The analytic sandbox should be minimally governed. The idea is to create an environment that lives without all the overhead of the data warehouse environment. It should not be used to support the organization’s mission critical capabilities. It shouldn’t be used to directly control or support any core operational capabilities. Likewise, it is not intended to be utilized for ongoing reporting or analytics required by the business on an ongoing basis, especially any reporting that supports external reporting to meet financial or government regulations.
Source: Design Tip #174 Does Your Organization Need an Analytic Sandbox? – Kimball Group
Built one of these in 1992. It was retired in 2014.
This Design Tip reflects on the remarkable durability of the basic Extract-Transform-Load paradigm, while at the same time recognizing some profound changes that must be addressed. These changes are due to new data demands, new classes of users, and new technology opportunities.
via Design Tip #169 New Directions for ETL | Kimball Group.
One of the most effective tools for managing data quality and data governance, as well as giving business users confidence in the data warehouse results, is the audit dimension. We often attach an audit dimension to every fact table so that business users can choose to illuminate the provenance and confidence in their queries and reports. Simply put, the audit dimension elevates metadata to the status of ordinary data and makes this metadata available at the top level of any BI tool user interface.
via Design Tip #164 Have You Built Your Audit Dimension Yet? – Kimball Group.
This article describes six key decisions that must be made while crafting the ETL architecture. These decisions have significant impacts on the upfront and ongoing cost and complexity of the ETL solution and, ultimately, on the success of the overall BI/DW solution. Read on for Kimball Group’s advice on making the right choices.
via IntelligentEnterprise : Kimball University: Six Key Decisions for ETL Architectures:
Notwithstanding the claims of some DW appliance vendors that you just “wheel it in and slap your data on (just load, and don’t worry where it is) and then you do the analytics” a lot of organisations go along the long-established route of regular batch data loads to a data warehouse. These traditional data warehouses often have long life spans, they run day in day out for many years; and in my opinion to do that you need sustainable, supportable ETL code.
via Rittman Mead Consulting » Blog Archive » Simple Steps to Sustainable ETL.