On Demand
Traditional systems development projects are process driven, and the requirements-gathering activities proceed accordingly. Business intelligence initiatives are data driven, and this requires a different approach to understanding the needs. This Webinar examines three major differences and techniques for getting requirements.
Jonathan Geiger
Sponsored by
Tableau Software
Adoption of predictive analytics has been increasing thanks to a better understanding of the value of the technology, vendors making the technology easier to use, and the availability of computing power. The uses for predictive analytics are extensive and growing. Companies want to understand customer behavior, they want to better predict failures in their equipment, and they want to deploy analytics in order to take action.
Fern Halper, Ph.D.
Sponsored by
TDWI and IBM Content
In many ways small and midsize businesses (SMBs) have greater opportunity when using BI. Yes, budgets and resources may be limited, but most SMBs are not as constricted by robust IT infrastructures that control BI access and use like their enterprise counterparts. Consequently, many SMBs are empowered through their BI applications to take advantage of interactive technologies without the limitations of large-scale enterprisewide IT infrastructures.
Lyndsay Wise
Sponsored by
Information Builders
The big data software ecosystem has evolved into a robust framework for developing analytics applications spanning a wide range of complexity. At the same time, big data deployments more commonly center on the platform as an expansion of the corporate file system. The concept of the data lake resonates with enterprises desiring to offload data assets into a common platform for analysis, yet the analyses often remain batch-oriented—summarizations, aggregations, and other ETL-like tasks.
David Loshin
Sponsored by
Cray
The vast amount of information now available to organizations is spurring a push toward leveraging data to understand customers more completely. Organizations can gain insights from the data they collect, but developing higher retention and better competitive advantage also means providing customers with access to the analytics that apply to them. This is becoming prevalent in vertical markets such as data service providers, education, health care, utilities—the list is endless.
Lyndsay Wise
Sponsored by
Information Builders
The pace of business continues to accelerate, such that organizations must now react faster and more frequently to customer interactions, service-level agreements, operational commitments, competitive pressures, and other time-sensitive issues. With technologies maturing, organizations must evaluate the options they need for the real-time delivery, access, and analysis of information, if they are to reduce business latency or eliminate it.
Philip Russom, Ph.D., Fern Halper, Ph.D., David Stodder
Content Provided by TDWI and IBM, Actian, Cloudera, Datawatch, HP, Tableau Software, Treasure Data, Striim
TDWI, IBM, Actian, Cloudera, Datawatch, HP, Striim, Tableau Software, Treasure Data
Traditional data warehouses are becoming even more complex as they strain against the weight of today’s data explosion.
Philip Russom, Ph.D.
Sponsored by
TDWI and IBM Content