On Demand
As the use of big data grows, the need for data management in the new environment will also grow. The combination of new data and new technology requires new data management capabilities and processes in order to realize the promised benefits.
Mark Madsen
Sponsored by
SAP
Big data analytics, mobile devices, cloud-based solutions, social media data, and predictive analytics—these are the major trends in today’s decision-making environments. Exciting, yes, but incorporating these trends can also be quite disruptive to traditional architectures and the implementers, analysts, and decision makers themselves.
Claudia Imhoff, Ph.D.
Sponsored by
Information Builders
Advanced analytics is being embraced at an increasing rate by organizations that need to gain actionable insight from their vast amounts of both structured and unstructured information. Although much of the technology that comprises advanced analytics has been around for decades, over the past several years, adoption has increased for a number of reasons.
Fern Halper, Ph.D.
Sponsored by
Tableau Software
Dashboard and self-service excellence is essential to gaining full value from investment in business intelligence tools. Dashboards can play a critical role in increasing an organization’s information awareness and improving overall transparency, strategic alignment, accountability, collaboration, and data governance. However, after initial success in deploying their first dashboards, many organizations struggle with how to get them to the next level of maturity. They also face challenges in keeping growing numbers of dashboards well-managed and in sync, especially as users employ more self-service BI tools and seek to interact with dashboards on their mobile devices.
David Stodder
Sponsored by
TDWI and IBM Content
In one of the strongest trends today, many user organizations are moving deeper into advanced analytics with big data. That’s because conventional wisdom now tells us that there are leverage-able business insights to be discovered in big data.
Many businesses are deploying teams and tools for big data analytics in silos that are disconnected partially or wholly from the rest of their enterprise. Organizations in this situation are not getting full business value from the new insights being discovered because they are rarely shared throughout the company.
Philip Russom, Ph.D.
Sponsored by
Actuate - now OpenText
For those of us in IT and especially BI, there’s nothing more exciting than seeing practices and technologies come together in a new combination, to support enterprise business in a new way. At the moment, we are seeing such a confluence of practices and technologies for real time, analytics, big data, and in-memory processing. The combination enables more organizations to credibly address time-sensitive business processes that involve big data and benefit from analytics.
Philip Russom, Ph.D.
Sponsored by
Splunk
Delivering value sooner and being adaptable to business change are two of the most important objectives today in developing and deploying business intelligence (BI) and analytics. Organizations are under pressure to adjust strategies and tactics to fast-changing markets and economic situations, and they are depending on BI and analytics to help them make good decisions. In addition, as more users are exposed to BI and analytics tools, the more they want in terms of functionality, data access, and other capabilities. IT organizations, used to long “waterfall” development cycles, are struggling to keep up, and are hearing loud and clear from users that they want an end to the frustration.
David Stodder
Sponsored by
Attivio, Informatica Corporation, Jaspersoft, MicroStrategy, SAP, Tableau Software, WhereScape