EZINE:
In this week's Computer Weekly, we look at Gartner's call to innovate – and innovation across retail, the circular economy and the automotive sector. We talk to Verastar's CTO about customer engagement in its small business services. And we examine how poor data quality is frustrating corporate desires to be data-driven. Read the issue now.
EGUIDE:
The value of data depends on its quality. In this 14-page buyer's guide, Computer Weekly looks at how the coronavirus pandemic has highlighted the challenges of inaccurate datasets, the new analytics techniques improving data quality and Informa's use of Collibra software
WHITE PAPER:
By automating information integration and governance and deploying it at the point of data creation, organizations can boost big data confidence. Access this whitepaper now to discover the importance of data integration, and how your business will benefit from such a methodology.
EGUIDE:
As your company amasses data from multiple sources, you can potentially lose control over data quality and accuracy. In this expert e-guide, learn why it's time to halt the data free-for-all and apply data governance to keep your organization on track.
WHITE PAPER:
This white paper discusses the challenges facing companies when it comes to the analysis of unique data, like emails and chat logs. Access now to see how one system provides valuable insights from non-binary information, a key aspect of a successful future.
EGUIDE:
Companies will typically begin MDM efforts in one domain area before expanding to a multi-domain program model. When taking the multi-domain leap, it's critical to keep key elements in mind. In an excerpt from a MDM book, experts explain how to identify MDM domains and your master data. Plus, learn 5 steps to implementing a MDM program.
EBOOK:
Data integration is much more than just extract, transform and load tools. Today, it's a businesswide effort that requires a diverse set of tools and methodologies.
WHITE PAPER:
Ensuring your data is secure and trustworthy is paramount to harnessing the power of big data, but it's also a difficult task when you've got such a large volume and variety of information coming into the business. Unfortunately, traditional methods of governing and correcting often aren't applicable to big data -- so what can you do?
