EGUIDE:
In this expert e-guide, learn how cloud analytics removes the barrier between business workers and important data. Discover why you should use only quality data in your cloud analytics, and how software platform company ServiceChannel eased the burden on their IT department by deploying a cloud BI platform.
WHITE PAPER:
This whitepaper discusses the new features of IBM's InfoSphere Information Server V11.5, which helps you understand data and cleanse, monitor, transform, and deliver it.
CASE STUDY:
Calvin Klein, one of the world's leading fashion brands, had to transfer all of their transactional and master data from a non-SAP system to the SAP platform, without losing any information or compromising data and process quality. To do this, Calvin Klein leveraged an out-of-the-box SAP add-on for data migration.
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.
WHITE PAPER:
Learn about the 10 essential MDM requirements, which will allow you to address both your current and future business needs, and quickly reap the returns from your MDM initiative.
WHITE PAPER:
What companies need are agile analytics tools that help users get insights, and help IT maximize its bandwidth and abilities to help reach business goals. Answer these 5 key questions to help IT pros and business users leverage data.
WHITE PAPER:
This resource examines the roles that information integration and governance play in today's big data world, and offers key recommendations to help you realize the full value of your information and improve business outcomes.
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?
