WhereScape RED White Papers and Reviews
Best Practices for BI: What We Have Learned in 20 Years
Claudia Imhoff, Ph.D. Intelligent Solutions, Inc
"Business Intelligence (BI) is no longer the new kid on the block – we have been building data warehouses, data marts, and the analytical applications to go with these data stores for more than 20 years! And in that time, we have learned a great deal about the right way – and the wrong way – to implement these critical components. We now have sophisticated analytical applications, mature hardware and software, and an educated business community. There is little question that the critical components for BI success are a set of best practices and an iterative, prototype-based methodology for its implementation. Unfortunately, these last, most critical pieces still elude many organizations and are therefore, the topic of this report." Read the full white paper here.
Best Practices for BI: What We Have Learned in 20 Years
WhereScape RED v6 Technology Audit
(Butler Group)
Butler Group, a Datamonitor Company, undertook an independent review of the latest version of WhereScape RED. The full document can be downloaded here, the summary reads:
Building data warehouses/data marts can be a complex and time-consuming undertaking, and the use of these can be limited by the change requirements of an organisation, with speed of organisational change not being matched by the technical change implementation. With WhereScape RED, organisations are not only able to build data warehouses faster, but they can manage the change requirement with less involvement of IT, thus helping to speed up the process.
Although WhereScape RED is designed for data warehouse design specialists, Butler Group found on reviewing the solution – especially the highly intuitive GUI – that most people with an understanding of database principles (as the solution uses standard relational model databases as the target data warehouse) would be equally well served by the product. Much of the inherent complexity of data warehouse design is effectively hidden from the developer, who can concentrate on providing the schemas required. One aspect of this that we found especially useful was the way in which relevant indexes were created without a requirement to understand the performance impact that creating the indexes would have, as the required indexes were created automatically.
Butler Group Technology Audit
Data Warehouse Prototyping - Reducing Risk, Securing Commitment and Improving Project Governance
(Marc Demarest, WhereScape)
Marc Demarest looks at how to more effectively manage both the hard (requirements, budgets) and soft (user perception, internal politics) aspects of complicated data warehouse projects through the use of data driven prototyping.
Data Warehouse Prototyping
Support the Changing Business Needs for Business Intelligence and Performance Management Through Data Warehouse Lifecycle Management
In this white paper IDC describes the latest trends in the business analytics market which includes both data warehousing and business intelligence. It highlights the challenges faced by IT or information management departments in addressing the ever changing decision support needs of business users. Furthermore, it introduces WhereScape Software as a provider of DW lifecycle management software, and summarizes the experiences of two organizations with WhereScape RED software.
IDC WhereScape White Paper
WhereScape RED builds data warehouses, fast.
WhereScape RED is an Integrated Development Environment (IDE) specifically designed for data warehousing. Unlike traditional IDEs, WhereScape RED includes support for the entire data warehouse lifecycle. It enables developers to prototype, build and enhance data warehouses ten to one hundred times faster than any other available software. Read about how our software can deliver fast results to your data warehouse problem.
WhereScape RED Fast
Dimensions of Fast
Understanding the Data Warehouse Lifecycle Model
(Marc Demarest, WhereScape)
Describes the common problems associated with data warehouse projects when they do not use a lifecycle model approach to development and implementation.
Life Cycle
The WhereScape Pragmatic Data Warehousing Methodology:
WhereScape RED is a data warehouse specific Integrated Development Environment (IDE) that encourages the use of a methodology. A standard approach speeds up delivery, and a consistent implementation assists with support and speeds up enhancements.
This paper describes in summary fashion the models, methods and processes that make up the essence of WhereScape's Pragmatic Data Warehousing methodology as practiced by WhereScape designers and as implemented in the WhereScape RED data warehouse Integrated Development Environment. This methodology is gently suggested in WhereScape RED, but can be subjugated by other approaches if preferred.
Pragmatic Data Warehousing
WhereScape RED Architectural Overview
WhereScape RED is an Integrated Development Environment for development data warehouses. This paper provides an overview of the different WhereScape RED components.
Architectural Overview
Adding OLAP to your data warehouse using WhereScape RED
(Douglas Barrett, WhereScape)
The benefits, the features and the architecture of adding OLAP cubes to your data warehouse using WhereScape RED.
Adding OLAP
One Size Does Not Fit All
(Adrian Jurke, Independent)
Why data warehouse developers need their own tools to publish data to business users faster.
One Size Does Not Fit All
Handling Changed Data
(Ken Taylor, WhereScape)
This article examines the data load and processing approaches to handle changing data on the source systems.
Handling Changed Data
Second Tier Tables deliver big Data Warehouse ROI
(Vincent P. Donovan, Arkadia International Consulting)
Discusses how to deliver the analysis that business users want, and that (well designed) single level fact tables can not easily provide.
Second Tier Tables
The Value of the Prototype
(David Morris, WhereScape)
Prototyping significantly reduces the risk that your data warehouse will fail by aligning data warehouse design and user expectations.
Prototype
Does One Size Fit All?
(Wayne M. Richmond, WhereScape)
Discusses how data warehouse practitioners must question the techniques and tools that they use to deliver the best data warehouse for the needs of their users.
Does One Size Fit All?