To avoid a million-dollar software implementation mistake, Data Warehouse World was the place to be recently.
That's because measuring the success or failure of projects and debunking myths surrounding software trends were the main topics of discussion there and at related trade shows.
Data warehouse and ERP projects, especially, can cost millions of dollars for large companies. In an effort to guide users and help them avoid common software implementation pitfalls, several keynote speakers focused on debunking common beliefs that may lead to costly mistakes.
The tone of several panels was set by Bill Inmon, chairman of the board of Pine Cone Systems and a data warehouse consultant. Inmon was co-founder of Prism Solutions and is often referred to as the "father of the data warehouse".
"I've been reading that 70 per cent of data warehouse projects fail," Inmon said. "This is poppycock."
In both the general press and trade press recently there have been reports that a majority of data warehouse projects fail, which may turn off many companies from technology that can give them a strategic and beneficial business edge, Inmon said.
Close examination of the research projects that are the basis for these reports of failure lead to a very different conclusion, he said.
In a heated preamble to his keynote speech, Inmon said he had contacted several companies that have researched data warehouse projects. Some researchers say a data warehouse project is a failure if the goals of the implementation change within a year, he said.
"This is like saying . . . Bill Gates is a failure because he didn't graduate from Harvard, because his original goal was to go to college and get a degree," Inmon said.
However, companies can make costly mistakes, he said. Building several data marts before developing a data warehouse can be one of the biggest mistakes a company can make, he said, refreshing a theme that has been discussed at several Data Warehouse World shows.
Data marts are a subset of data warehouses, containing less data and less history, and customised for a specific department. Data warehouses contain more detailed data, which the data marts summarise for the purposes of different departments in a company.
Building data marts before a data warehouse can make it difficult to integrate different departmental-level data. Data marts require a separate interface to be built for each data source - for example, transaction processing applications.
Data marts roll up detailed data in different ways. "The result is that the sales department will give you a different number for your revenue than the marketing department . . . you end up with a big mess," said Inmon.
On the other hand, there are some trends that can save companies big money, and allow them to facilitate analysis by "out of the box" thinkers, said Inmon.
Information on DCI shows can be accessed at (www.dci.com/).