How the problems of multi-source data discovery as experienced by a typical business analyst today can be addressed by introducing an integrated information platform—a modern, high-level architecture—that includes data virtualization.
The third EMA / 9sight Big Data Survey was conducted in late 2014, with the results published in April 2015. Beyond Big Data itself, the survey also addressed the concepts of data lake, data driven and the Internet of Things, providing a comprehensive view of the state of thinking in the broadest definition of Big Data from 351 respondents. (more…)
Three key ways in which data warehouse automation changes the design, development and ongoing maintenance of data warehouses and marts. First, how automation addresses the old conundrum of delivering consistent, quality data in the timeframe demanded by modern business needs. Second, how streamlining the overall process provides a single repository of metadata and integrated tooling to speed and simplify development. Third, how business and IT can truly collaborate in delivering business solutions. (more…)
We explain how and why the current layered DW architecture developed and examine why today’s business imperatives of speedy decision making and data driven action taking demand a new operational/informational approach. This environment, also called HTAP (hybrid transaction/analytical processing), needs a combination of in-memory operation and novel database techniques to enable simultaneous read/write and long-read activities on the same data. (more…)
This paper examines four use-case-based business needs in banks and financial institutions that demand increasing speed, agility and business-IT collaboration in today’s market conditions. In each of these areas–reporting, risk management, customer profitability and responsive decision making–we examine the business challenges, prior and current implementation problems, and the answers offered by data warehouse automation. (more…)