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The expansion of big data applications has created opportunities across economic sectors. In healthcare, however, the potential of big data applications goes far beyond the financial. The contextualdata gleaned from big data can drive healthcare solutions and accessibility to new heights.
In that capacity, he knew that, in addition to having the right team and technical building blocks in place, data was the key to Regeneron’s future success. “It It is all about the data. Everything we do is data-driven, and at that time, we were very datacenter-driven but the technology had lots of limitations” says McCowan. “It
Emission factor mapping and other capabilities As part of Oracle Fusion Cloud Sustainability, enterprises would get access to features such as automated transaction records, contextualizeddata, pre-built dashboards, emission factor mapping, and audit capabilities.
This is where metadata, or the data about data, comes into play. Having a data catalog is the cornerstone of your data governance strategy, but what supports your data catalog? Your metadata management framework provides the underlying structure that makes your data accessible and manageable.
Data is now being used to support business decisions few executives thought they’d be making even six months ago. So, what is data literacy? Collaborate more effectively with their partners in data (management and governance) for greater efficiency and higher quality outcomes. Good Data = Good Decisions.
Data consumers need detailed descriptions of the business context of a data asset and documentation about its recommended use cases to quickly identify the relevant data for their intended use case. Data consumers have more contextualizeddata at their fingertips to inform their analysis.
Knowledge graph technology can walk us out of the lack of context (which is basically absence of proper interlinking) and towards enriching digital representation of collection with semantic data and further interlinking it into a meaningful constellation of items.
One technology getting attention in this area is knowledge graphs (KGs), as the related standards and tools can contribute semantics, stronger reliability and greater interoperability to this data so users can optimise and leverage its full value. A resource might be something like a power plant or a specific generator within a power plant.
Our Knowledge Hub Fundamentals article What is a Knowledge Graph describes how knowledge graphs are more than just simple data graphs because they include a knowledge model that adds three things: formal semantics, descriptions that contribute to each other, and diverse data that is connected and described by semantic metadata.
For this reason, people often struggle to make vital business decisions as they face a complex data landscape. Metadata is the information about data that gives it meaning and context. It helps to answer basic, yet important questions like: “What does this data mean?”, “Which data is used the most?”, “Where did it come from?”,
The emergence of generative AI prompted several prominent companies to restrict its use because of the mishandling of sensitive internal data. In the generative AI or traditional AI development cycle, data ingestion serves as the entry point. This may also entail working with new data through methods like web scraping or uploading.
An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.
Many organizations prioritize data collection as part of their digital transformation strategy. However, few organizations truly understand their data or know how to consistently maximize its value. How does your business become more adept at wringing all the value it can from its data?
It’s a truism that data is the most important asset in the 21 st century economy. But, today too many enterprises exist in a data fog, with poorly contextualizeddata scattered across millions of tables. Dispelling this data fog is one of the key challenges for the next generation enterprise.
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