This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
In the rapidly evolving digital landscape, information governance has become more critical than ever. As we approach 2025, organizations face new challenges and opportunities in managing, securing, and extracting value from their data. Improve Decision-Making: AI-driven analytics provide deeper insights into data trends and patterns.
This research reveals that while organizations are eager to harness the power of AI, significant hurdles stand in the way—such as data silos, unstructureddata , real-time analytics delays, and security concerns. In a world increasingly driven by AI and machine learning, this is a critical gap that must be addressed.
In today’s digital age where data stands as a prized asset, generative AI serves as the transformative tool to mine its potential. IBM, a pioneer in data analytics and AI, offers watsonx.data, among other technologies, that makes possible to seamlessly access and ingest massive sets of structured and unstructureddata.
Data science is a broad, multidisciplinary field that extracts value from today’s massive data sets. It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. It’s also necessary to understand data cleaning and processing techniques.
Some utilities have built “data lakes” to handle structured and unstructureddata (weather, social media, sensors, etc.), as well as ascertain how the cloud fits into the equation.
While these RIM practices are still important to help ensure governance, compliance, and manage risks, it is also important to realize that information is both a product and a service. Information Governance (IG). Discussions of IG often lead to a discussion of datagovernance (DG) and whether the two are different.
According to the report, Organizations should consider OpenText for its strong content governance, records management, and workflow capabilities. Organizations simplify data migration to the cloud, ensure information governance, and reduce costs. Document Mining and Analytics.
When we consider that fixed, controlled records following recordkeeping principles and information governance are typical objectives in our programs, it’s not unreasonable to get a little scared by this. A recent Iron Mountain US government employee survey cited the skills gaps that need to be closed by tomorrow’s info pro.
We organize all of the trending information in your field so you don't have to. Join 55,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content