SCUBA的动态

Privacy, increased focus on 1P data, and AI have created a gap in the tech stack. Learn more about how the AI Data Warehouses is the foundation for a modern 1P data strategy. Harnessing 1P and AI-generated signals and time-series data for in-the-moment insights. Check out the latest blog from SCUBA's CEO, Tony A. , "Capture Signal Loss and Measure with Decision Intelligence." https://hubs.li/Q02VB7W-0 #FirstPartyData #DataPrivacy #TimeSeriesAnalytics #SCUBA #AI

I am excited to share a detailed blog post that examines?"The Data Trends Shaping 2024 & Beyond". Crafted by my brilliant colleague Nelson Ogbeide, this article provides an in-depth look at the innovative developments that are redefining our approaches to data management. ?? Key Insights: ? Generative AI: Pioneering new ways of generating and enhancing data across sectors. ? Responsible AI & Ethical Data Governance: Ensuring trustworthiness and reducing bias in our data-centric society. ? Data Fabric: Streamlining data integration to boost flexibility and oversight. ? DataOps: Merging data science with operations to accelerate actionable insights. ? Data Observability: Guaranteeing the robustness and dependability of our data systems. ?? Read the Full Article: https://lnkd.in/epzPr57i #DataTrends2024 #GenerativeAI #DataGovernance #DataFabric #DataOps #DataObservability #Billigence

AI-related Data Management Trends for 2025 - RTInsights: Even with the dawn of AI, organizations still face issues such as siloed heterogeneous data, governance concerns, and poor data quality; all of which?...

In his latest TDAN.com - The Data Administration Newsletter column, John Wills, Founder & Principal of Prentice Gate Advisors, highlights why data mapping isn’t just technical—it’s a strategic necessity for data leaders. Poor mapping leads to?quality risks?and hidden?people costs?that drain resources. Key Tips: 1. Define & align?on the value of data mapping. 2. Create standards?to guide its use. 3. Enforce validation?to avoid rework. Boost data quality, reduce confusion, and free your team for AI and analytics. Are you making the most of data mapping? Read now:?https://lnkd.in/eamy9hRD #DataLeadership #DataMapping #AI #Analytics #DataStructures #Data

Data Products are something I've been learning more about as I work with larger and larger systems. They are a really cool way of not only getting rid of messy integrations and organizing data, but they also can be used to power AI. Since your AI is only as good as your data, this is a great way to help get your data organized. https://lnkd.in/gjnG4VcU

My colleague Brandon DeLano wrote a great introduction on Data Products. Your organization's unique data is the key to unlocking the power of Generative AI, and Data Products are a key tool to get you there. #ArtificialIntelligence #Data

Imagine creating detailed metadata like this shortened version for your entire collection of artworks—manually: ? <?xml version=”1.0” encoding=”ISO-8859-1”?> <ListArtwork> <artwork xml:id=”#Struycken_Computerstructuur_4A”> ???????????????<artist ref=”#Struycken”> Struycken, Peter </artist> ???????????????<title ref=“#Computerstructuur_4A“> Computerstructuur 4A</title> <year>1969</year> ?<description>Computerstructuren is a pioneering digital artwork created by Peter Struycken in 1969. It explores the use of computer algorithms to generate complex visual structures, marking a significant development in the field of digital art.</description> </ListArtwork> ? It remains a common and time-consuming practice for many researchers in Digital Humanities and collection registrars in museums and libraries. But is GenAI making a leap in 2025 to revolutionize metadata creation, to allow more time for meaningful research?and?curation? Read the blog post on 2025 data management trends ???

Can semantic graph technology truly solve the data management problem, or is it just another point solution? Simply deploying the technology won't magically banish data silos. The real challenge for businesses is building a strong data foundation with clear ownership, access controls, and consistent data structures. This is where the the unglamorous but essential work of cleaning, organising, and connecting data before reaping the benefits of AI. Will businesses prioritise this data housekeeping, or will siloed data continue to be the Achilles' heel of AI projects? #DataManagement #AIandData #FutureofBusiness https://lnkd.in/gtS_uUmu

Drowning in data but thirsty for insights? Traditional data management is slow and cumbersome. The Modern Data Company proposes a data product revolution! Build modular, pre-packaged data solutions for specific needs. Just like a just-in-time supply chain, get the data you need, when you need it. Make faster decisions and unlock hidden value in your data! #datamanagement #dataproducts #datadriven #AI #ML #LLM #dataengineering #CDO https://hubs.li/Q02zMn0G0

???????? ???????? ???????? ???????? ?????? ???????? ????????????????????? From interoperability to generative data management: new challenges are emerging and shaping the data management agenda. In our latest blog post, we discuss these trends, including: ?? The interplay between GenAI and data management. ?? Overcoming heterogeneous technologies and data semantics across organizational siloes. ?? Balancing data democratization with people capabilities to foster high-quality decision-making. ?? Read all about it here: https://lnkd.in/eubVeEcV Are you dealing with data management within your organization? Share your experience in the comments. #DataManagement #AI #GenerativeAI #DataTrends #Interoperability #DataMesh #ScalingData