Here's an actual Share the Data™ project. This is a simplification of a plan developed with a real client, with details changed to remove any identifying information. While every project is unique, this is not an unusual engagement. Share the Data™ engagements range in length from 3 days to several weeks, depending on project complexity and client resource availability.
The client is approaching a key turning point in their operational history- going beyond traditional reporting with mainframe technologies to an advanced data warehouse with web-based reporting, dashboards, self-service analytics and even advanced analytics to optimize customer recruitment, operational management and improve the overall customer experience.
All of these areas are a dynamic, iterative undertaking with each area interlinked and interdependent. It is critical that the management team at the client work to prioritize, fund and support each iterative phase of these projects. Likewise, it is imperative that each phase of these projects show an acceptable rate of return (or greater!) for the time and money invested in these initiatives. Better data and analytics are not an end in themselves, but rather a means to a more profitable and competitive company.
My Background in Data Warehousing
I have been involved in the creation, development, and maintenance of seven data warehouses through the years- one of them before I even knew about the term "data warehousing"! I have built them with SAS and Oracle, SAS alone, Informatica and Oracle, Oracle alone, and SQL Server.
I have also visited many companies as an adviser, consultant and user of their data warehouse. In these many visits, I have seen some successes and many failures. Often, the failures could have been prevented with some key guiding principles.
Data Warehousing or Enterprise Data Integration?
Data warehousing is now known by a new buzz word, Enterprise Data Integration. In fact, SAS recently renamed SAS ETL Studio as SAS Data Integration Studio (they also added some new features around the EDI area, one new feature was around continual data acquisition so that near real time data feeds are available in the data warehouse.) Another great part of SAS EDI is SAS Data Quality, this should be a consideration throughout the entire process, but I won't directly comment about data quality in this post. Since most people still use the term data warehousing, so I will keep the popular terminology over the analysts and even SAS.
What Does it Take to Build a Successful Data Warehouse?