Following hot on the heels of its acquisition of web analytics firm Coremetrics, IBM has been playing up its role in the space as it looks to spearhead the growing business optimisation and analytics market.
The firm reckons that the business optimisation sector, which includes BI and analytics, is growing at more than twice the rate of the business automation sector, and is currently worth around $105bn globally and growing by 8% per year.
The company has spent over $12bn over the last few years on research and development in the space and on acquisitions, most notably Cognos, bought for $5bn in 2007 and SPSS, acquired for $1.2bn in July 2009. A number of the big software houses moved into the analytics space through acquisitions: SAP bought Business Objects while Oracle snapped up Hyperion.
A survey carried out by IBM recently revealed that one in three business leaders frequently make critical decision without all the information they need and 53% don’t have access to the information across their organisation that they need to do their job.
Henry Cook, data warehouse business lead for IBM UK’s InfoSphere team, said that Big Blue is aiming to reduce the complexity associated with many business analytics platforms: "We want to look at the complete process – how long does it take for the right person to be given the information they need to actually start improving the business? The traditional method often involves just adding more loads on to the complexity and more and more spreadsheets that can contain anything anyone wants to type into them."
So what is IBM doing differently? Cook says that the company wants to offer a complete view of a company’s information, "an electronic picture of everything that is inside the organisation, every person, transaction, supplier and product so that IBM can electronically fly around it in a way you can’t do in the physical world to quickly and simply answer questions," he said.
Content from our partners
The Smart Analytics System Alternative, as Cook calls it, aims to offer customers a "single vision of the truth", which is easy to deploy, share, administer and understand. "It sits in the middle [between the systems where the data is held and the people who need to access it] and is something that anybody at any level of the organisation can go to for a single, understood description of the data," Cook adds.
The huge amount of data that these systems need to crunch through in order to return the most useful information can sometimes make legacy analytics systems slow, Cook argues, but IBM’s platform hopes to address those issues through parallel processes.
"If you keep adding more data to the computer system, it will slow down," he said. "But what if we gave each bit of data its own computer? Then, providing we’ve written the software correctly, it can take a question and divide it up into lots of little questions and the system will run much faster. Parallel processing is one of the absolute key requirements for handling large analytics systems."
SAS has also beefed up its portfolio to enable companies to make decisions much more quickly. The firm said that SAS High-Performance Computing uses private computer grids and SAS In-Memory Analytics, which enables calculations to be performed on each server node. This speeds up the computational process, SAS claims.
"Our customers face growing problems that challenge current computing techniques," said SAS CEO Jim Goodnight. "SAS High-Performance Computing breaks down highly complex tasks into groups of much smaller problems, distributing those across many processors with the data in-memory. Rapid analysis delivers better answers faster, and a boost to competitiveness and profitability."
A report from analyst house Gartner earlier this year said that IBM claimed 12.2% of the BI, analytics and performance management space in 2009, behind SAS with 14.2%, Oracle on 14.5% and SAP, leading the pack with 22.4% market share.
