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Statistical Data Analysis

QlikView Plots Business Intelligence for the Masses

For many years, decades even, the segment of ‘business intelligence’ has sat in the overlap of the Venn diagram of desires shared by IT leaders and their business stakeholders. Business wants IT to deliver tools that mine data to generate market-changing insights and for IT that goal would give them the ticket to sitting on the Board and earning the full respect of peers. All too often though, despite huge sums spent on software programs and consulting engagements, business intelligence has remained somewhat of an oxymoron.

BI projects have ended up mining fools’ gold and engendering disappointment. Complex algorithms and user interfaces have been understood by a select few and those few have too often struggled to create a common language with business heads. So ‘rubbish in, rubbish out’ has frequently prevailed. But one company stands out for having delivered usable tools and real results. That company is QlikTech, or QlikView as the firm is better known after its flagship product.

Remarkably, QlikView has earned that reputation without having come to the party late and without legacy, unlike relative newcomers playing in broadly the same field such as Tableau Software and Splunk. The company was formed in 1993 and did not float until 2010. That steady-as-she-goes progress is partly explained by its roots in Sweden: no get-rich-quick, fast-talking outfit this. The company may be softly spoken but it has racked up a $3bn market cap and a roster of 29,000 customers across 100 countries.

Rather like Tableau and Splunk, QlikView has a passionate, even evangelical following. They call themselves Qlikkies and are highly effective advocates for a company that by the brash standards of the enterprise software industry is notably self-effacing.

“We’re dealing with a subject matter that’s universal but has a very personal experience in terms of the way people interact with data,” says Les Bonney, QlikView COO. “The younger generation has grown up with easy and unique access to data but in most cases they’re being thrown back into the dark ages when they come to the workplace.”

Of course, partly that’s the issue of not knowing upfront where the valuable data and correlations lie. After all, if it were that easy every company would be reinventing itself in marvellous ways with sky-high rates of successful execution.

“If you want to buy a fridge or a car you get swamped with information,” says Bonney, a business software veteran and former general manager at Oracle. “In the workplace it’s difficult to know where the data is, never mind how you make best use of it. The IT industry has done a reasonable job in [process] but the last mile is the challenge. How you get that [actionable] information into the hands of people who need to make a decision?”

The question of who those decision-makers are is at the crux of modern BI. Typically, a rarefied set of users has dominated with specialist data analysts reporting into strategic decision-makers, excluding the rank and file and many of the people who are closest to the business action. But Bonney sees BI as being for everybody “from the janitor to the CEO”.

“It’s quite incredible that you go into the largest companies on the planet and they’re still dealing with 35-year-old information access challenges. Large companies we talk to often don’t know how many people they have or what their roles are. But the demand of workforce is to have more and more data. I think there’s going to be more change in the way enterprises are structured and the way they have to organise themselves in the next five years than since the industrial revolution.”

That’s a bold claim but then scarcity of resource, globalisation and other broad trends may mean that companies have to become more agile and flatter organisations that empower people to make decisions every day, Bonney argues. As opposed to just talking about the same and then not doing anything practically, I suggest, and Bonney concurs.

“It’s also transparency, all these things people have talked about for years, but if they don’t work with these trends they’re going to lose their way competitively.”

Real-world decision-support systems will move from “nice to have” to “must have” if companies are to avoid the precipitous declines in fortune that we have seen so visible in recent years in retail, for example. The race will be on to discover “serendipitous ‘aha’ moments”.

At the same time, companies will have to edge carefully around governance rules and there will be “a tension between highly governed data and the freedom to swim around”.

Data scientists will rise and they will work in tandem with domain experts to solve problems. We will all have to become adept at understanding data patterns and asking ‘what if?’ questions but this will happen automatically in the same way that camera phones made us all photographers.

Bonney says QlikView is pursuing a situation where BI becomes such a natural, instinctive experience that “the technology gets out of the way”.

“People who are experts in their jobs tend to enjoy their jobs; if you give them access to information that’s a very seductive, addictive environment. There’s almost an emotional response. People say ‘you’re going to have to prise this out of my hands’ or ‘I’ll cry if this goes.’”

Part of the historic problem with BI has been sticker price. These tools have commanded large premiums and therefore have only been allocated to specialists but Bonney sees a change coming with more utility-based and user-band pricing. As tools become simpler, “price will come down and down and down”.

Bonney is less bullish than some on cloud, however, suggesting that large data sets can be a tricky proposition when constrained by bandwidth, but he says that QlikView is working on its own cloud service using a datacentre partner.

The change coming in BI will be easier for QlikView to handle than for the giant stack players like IBM, Oracle and SAP, he argues.

“They’re still confused. I don’t think they were clear what they wanted to do [when they bought BI specialists] and the age-old problem is that analytics gets lost in these stacks. Stacks are complex, difficult to implement and difficult to use. This consumerisation of analytics is always going to be challenge for [stack vendors]. They’re going to have to disrupt their own revenue streams radically because they have huge investments in place.”

Buyers will naturally evolve to those vendors offering “a guerrilla approach to data”, he reckons. It will be a Brave New World that puts an end to the cautious and cumbersome approaches that have clung to BI for so long. A change is going to come. Finally.

 

Martin Veitch is Editorial Director at IDG Connect

 

Related stories:

Birst CEO Brad Peters on Making BI’s Promise a Reality

Splunk EMEA Boss is inside the Tornado

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Martin Veitch

Martin Veitch is Contributing Editor for IDG Connect

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