a new platform, Google Analytics 4 (GA4), raises questions about its data and privacy risks. Should enterprises think twice about consenting to the forced automated migration, or better opt-out and settle for a new analytics platform? What does this imply about the risks of automated data migration?
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