The business intelligence (BI) market, which Gartner estimates is now worth more than $14 billion, is large and expanding. The list of leading vendors includes well-known names such as Microsoft, IBM, SAP and Oracle, as well specialist companies including Tableau Software, QlikTech, Tibco Software and Information Builders.
Over the past few years many companies have implemented business intelligence platforms, most of which are purchased by IT departments. These BI systems tend to be highly centralized, with reports produced by the IT department pushed out to a range of analysts and more general users, according to Gartner. Because of this, many BI platforms are underused and have ultimately proved to be a poor investment, it concluded in a recent report:
"While analytical capabilities were deployed - such as parameterized reports, online analytical processing (OLAP) and ad hoc query - they were never fully embraced by the majority of business users, managers and analysts, primarily because most considered these too difficult to use for many analytical use cases."
As a result, many companies are looking to complement or even replace their existing business intelligence platforms over the coming months. If you are planning a BI investment in the near future, here are six common mistakes that you need to avoid to ensure your investment is an effective one.
Paul Rubens has been covering enterprise technology for over 20 years. In that time he has written for leading UK and international publications including The Economist, The Times, Financial Times, the BBC, Computing and ServerWatch.
Originally published on Enterprise Apps Today.
CPQ is a sales tool designed to help companies produce accurate and highly configured quotes. It centralizes all complex product, pricing and business rules, making them automatic and available in real time. ... More >>
Embracing a digital supply chain not only drives greater agility, efficiency and innovation, it also creates business advantage for companies. ... More >>
In our enthusiasm for all things "Big Data," are we abetting the data collectors in something that might be bad for society's (and our own) best interest? ... More >>