On Demand
Reports and dashboards that utilize historical data to gain insight are just the beginning of a company’s analytics journey. Advances in technology including predictive capabilities can help organizations gain competitive advantage by helping them discover trends, patterns, and relationships in data and guide their next course of action. In the past, predictive analytics has been the realm of statisticians and other quantitative individuals and was often separated from BI activities.
Fern Halper, Ph.D.
Sponsored by
TDWI and IBM Content
Big data analytics, mobile devices, cloud-based solutions, self-service BI, and predictive analytics—these are the major trends impacting today’s decision-making environments. Exciting, yes, but enabling these trends can also be quite disruptive to traditional data management processes and the implementers, analysts, and decision makers themselves.
Claudia Imhoff, Ph.D.
Sponsored by
Liaison Technologies
Speed, agility, and intelligence are competitive advantages that nearly all organizations seek. To seize these advantages, organizations require timely, diverse, complete, and accurate data. Unfortunately, traditional data warehouse extraction, transformation, and loading (ETL) processes are not fast enough. They put too much burden on ETL developers to understand every nuance of every data source, and it’s getting worse as Hadoop and other big data sources become part of the mix. How can organizations take advantage of new big data sources to deliver complete and diverse views of data—and get beyond the limits of traditional data warehouses?
David Stodder
Sponsored by
SAP
Cloud BI has been positioned as the next evolution in business intelligence because of the advantages it provides in terms of flexibility and elasticity. However, there is still confusion in the market around moving to a cloud model, and cloud BI adoption has been slow, although interest seems to be increasing. For instance, in a recent TDWI survey, a majority of respondents were either already using the cloud or were considering it for BI and analytics.
Fern Halper, Ph.D.
Sponsored by
GoodData, MicroStrategy
As big data continues to grow bigger and become more diverse and more real-time, forward-looking organizations are looking to manage and analyze this data using advanced analytics in an environment that might include multiple approaches and technologies. For real-time streaming data this could include utilizing technologies that support in-memory processing, where data and mathematical computations are performed in RAM rather than on disk, enabling processing thousands of times faster than data access from disk.
Fern Halper, Ph.D.
Sponsored by
SAP
A picture can paint a thousand numbers and broaden the appeal of BI tools. A fiercely competitive business environment demands more agility and shorter time to insight. These forces have given rise to visual data discovery tools as a new module in the BI portfolio. Specialty BI vendors are growing rapidly and BI platform vendors have rushed to add visual discovery capabilities to their portfolios.
Cindi Howson
Sponsored by
SAS
Predictive analytics is a powerful technology that is rapidly becoming mainstream. It is being used across industries to understand and predict customer behavior, detect fraud, determine outcomes, and much more. An important trend in the market is the move to make the output from predictive analytics more consumable by end users.
Fern Halper, Ph.D.
Sponsored by
Information Builders