Recently I was on a road trip with a couple of girlfriends. It was a gorgeous early summer weekend. We were driving from Boston to Maine, about three hours away. What do you do on road trips? You eat snacks and sing loudly.

We were in the mood for a little U2. One friend plugged her iPod into the iPod-specific jack on the car stereo—a media package I paid extra for when I bought the car. The stereo came with upgraded speakers and sounded pretty good when I went for a test drive, and it was purported to support iPods and iPhones.


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The first challenge came when the stereo didn’t recognize my friend’s iPod. Maybe her iPod was too old. So she plugged in my iPhone 4. The stereo recognized the device just fine. But we spent nearly 20 minutes trying to figure out how to get to my U2 collection. The interface seems fairly straight forward, upon first glance. But what is “PTY/CAT?” “What is “A.S?” What is “RDM?” After you push PTY/CAT, A.S, or RDM, then what?

It would have been fine if we could have interacted with the stereo using the iPhone, which has a very intuitive user interface. But the system requires that you interact with your mobile device via the stereo panel rather than your device’s screen.We eventually stumbled on an “artist mode” option, but it looked like the only way to get from the As to the Us was to manually page through the artists, pushing a button over and over to move down through the list of artists. After a few moments of that we switched our choice from U2 to Abba (QlikTech’s Swedish roots have gotten to me!). But someone pushed something and we couldn’t figure out how to get back to artist mode.

We pulled over by the side of the road and took the half inch-thick user manual out of the glove box. We tried to follow the instructions to get to the music we wanted to hear. But we eventually gave up. My friend pulled out her BlackBerry and pushed play, and we sang loudly to the tinny sound of Abba songs coming out of the tiny speaker in her handheld device.

Wait, wait, don’t go. I’m not hijacking The QlikView Blog to complain about my car stereo. My point is this: even if a car stereo has the best technology behind the face plate—the highest wattage, the best digital sound processing, the finest magnets—all that goodness is of no use to me if I can’t figure out how to use it.

The same is true for BI software. Even if all the company’s data is on the back end, and a skilled BI team spent months building out the richest, most comprehensive dashboard, if the user can’t figure out how to ask a question and get an answer, ask another question and get another answer—without having to get in the queue to ask IT for a new query or report—than nothing else matters. It’s all about the user experience, and the user experience is more than just a pretty (inter)face.

Since joining QlikTech last year, one of the things I’ve been most impressed with is the passion and excitement QlikView users have for the product. I wrote about this in my first blog post here, and it underlies a core theme that we are seeing in the market: the consumerization of business intelligence stemming from a growing population of empowered consumers within the enterprise.

 

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Earlier this month James Richardson from Gartner published an excellent piece on this topic: The Consumerization of BI Drives Greater Adoption (available here for Gartner subscribers). Reiterating many of the comments I have made in previous posts (here and here), James states that because traditional BI tools are too complex, too rigid and too slow, well below 30% of the potential BI users actually use the technology today.

 

James then lays out three key recommendations for organizations (and BI vendors), drawing from new technologies and models found in the consumer space:

 

  • Usability:  As James points out, consumers today just pick up new technology and use it. They don’t read a user manual for Facebook or Google, and they have come to expect that ease of use from their enterprise software. In fact, according to Gartner “ease of use for end users” is now the most important selection criterion when choosing BI tools. At QlikTech ease of use for business users means the freedom to interact with the data the way your mind works: search, drill anywhere and navigate across data sets. Don’t be constrained by rigid hierarchies and predefined selection options.

 

  • Performance: Google has taught us to expect answers to all our questions in under a second. If it takes more time than that we assume something has gone wrong and we stop and rerun the search. If users are to truly adopt BI, they must get that same performance when querying data. James identifies in-memory processing as a key technology here, but his main point is that quicker is better: by making BI quick, users will ask more questions and test more hypotheses before making a decision.

 

  • Relevance: At a recent Gartner conference, one of the keynote speakers quipped that traditional BI tools have become sophisticated ETL tools for business users: they use them to pull data out of the data warehouse into Excel where they do their real analysis. Part of this is due to the usability issues outlined above, but part of this is because the users have other data they want to combine with the standard corporate data to get a complete picture. As James points out, if the BI platform omits critical information, users won’t use or trust it. Thus, BI platforms need to support data mashups, allowing business users to combine their own data sources without relying on formal data integration.

 

I am certainly seeing the consumerization of BI software in the QlikView customer base and I think James has made some great points about what is necessary to make this happen. What do you think? What will it take for BI to become a daily productivity tool for your business users?

Since joining QlikTech last year, one of the things I’ve been most impressed with is the passion and excitement QlikView users have for the product. I wrote about this in my first blog post here, and it underlies a core theme that we are seeing in the market: the consumerization of business intelligence.

Earlier this month James Richardson from Gartner published an excellent piece on this topic: The Consumerization of BI Drives Greater Adoption (available here for Gartner subscribers). Reiterating many of the comments I have made in previous posts (here and here), James states that because traditional BI tools are too complex, too rigid and too slow, well below 30% of the potential BI users actually use the technology today.

James then lays out three key recommendations for organizations (and BI vendors), drawing from new technologies and models found in the consumer space:

·         Usability:  As James points out, consumers today just pick up new technology and use it. They don’t read a user manual for Facebook or Google, and they have come to expect that ease of use from their enterprise software. In fact, according to Gartner “ease of use for end users” is now the most important selection criterion when choosing BI tools. At QlikTech ease of use for business users means the freedom to interact with the data the way your mind works: search, drill anywhere and navigate across data sets. Don’t be constrained by rigid hierarchies and predefined selection options.

 

·         Performance: Google has taught us to expect answers to all our questions in under a second. If it takes more time than that we assume something has gone wrong and we stop and rerun the search. If users are to truly adopt BI, they must get that same performance when querying data. James identifies in-memory processing as a key technology here, but his main point is that quicker is better: by making BI quick, users will ask more questions and test more hypotheses before making a decision.

 

·         Relevance: At a recent Gartner conference, one of the keynote speakers quipped that traditional BI tools have become sophisticated ETL tools for business users: they use them to pull data out of the data warehouse into Excel where they do their real analysis. Part of this is due to the usability issues outlined above, but part of this is because the users have other data they want to combine with the standard corporate data to get a complete picture. As James points out, if the BI platform omits critical information, users won’t use or trust it. Thus, BI platforms need to support data mashups, allowing business users to combine their own data sources without relying on formal data integration.

 

I am certainly seeing the consumerization of BI software in the QlikView customer base and I think James has made some great points about what is necessary to make this happen. What do you think? What will it take for BI to become a daily productivity tool for your business users?

Since joining QlikTech last year, one of the things I’ve been most impressed with is the passion and excitement QlikView users have for the product. I wrote about this in my first blog post here, and it underlies a core theme that we are seeing in the market: the consumerization of business intelligence.

Earlier this month James Richardson from Gartner published an excellent piece on this topic: The Consumerization of BI Drives Greater Adoption (available here for Gartner subscribers). Reiterating many of the comments I have made in previous posts (here and here), James states that because traditional BI tools are too complex, too rigid and too slow, well below 30% of the potential BI users actually use the technology today.

James then lays out three key recommendations for organizations (and BI vendors), drawing from new technologies and models found in the consumer space:

·         Usability:  As James points out, consumers today just pick up new technology and use it. They don’t read a user manual for Facebook or Google, and they have come to expect that ease of use from their enterprise software. In fact, according to Gartner “ease of use for end users” is now the most important selection criterion when choosing BI tools. At QlikTech ease of use for business users means the freedom to interact with the data the way your mind works: search, drill anywhere and navigate across data sets. Don’t be constrained by rigid hierarchies and predefined selection options.

 

·         Performance: Google has taught us to expect answers to all our questions in under a second. If it takes more time than that we assume something has gone wrong and we stop and rerun the search. If users are to truly adopt BI, they must get that same performance when querying data. James identifies in-memory processing as a key technology here, but his main point is that quicker is better: by making BI quick, users will ask more questions and test more hypotheses before making a decision.

 

·         Relevance: At a recent Gartner conference, one of the keynote speakers quipped that traditional BI tools have become sophisticated ETL tools for business users: they use them to pull data out of the data warehouse into Excel where they do their real analysis. Part of this is due to the usability issues outlined above, but part of this is because the users have other data they want to combine with the standard corporate data to get a complete picture. As James points out, if the BI platform omits critical information, users won’t use or trust it. Thus, BI platforms need to support data mashups, allowing business users to combine their own data sources without relying on formal data integration.

 

I am certainly seeing the consumerization of BI software in the QlikView customer base and I think James has made some great points about what is necessary to make this happen. What do you think? What will it take for BI to become a daily productivity tool for your business users?

Since joining QlikTech last year, one of the things I’ve been most impressed with is the passion and excitement QlikView users have for the product. I wrote about this in my first blog post here, and it underlies a core theme that we are seeing in the market: the consumerization of business intelligence.

Earlier this month James Richardson from Gartner published an excellent piece on this topic: The Consumerization of BI Drives Greater Adoption (available here for Gartner subscribers). Reiterating many of the comments I have made in previous posts (here and here), James states that because traditional BI tools are too complex, too rigid and too slow, well below 30% of the potential BI users actually use the technology today.

James then lays out three key recommendations for organizations (and BI vendors), drawing from new technologies and models found in the consumer space:

·         Usability:  As James points out, consumers today just pick up new technology and use it. They don’t read a user manual for Facebook or Google, and they have come to expect that ease of use from their enterprise software. In fact, according to Gartner “ease of use for end users” is now the most important selection criterion when choosing BI tools. At QlikTech ease of use for business users means the freedom to interact with the data the way your mind works: search, drill anywhere and navigate across data sets. Don’t be constrained by rigid hierarchies and predefined selection options.

 

·         Performance: Google has taught us to expect answers to all our questions in under a second. If it takes more time than that we assume something has gone wrong and we stop and rerun the search. If users are to truly adopt BI, they must get that same performance when querying data. James identifies in-memory processing as a key technology here, but his main point is that quicker is better: by making BI quick, users will ask more questions and test more hypotheses before making a decision.

 

·         Relevance: At a recent Gartner conference, one of the keynote speakers quipped that traditional BI tools have become sophisticated ETL tools for business users: they use them to pull data out of the data warehouse into Excel where they do their real analysis. Part of this is due to the usability issues outlined above, but part of this is because the users have other data they want to combine with the standard corporate data to get a complete picture. As James points out, if the BI platform omits critical information, users won’t use or trust it. Thus, BI platforms need to support data mashups, allowing business users to combine their own data sources without relying on formal data integration.

 

I am certainly seeing the consumerization of BI software in the QlikView customer base and I think James has made some great points about what is necessary to make this happen. What do you think? What will it take for BI to become a daily productivity tool for your business users?

Earlier this week I wrote about social BI―in particular, about the various contexts through which social BI can be delivered to users. (See related blog posts here and here.) I discussed two primary approaches to delivering social BI: Information Workplaces, and deploying BI platforms that have embedded social and collaboration capabilities.

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We deliver it how you want it

Our approach is to meet the needs of both types of organizations and teams: those that want to use BI in the context of their existing collaboration and social platforms (or Information Workplaces, where they exist), and those that want social and collaboration features embedded in their Business Discovery platforms. Here’s how we do it today.

If you want embedded collaboration capabilities . . .

We offer:

  • Shared bookmarks. Another way to think of shared bookmarks is user-driven report creation. A user starts from a core dashboard and finds something interesting. They bookmark it and share it, allowing other users to see exactly what they saw. This is effectively an interactive report―a starting point with which users can explore the data further in a collaborative way.
  • Collaboration objects for self-service BI. Often, the notion of self-service BI means users can grab data from the source and work with it locally themselves―typically in an Excel spreadsheet. This private analysis is now disconnected and not shared. But with QlikView, the document is on the server and all users have the same starting point and viewpoint. If a user has a perspective they gain through creation of a new object, or discovery of a bookmark, they can put this object on the server and decide who to invite in. A developer (or business user who has permissions) can easily incorporate the change back into the design of the core app and share it with a broad set of users.

If you are taking a Microsoft-centric Information Workplace approach . . .

We offer:

  • Microsoft Office integration. QlikView provides the ability to run inside Microsoft Office applications using a QlikView plugin. Users can bring a QlikView app into a Microsoft PowerPoint presentation, for example, to share it with others.
  • SharePoint integration. Organizations can enhance the context for decision-making by embedding QlikView apps in SharePoint portals and team collaboration sites. Users can then interact with QlikView objects in SharePoint sites alongside other decision-making inputs, such as documentation, enterprise applications, or reports generated by traditional BI solutions. QlikView customers can embed full QlikView apps in SharePoint sites as web parts, right out of the box. Or, by using our QlikView web parts for use with Microsoft SharePoint® product, customers can embed individual QlikView objects (e.g., charts, visualizations, and list boxes) in SharePoint sites.

Social Business Discovery is a big theme for QlikTech for 2011. Stay tuned for more info!

I raised a question in a recent blog post: What’s the right context for users to engage in social BI? Should social and collaboration tools be delivered to users as part of their BI platform? Or should BI capabilities be delivered to users as part of their enterprise collaboration platform or information workplace? (See related Forrester blog post, “The Information Workplace Gets Social.”) The answer depends on a couple of factors.

Three factors determine context.png

If and where users can get the social and collaboration capabilities they need

Social Business Discovery is about enabling people to collaboratively create analytic apps, make shared business discoveries, and collaborate on data-driven decisions. Do business users have access to a great set of social and collaboration tools they can use to accomplish this? If so, which environment provides these capabilities to users in the easiest, most intuitive way: the enterprise collaboration tools or the BI platform?

  • Several of the BI megavendors made it onto Forrester’s list of the four anchor vendors lighting the way with information workplaces (Google, IBM, Microsoft, and Oracle). (See the October, 2010 Forrester report, “The Information Workplace Light Burns Brighter”―available only to Forrester clients, or for purchase.) These vendors offer a gigantic stack of technology, pieced together through acquisition, which includes both BI tools and collaboration tools.
  • But Forrester has pointed out that even after an organization has made a big bet on one of the information workplace platform vendors, the organization may still need to fill in gaps in areas like BI, business process management, and search. And competing analyst firm Gartner pointed out in its “2011 Magic Quadrant for Business Intelligence Platforms” that one BI platform may not be enough; to ensure that the needs of business users are met, IT organizations should take a portfolio approach to BI.

Users’ primary work environment for decision-making

In which software environment(s) do people spend the bulk of their time? And where do they go when they need to make a decision?

  • Some information workers may spend their time with their laptops and an information workplace—and they may best be served by accessing their BI tools in this context.
  • Other people make go into a decision application (like QlikView), and while in there make a discovery they want to share or discuss with someone.
  • Still others (e.g., data wranglers, power analysts, or data-driven decision makers) may by the very nature of their jobs spend nearly all their time in their BI environment.

There’s no one right answer—no one-size-fits-all solution. For some organizations, the dominant approach to social BI will to be to deliver BI to users in the context of an information workplace. In these environments, BI tools should integrate with the existing enterprise collaboration platform. Other organizations will choose to deploy BI platforms that have embedded social and collaboration capabilities. And it’s likely that even in an organization that settles on one of these options as the enterprise standard, not all users will consume (achieve?) social BI in the same way.

How does it work in your organization? Has your organization deployed information workplaces—and if so, is BI delivered to users through them? Are you using BI software that has built-in social and collaboration capabilities? Are you running into “when do we use which tool?” problems? I’d like to hear from you―drop me a line at erica.driver@qlik.com or leave a comment below.

People don’t make decisions based on data alone. They take into account the opinions, ideas, experiences, and perspectives of other people. Conversation and collaboration help create the context around data and drive decision-making forward. It’s this need that social BI aims to meet.

 

People Don’t Make Decisions Based on Data Alone.png

 

A few weeks ago I had conversation about social BI with a QlikTech partner based in Sweden: Peter Skoglund of EdgeGuide Business Solutions AB. EdgeGuide is an IT service provider that has practices in areas such as BI and social media utilizing IBM Lotus Connections. Peter shared with me some of his personal perspectives about the future of social BI.

He described a scenario in which a business user explores data in his Business Discovery app. This exploration leads to questions, conclusions, and insights. The user shares his insights with his team by creating and sharing notes and comments. The BI software passes metadata about the notes and comments to the enterprise social software. The team members interact with the analytic app to gain new insights and with the social software to ask and answer questions of each other, and compare their analysis and conclusions. The team reaches a decision based on the data and their interactions. All notes and comments are stored for future use and knowledge transfer.

This got me thinking . . .

My conversation with Peter Skoglund got me thinking about a question that’s near and dear to my heart, as a former industry analyst who covered information workplaces at Forrester Research. An information workplace enables aggregation of software functionality that helps knowledge workers access the information and expertise they need. It brings together multiple technologies in a seamless, contextual user experience. (See related Forrester blog post, “The Information Workplace Gets Social.”)

The question is this: What’s the right context for users to engage in social BI? Should social and collaboration tools be delivered to users as part of their BI platform? Or should BI capabilities be delivered to users as part of their enterprise collaboration platform, or information workplace? Part of what drives this question is IT’s desire to minimize the overlap in the tools they make available to users, as well as users’ desire for a fun, easy experience and clarity about when to use which tool in their portfolio.

I’ve got lots of thoughts about this and will write more later this week. I’d like to hear your take. What is your approach to social BI? What do you think is the right way to deliver social BI to business users?

In our daily lives, when we search for something (say, our missing car keys), we look or explore, right? We do not drill down or ask one question at a time in the style of a traditional BI query: “I was last in the US when I had the keys,”  “I was last in Wisconsin,” “I was last at home,” and, finally, “I was in the kitchen when I last had my keys.”

Instead, we explore and form associations to try to make a discovery. To try to find your keys, you try to remember the last time you had them. You might remember that you had them in hand when you were talking to your family, and that you were making dinner when you had that conversation. You go into the kitchen and find the keys on top of the microwave oven.

This is the way our minds work. So in the workplace why do we have to drill down in a linear fashion, or run pre-determined queries, when we are searching for business information?

 

Traditional BI tools were not designed with discovery in mind

The challenge with the traditional BI tools is they are not designed with discovery in mind. They were not designed to enable users to search for the answers they need. Traditional BI tools are query- or cube-based. Users can ask one question at a time, or must drill down a pre-defined path. They have no way of visually searching the data at the speed of thought. They might be able to get an answer to the first question that comes to mind. But when they come up with a follow-on question, they need a whole new query.

 

The trouble with OLAP.png

Here is another example. Let’s say you want to review profits across all combinations of five dimensions: gender, region, store type, time and product. The chart above shows the number of possible values that are defined by these five dimensions when evaluated over every combination: more than 100,000,000 possible values!!!

 

Using a conservative estimate for the time it takes to “eyeball” or visually pick out relationships or a pattern in a given number of combinations, it might take more than 250,000 days (684 years!) for an analyst to explore this five-dimensional business question, assuming that roughly 50 combinations could be reviewed in one hour. Most cubes, in traditional BI solutions, have a dozen or more dimensions and perhaps 10-20 measures. You can see why it becomes advantageous to ease the search for interesting relationships in the data.

 

QlikView works the way your mind works

QlikView is different from traditional BI solutions in that it enables business users to search for information in the way their mind works: through associations. With the QlikView Business Discovery platform, users can find the data they’re looking for even when they are unfamiliar with the data structure. They don’t have to drill down on every possible combination of values. They can search using terms that are meaningful to them and QlikView finds the permutations. All the user needs to know is some associated facts.

 

Would you like to see the profit for a product but you can only remember the store type and the region where the product is sold? In QlikView, you could type the store type and region into the search field in the “products” list box. Using just these two associated facts, you would quickly get to the possible product matches. It’s that simple.

 

This powerful capability can be made available to business users by selecting "associative search" as the default search mode on the list box porperty to enable them to do their own search!

Have you ever wanted to give us your input or feedback on demo apps available on the QlikView demo site? Perhaps an app helped you communicate the value of QlikView to a new set of business users. Or you came across something that isn’t working quite the way it should be.

You can always contact our demo team by email. But now, registered members of QlikCommunity can also rate and review our demo apps quickly and easily, right on the demo site.

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Your reviews of QlikView demo apps will be visible to other visitors to the site. Your scores and reviews will guide us as we hone and refine the apps we create. I recently spoke with Shima Nakazawa, global director of QlikView demo and best practices. She said, “We knew how many people were visiting our demo applications, but we didn’t have enough visibility into which demo apps people liked the best. Now, we can begin to identify what it is that makes some applications more popular than others, and direct more of our resources in that direction.”

Your input could even help us improve our product. Shima said, “Like any software company, sometimes we get so used to QlikView and the way it works that it’s hard to see things with fresh eyes. People who use our demo apps may see something that wasn’t obvious to us.” 

We take your ratings and reviews seriously

When you score or write a review about a demo app, a member of our demo and best practices team will give the review a quick read to ensure that it is relevant before publishing to the site. (Don’t worry, we won’t be filtering out less-than-glorious reviews. We just want to make sure no spam gets through.) Based on your feedback and input, we will create more demo apps that have the characteristics you like and will fix any issues you discover.

Tell us how you envision an app could be used for Business Discovery. Let us know if you identify something that is unique―that you haven’t seen in any other app. Let us know what your favorites are. And let us know if there’s something you don’t like about one of the apps. We want to hear your voice.

We commonly get questions about the level of technical skill needed to create and deploy QlikView apps. People want to know if they are going to be successful with their existing skills―or are going to need more training or additional resources. The answer, of course, is “it depends.”

QlikView maturity model - graphic.png

 

Conduct an up-front assessment

The key to a successful QlikView deployment is ensuring that the team possesses the knowledge and experience required by the size and complexity of the implementation. I spoke with Nik Boman, QlikTech’s global director of expert services, and Kim Peretti, our head of global education services, and they offered these thoughts about conducting an upfront assessment:

  1. Identify the skill level of each developer on your team. Remember that with QlikView, business users often do work that traditionally has required IT skills. We recommend bucketing developers into four groups based on their QlikView education and experience: “personal,” “enabled,” “advanced,” and “expert.”
  2. Identify the complexity level of the project. Map the project to a similar complexity model: simple, basic, advanced, and expert.
  3. Determine the criticality of the application. Some projects are high profile or business-critical, where failure is not an option. Other projects are more experimental or are “nice-to-haves.”
  4. Map developer skill against project complexity and criticality. This helps you identify any gaps. Gaps will suggest where to invest in training and education or augment the internal team with additional expertise.

QlikView users with Microsoft Excel skills and a few hour-long QlikView eLearning courses under their belt can create simple apps on their own. By simple apps we mean those that have one to three columnar spreadsheets or low-complexity flat file data sources, simple dimensions and math, a straightforward user interface, and a single language and currency. For these apps, users may not need to complete formal QlikView training. They can get started with QlikView’s wizard-driven interface, online product documentation, and eLearning courses, and can leverage their personal background and instincts for a successful project.

While additional training or resources are not likely needed for simple projects, they may be required for basic, advanced, or expert projects—especially projects that are high profile or business critical.

  • Basic projects. By basic projects we mean projects that may have more data sources (2-3), a single calendar, drill and cycle groups, simple math, a straightforward UI, and a single language and currency. These projects use Microsoft Active Directory, a single QlikView Server and Publisher, and QlikView Web Server.
  • Advanced projects. Advanced projects may have multiple fact tables and 3+ data sources at different granularities, multiple calendars, complex drill and cycle groups, calculations that use variables and basic set analysis, and some user interface automation. These projects involve integration of Publisher with external schedulers, data restrictions via loop and reduce or section access, clustering, use of Microsoft Internet Information Services (IIS), and multiple languages and currencies.
  • Expert projects. Expert projects may have extensive disjointed data and varied facts at different levels of granularity, advanced calendaring, calculations and nested expressions, advanced set analysis, macros, portal integration, mashups, and custom Ajax. Expert projects may also have real-time data updates and write-backs to a database, LDAP or other security integration, multiple clustered QlikView Servers and Publishers, external access, and multiple languages and currencies.

If you need more information, contact your QlikTech services manager. If you don’t know who to call, let me know and I’ll hook you up.

In June, 2011 IDC published its Worldwide Business Intelligence Tools 2010 Vendor Shares report (available only to IDC clients or for purchase). This report assesses the BI tools market and includes revenue and market share information for BI software vendors.

IDC’s Predictions for the BI Tools Market.png
The key highlights from this report are:

  • The BI tools market is nearly USD $9 billion in size. In 2010, the BI tools market reached $8.9 billion in software license and maintenance revenue (including subscription revenue from SaaS offerings). The market grew 11.4% in 2010 compared with 2.0% in 2009. This growth was higher than IDC expected due to better-than-expected worldwide economic activity.
  • The top 10 vendors account for more than 75% of the market. The top ten vendors comprised 75.3% of the market, up from 57.9% in 2003. According to IDC, the top 10 vendors in the worldwide BI tools market by revenue (2008-2010) are SAP, IBM, SAS, Oracle, Microsoft, MicroStrategy, QlikTech (yippee!), Information Builders, Actuate, and Panorama Software. (Click here for QlikTech’s financials.)
  • Most of the action is in end-user query, reporting, and analysis tools. The end-user query, reporting, and analysis segment of the market (which includes QlikTech) outpaced the growth of the advanced analytics segment of the market. The end-user query, reporting, and analysis tools represented 81.3% of the total BI tools market and grew at 12% in 2010. IDC found that in this segment, vendors including QlikTech “significantly outpaced the growth of the market.”
  • Simplicity is king. In 2010, the market saw incremental improvements to BI tools in the areas of simplicity―which primarily meant improvements in user interfaces, interactivity, and administration. This is certainly true for QlikView. One of the key themes in QlikView 10, which we released in October, 2010, was “easier to use.” (Click here to download the data sheet “What’s New in QlikView 10.”)

Looking ahead: the future of BI is bright

Based on trends he’s seeing in the BI tools market, in this report IDC analyst Dan Vesset called out a few themes that are also important to us at QlikTech. He commented that the influence of the cloud computing model’s focus on simplicity, and the increasing buying influence of business users, will grow. Demand for mobile BI will grow also, but organizations will demand BI tools that support specific use cases, rather than just support for various devices. “Mobile BI,” he wrote, “will be driven by the need for mobile workers to participate in specific, collaborative business processes and ad hoc approval workflows for tactical decision making.” And he said that “collaborative and social decision making” (the discipline formerly known as knowledge management) will spur new investments in collaborative BI tools―music to our ears, to be sure.

In his 2009 book Change By Design, author and IDEO president and CEO Tim Brown used the term “design thinking” to describe a non-linear way of innovating and solving problems. Design thinking is a means of applying principles of design in a disruptive, game-changing way to generate more and better insights. (Register here to get a free copy of the book. We have a limited number of copies available.)

Change by design book cover.JPG
 
Design thinking is an exploratory process that results in unexpected discoveries. These discoveries can be significant enough to warrant refining or rethinking assumptions rather than pressing onward in adherence to an original plan. One example Brown gave in the book was Nokia’s shift from being a hardware company to becoming a provider of platforms for delivery of rich, interactive services that connect people.

The question is, “how?” How do design thinkers arrive at game-changing insights? They explore many options, collecting insights along the way. They head for the edges, the places where they might expect to find extremes. They talk not just with the “average Joe” who may have a useful perspective, but with people who may have unusual or extreme perspectives. They enrich their perspectives by exploring associations and relationships in seemingly unrelated data sets. They synthesize multiple, differing points of view.

Design thinkers need to be able to ask questions and explore data on their own to find answers and generate insights. They might ask, “Which of our active customers are not purchasing our most profitable products?” or “What would happen if we increased headcount in the factory by 10%?” They need tools to help them discover associations and intersections to uncover meaning in data.

Business intelligence software products—specifically, Business Discovery platforms—give design thinkers a way to explore seemingly unrelated data, make connections, and derive insights. Business Discovery platforms enable design thinkers to explore anomalies in the data. They dig into data points at the edges of a scatter chart to explore the “why” behind the highest highs and lowest lows on a related bar chart. One insight leads to the next as seemingly insignificant details accumulate.

Important decisions must ride on more than hunches. Design thinking supported by Business Discovery platforms can drive innovation throughout an organization. With Business Discovery platforms, new concepts and solutions can begin to take shape as insights become clear.

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A common notion is that when it comes to business intelligence, agility and governance are mutually exclusive. But this is a misperception. I talked about this recently with Johan Averstedt, segment manager for financial services at QlikTech, and Elif Tutuk, technical expert, and they had some great insights to share.

With QlikView You Can Have Both Agility and governance.png

 

The conundrum

Large organizations―especially in highly regulated industries like financial services―have an extreme need for data governance. The health and wellbeing of the business can be negatively influenced by people making decisions based on numbers that are not quality-controlled. At the same time, business moves very fast, making it nearly impossible for IT organizations to provide business users with all the data they need to get their jobs done. To make the decisions they need to make, business users go out and get data on their own and analyze it using spreadsheets and other productivity tools.

The question is: how do you create an environment where governance and agility co-exist? Where the data that must be controlled and protected is taken care of, and users still have the ability to obtain and work with their own data as needed? Where business users can ask—and answer—cross-functional questions?

A solution: a Business Discovery environment with analysis sandboxes

In the large financial services organizations he works with, Johan Averstedt often sees a scenario in which data wranglers harmonize and rationalize data for power analysts, collaborative users, and netizen users. (See the related post “Self-Service BI: Power to ALL the People.”)

The data wrangler’s role is to determine if data is correct. These business users tend to be people who deal with risk on a daily basis. In banking, they may be in middle office roles like financial risk control or product control. In insurance, they may be actuaries. But they could be business or IT controllers in any part of the organization.

The data wranglers use QlikView to create an environment where they can conduct one-off analyses and monitor data over a period of time. We think of this as an analysis sandbox. (See related blog posts “Analysis Sandboxes: Indispensable Tools for Insight Discovery” and “Analysis Sandboxes the QlikView Way.”)

The data wranglers invite a selected group of other business users to “play” in the sandbox. They bring the data they want to work with into QlikView from spreadsheets, web feeds, etc., and the data wrangler spends time with the data to make sure it is correct.

Groups of people who perform this local analysis often come up with ideas that may be valuable for a larger group. These good ideas can then be channeled back to IT for use in bigger, more formal Business Discovery projects that are deployed to a larger community. Data wranglers may work with IT to make the data more broadly available to an appropriate set of users by creating a QlikView data file (QVD) layer from which QlikView apps (QVWs) can be built.

QlikView-based analysis sandboxes for data wranglers, and the power analysts and collaboration users they work with, deliver the needed combination of governance and agility.

Visual thinking is an important aspect of design thinking; designers have always evolved visual ways to synthesize ideas. Visual thinking also applies to data analysis.

 

To support design thinking data visualization should not only provide clear and effective communication of information but should also be intuitive, and help people ask and answer their own questions.  Data analysis tools should provide extensive choices when it comes to visualization options because different data analysis scenarios require different visualizations. (See related blog posts “Build to Think: Applying Design Thinking to BI” and “QlikView Supports a Build to Think Approach to BI”.)

 

QlikView extension objects - Fig 1 (2).png

 

QlikView extension objects open up a virtually endless array of visualization and other customization opportunities. (See related blog post and video, “Boundless Visualization Options.”) I see extension objects as a great way of applying design thinking to data analysisit is like having multiple front doors to your house, each one of which opens up to a different city in the world. You can step out through any door and begin exploring the world around you.

 

QlikView extension objects - Fig 2 (2).png

 

Extension objects work like any other QlikView object. They work in both the desktop and Ajax clients and take full advantage of core QlikView functionality like the associative experience. Extension objects provide the same user experience as native QlikView visualization objects, so no additional user training is required.

 

Developers can create their own visualization objects to meet specific customer and partner needs, or can import them from third-party chart and visualization libraries like FusionCharts or Stanford Visualization Protovis. Extension objects are also easy for business users to incorporate into their applications; all they have to do is double click on a .QAR file the developer has created and add the extension object to the QlikView app, just as they would any other QlikView object.

You can find more info about QlikView extension objects by searching for the word “extension” on QlikCommunity. Soare you ready to step into the new world of visual thinking?

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