On Demand
TDWI Research indicates that more companies are considering moving to public or hybrid cloud offerings for some or all of their analytics. Whether for customer, supply chain, or financial metrics, such organizations often collect large amounts of data—especially public cloud-generated data—and are interested in analyzing that information in the cloud.
Fern Halper, Ph.D.
Sponsored by
Teradata
No matter the vintage or sophistication of an organization’s data warehouse (DW) and the environment around it, the DW probably needs one or more upgrades and enhancements to address new requirements for advanced analytics, real time, streaming data, machine data, big data, and unstructured data. These and related issues are addressed in a new Checklist Report by TDWI’s Philip Russom called Tips for Modernizing a Data Warehouse. That report was sponsored by vendor firms Cloudera, Impetus, MapR Technologies, and Teradata Corporation.
Philip Russom, Ph.D.
Sponsored by
Cloudera, Impetus Technologies, MapR, Teradata
Why predictive analytics now? Many companies use BI to better understand what has already happened in their business—a backward-looking view. Although this can be somewhat useful, organizations can gain real value by harnessing their valuable corporate data to understand why something is happening now, and more important, what's likely to happen next.
Claudia Imhoff, Ph.D.
Sponsored by
SAP
Data Platform as a Service (dPaaS) delivers a new, unified approach to data integration and data management that is changing the way many companies integrate their business partners and glean insights from their data.
Philip Russom, Ph.D.
Sponsored by
Liaison Technologies
While the ongoing work of delivering business value through daily decision making still continues through business intelligence and data warehousing efforts, a quiet but conspicuous evolution has occurred in the ease with which these projects proceed. Data warehouse automation (DWA) has spurred that evolution.
Barry Devlin
Sponsored by
WhereScape
Hadoop initially proved its worth as a Spartan but highly scalable data platform for reporting and analytics in Internet firms and similar digital organizations. Its journey is now taking Hadoop into a wider range of industries, use cases, and organizational types. Hadoop is again challenged to prove its worth, this time by satisfying the stringent requirements that traditional IT departments and business units demand of their platforms for enterprise data and business applications.
Philip Russom, Ph.D.
Content Provided by
TDWI, IBM, Actian, Cloudera, Exasol, MapR, MarkLogic, Pentaho, SAS, Talend, Trillium
Enterprise resource planning (ERP) systems have become commonplace at organizations seeking to optimize business performance measures. While ERP promises to streamline business processes, some hurdles must be overcome to optimally leverage data from ERP environments for business intelligence, let alone predictive analytics and operational intelligence. And as many enterprises juggle multiple ERP systems, some of the most critical issues include the pain of integrating non-ERP system data, and the complexity of balancing the ERP environment with reporting and analysis, which results in limited flexibility to make changes and incorporate other BI/analytic tools.
David Loshin
Sponsored by
Teradata