The Aginity Blog Planning and Building an Enterprise Data Factory Posted by: Dan Kuhn - CTO on 11/30/2009 | 0 Comments Categories: Netezza enterprise data factory analytic data factory data factory The key to the data factory approach is a clear end-to-end view of the data production system. It is important to chalk out what needs to be achieved in the short-term and the long-term. Before beginning a data factory initiative it is important to ask the question "How will the business be different after we've implemented this solution?"  Other questions that need to be asked are: what represents the real value for the end users and for the business? What are the challenges wit data and analytics quality? Read More Quality Control -- Ensuring Integrity in the Enterprise Data Factory Posted by: Dan Kuhn - CTO on 9/2/2009 | 0 Comments Categories: enterprise data factory data quality data factory The quality control subsystem typically executes during the data processing phase of the data factory. It is separated logically because it is managed differently and employs different types of processes. The most significant data quality issues are addressed in the data acquisition phase of the data factory. The quality control phase caters to the serious yet more subtle issues of data integrity and data pattern anomalies. Read More Data Acquisition – The Achilles’ Heel of the Enterprise Data Warehouse Posted by: Dan Kuhn - CTO on 8/31/2009 | 0 Comments Categories: enterprise data factory data quality data factory The data acquisition process is the Achilles’ heel of almost any data factory because: Acquisition errors that make it to an end user are very damaging to user confidence Acquisition errors  are extremely expensive to fix and hard to diagnose Data acquisition requires interfacing with a variety of different data sources like partners, clients or field staff The system has very little control over the timing and the quality of the transmission. Read More The MPP Data Factory: A Better Approach to the Data Production Problem Posted by: Ted Westerheide - Chief Architect on 8/31/2009 | 0 Comments Categories: enterprise data factory analytic data factory data factory For decades, heavyweights of the information service provider industry such as The Nielsen Company, Information Resources Incorporated (IRI), and Acxiom Corporation have successfully built systems that address the same issues today’s new data-centric businesses are struggling with. Read More   Blog Home		Recent Posts Compile and Register Analytic Process Creating a Netezza User Defined Aggregate (UDA) – understanding the basics Creating a Netezza User Defined Aggregate (UDA) – sample aggregate Archive July 2010 (3) June 2010 (5) May 2010 (1) April 2010 (3) March 2010 (4) February 2010 (1) January 2010 (1) November 2009 (3) September 2009 (2) August 2009 (6) July 2009 (2) Bloggers Brian Weissler Dan Kuhn - CTO Doug Grimsted - CEO Oleg Roman Taluev Sergey Astahov Ted Westerheide - Chief Architect Category List analytic data factory (5) architecture (3) cloud computing (1) code sample (5) data factory (12) data quality (3) data warehouse architecture (3) enterprise data factory (4) Enzee 2010 (5) methodology (2) MPP (3) Netezza (11) operations management (1) Tag Cloud amazon cloud computing cloud services code continuous build data distribution data warehouse performance dimensional scarcity dimensional sparseness ec2 factory architecture factory methodology iclass massively parallel netezza operations management sample snowflake schema udf udx