On Demand
Agile development methods—as applied in data disciplines—have experienced strong adoption by users in recent years, and for good reason. As more organizations “run the business” based purely on data (and compete and innovate), data management professionals are under increasing pressure to deploy data solutions into business use sooner, produce multiple solutions, and align data solutions with quickly evolving business goals. Hence, delivery speed, development productivity, and business alignment are the leading priorities (and benefits) for agile data management.
Philip Russom, Ph.D.
Sponsored by
Dell EMC
Although many different techniques and technologies for big data appliances can increase scalable performance, the ways that certain applications are mapped to a typical Hadoop-style stack might limit scalability due to memory access latency or network bandwidth. Yet the promise of big data must go beyond increased scalability for known problems.
David Loshin
Sponsored by
Teradata
Information integration is critical for becoming smarter with data. Across all industries, organizations want to use data analytics to discover how they can reduce costs without sacrificing quality and effectiveness. Firms both large and small want to pull diverse data streams together. Users can then uncover insights and innovate at a faster pace than their competition.
David Stodder
Sponsored by
Hewlett Packard
Changes in the way that today’s business transpires have slowly been cutting away at the ability to meet fully the needs of data consumers. At some point, those who manage the data warehouse will hit a threshold or boiling point that will make modernization mandatory.
Philip Russom, Ph.D.
Sponsored by
Hewlett Packard
Today’s BI environments have split personalities. They must support the production of routine reports and analyses used every day for decision-making by line-of-business employees, and yet, also enable data scientists and data crunchers to “freewheel” through the data in an unplanned, experimental fashion. What magic is this? How can implementers create a sustainable BI environment with these two seemingly contradictory purposes? Does one replace the other? What are the technological requirements for this new world?
Claudia Imhoff, Ph.D.
Sponsored by
SAP
High-quality data visualization is critical to the success of business intelligence, analytics, and data presentation. Because graphical interaction with data is now the norm, users are excited—and also have increasingly high expectations. Technology is important, but you also need to execute best practices to avoid pitfalls and to create beautiful data visualizations that are clear, effective, and accurate.
David Stodder
Sponsored by
TDWI and IBM Content
According to multiple TDWI surveys, the vast majority of IT users feel that big data is an opportunity, because of the new and more granular insights it provides about customers, operations, partners, and many other business entities and processes. Likewise, most users now see advanced forms of analytics as the primary path to reaping insights from big data, whether big data comes from traditional enterprise applications or new sources, such as Web applications, application logs, sensors, machines, and social media. For these reasons, TDWI sees many user organizations diving deeper into big data analytics.
Philip Russom, Ph.D.
Sponsored by
Teradata