On Demand
For the past three decades, relational database management systems have formed the bedrock on which most operational and analytics applications have been built. Over this time frame, these systems evolved and matured to the level where database technology became a commodity. Recently, however, many database products have added significant improvements that make possible what was previously impossible. These improvements not only enhance performance and reduce costs, but also enable the handling of new types of data and applications.
Colin White
Sponsored by
TDWI and IBM Content
Few organizations design an a priori “enterprise architecture.” Rather, systems environments evolve organically as technology decisions are made to address particular business challenges. In essence, this engineers complexity into the environment and establishes data integration as a necessity for interoperation.
David Loshin
Sponsored by
Liaison Technologies
Can business analysts effectively use predictive analytics? Adoption of predictive analytics and other advanced analytics has increased for a number of reasons, including a better understanding of the value of the technology and the availability of computing power. Economic factors are also a driving force in utilizing predictive analytics for business as companies strive to remain competitive. Companies want to better understand customer behavior. They want to better predict failures in their infrastructure. The uses for predictive analytics are extensive and growing.
Fern Halper, Ph.D.
Sponsored by
SAP
As big data continues to grow bigger, become more diverse, and more real-time, forward looking organizations are looking to manage and analyze this data using advanced analytics in an environment which 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 and Intel
Business users today want to move past the limits of spreadsheets and canned business intelligence (BI) reporting to gain a richer, more personalized experience with data. Users want to explore data and discover new insights they can apply readily to improve business strategies, processes, operations, and customer engagement.
David Stodder
Content Provided by
TDWI, IBM, Information Builders, Oracle, Qlik Tech, SAP, SAS, Tableau Software, Tibco Spotfire
Most legacy enterprise data warehouse (EDW) architecture can satisfy many routine workloads associated with operational querying, reporting, and analytics. However, the accelerated growth of data volumes, diversified types of both structured and unstructured data streams, have motivated many business intelligence stakeholders to consider newer technologies that can accommodate these workloads. Today, companies are being asked to support more advanced predictive and prescriptive analytics while also maintaining a nearly flat budget.
David Loshin
Sponsored by
Hewlett Packard Enterprise
Cloud computing is a hot topic as organizations look to take advantage of the agility and pay-as-you-go model the cloud offers. Data warehousing is undergoing significant change—an increasing number of organizations are using the cloud for data warehousing at the same time as they begin to take advantage of new sources of data, advances in business analytics, and new database technologies. However, determining which projects are best suited to cloud-based computing and selecting a cloud solution are not easy tasks.
Colin White
Sponsored by
Snowflake