Data Warehouse Headlines
Source: Gartner.com
Magic Quadrant for Data Warehouse Database Management Systems, 2007
The data warehouse DBMS market is in transition due to new entrants, the data warehouse appliance fever, large DBMS vendors challenging the data warehouse only vendors and the changing workloads affecting the performance of the data warehouse.
What You Need to Know
The data warehouse database management system (DBMS) market continues to show intense, increasing competition. Interestingly, 2007 saw the market continuing to embrace the appliance solution - while many organizations are deploying technically elegant solutions, a larger part of the market is following the mantra of "easy to install, rapid time-to-productivity and 80% of needs met." IBM, Oracle and Teradata continue to battle for the largest part of the market with increased marketing and new functionality. Microsoft has entered the fray with a more competitive DBMS, which has seen a rapid uptake in midsize businesses - especially important, as they will grow into large companies. Although some organizations are using Netezza for larger deployments, it continues to be opportunistic in delivery to organizations needing point solutions for specific analytic or end-user group needs. The march toward a mission-critical status for the data warehouse continues, with data warehouses serving in an increasingly mixed workload capacity. "Deep mining" analysts, and business analysts running less-structured but equally complex queries and fast-running tactical queries, are all competing for CPU, memory and disk access. Each have differing service-level expectations, while at the same time, data latency is changing from batch to continuous demand. Ignore marketing claims and base your decisions on customer references and proofs of concept to ensure that claims made by vendors will hold true in a real-life environment - more specifically, your own environment. Although this is a mature market with the full attention of large vendors seeking to make inroads with scale and innovation, smaller entrants often deliver a more focused, innovative solution (evidenced by the fact that IBM, Oracle and HP have all learned their lesson and deployed an appliance solution of some type). Read More . . .
Source: BI-BestPractices.com
Data Warehousing ROI: Justifying and Assessing a Data Warehouse
Drawing on the data warehousing literature, survey data, theory, and eight case studies, seven justification and assessment propositions are presented.
Data warehouses require a sizeable commitment of organizational resources. As a result, there is considerable interest in how they are initially justified and later assessed. Data warehousing costs are relatively easy to estimate, but the benefits are more difficult to evaluate. Survey data shows that most companies quantify the costs of data warehousing but not the benefits. In order to better understand how companies justify and assess data warehousing investments, eight case studies were conducted. Drawing on the data warehousing literature, survey data, theory, and the case studies, seven propositions are presented. Read More . . .
Source: DMReview.com
Data Warehouse Quality Assurance Best Practices
Customer Intelligence
In my April column, I commented that many organizations more fully understand the importance of data quality and data governance but are struggling with various aspects of implementing programs to address quality within their customer, value-added applications such as customer relationship management (CRM) and sales force automation (SFA).
While many organizations have been getting better at ensuring quality within CRM applications and understand the importance, they still struggle with the critical task of testing data warehouses and marketing databases. This column talks about some best practices regarding data warehouse quality assurance (QA).Read More . . .
Source: amazon.com
Amazon SimpleDB- Limited Beta
Amazon Web Services
Amazon SimpleDB is a web service for running queries on structured data in real time. This service works in close conjunction with Amazon Simple Storage Service (Amazon S3) and Amazon Elastic Compute Cloud (Amazon EC2), collectively providing the ability to store, process and query data sets in the cloud. These services are designed to make web-scale computing easier and more cost-effective for developers. Read More . . .
