Note: the following post is republished with permission from Technology Evaluation Center’s excellent blog. It is a part of a series of interviews by Jorge Garcia on trends in the analytic industry.

It is hard to imagine that organizations like SAP or former Business Objects (BO)—now a division of SAP—were once start-up companies. Nowadays on the business intelligence (BI) scene it’s almost impossible to avoid BusinessObjects. Like many other successful companies, SAP has grown into itself by offering a product that applied a radical approach to a business problem solution, and this is particularly true of its BusinessObjects stack of BI solutions. In this installment of my Thinking Radically interview series, I had the pleasure to speak with Timo Elliott, a prominent personality in the BI space.

Mr. Elliott was one of the first employees of the original French company Business Objects, which SAP acquired in 2007. He has held various positions, including Senior Product Director for SAP BO. With vast experience in the BI arena, Mr. Elliott is now part of SAP’s elite squad of “technology evangelists.”

Below, he comments on the past, present, and future of BI and SAP’s analytics products and technologies.

Hello, Mr. Elliott. Could you give us a brief overview of your career within the BI space and with SAP BusinessObjects?

TE: I’m a statistical economist by training, but when I left school, I wanted to see the world. I ended up working on an analytics project at Shell in New Zealand, with a makeshift system including a mainframe reporting tool, exports to Lotus 1-2-3, custom macros, and a pen plotter.

A few countries later, I joined Business Objects in 1991 as the eighth employee—prompted largely by the realization that the project that had taken me a month at Shell could be done in less than a day using SkipperSQL (as the BO product was then called).

I’ve had a variety of roles over the last 20 years, but one thing has been consistent: I’ve always been lucky enough to have a market-facing role, spending time understanding customers’ real-life information challenges. My role now is “technology evangelist”—I spend a lot of time at conferences and using social media, doing my part to explain new BI technology and how to achieve its full benefits.

Back in the early days of BO, what do you think it did that was so radically differently to be a leader in the BI space?

TE: Clearly, we had the right product at the right time: organizations had valuable information locked away in their databases, and you had to have technical knowledge to get it out (although Oracle at the time positioned SQL as an “English-like language” for power users). We pioneered the notion of a “semantic layer” that let business people access information using standard business terms and which automatically generated the complex SQL required to get the data from the database.

BO also benefited from great management from its founders, Bernard Liautaud and Denis Payre. They were determined to create a “Silicon Valley start-up” on the outskirts of Paris that included rapid expansion and a global vision. There were a few stumbles along the way, but in the end, it became the second European software start-up (after SAP!) to reach a billion dollars (USD) in revenue.

What are the main differences in the way organizations do BI now compared with how they did it in the past?

TE: Clearly, the technology has changed a lot over the years, but the business requirements remain remarkably similar: cutting costs, finding new opportunities, beating the competition, getting closer to customers… The biggest change is perhaps that BI is now clearly mainstream—only a tiny fraction of organizations don’t have some sort of BI in place, even if it’s only using spreadsheets.

What are the most common complaints from companies about what a BI solution should do but doesn’t?

TE: The dream of most organizations is to have a BI solution that just works—people believe strongly in the benefits of BI, but wish that it were easier to put in place robust solutions.

A new wave of technology, including in-memory techniques, holds the promise of making some of the processes much simpler. But many of the most intractable problems stem from business processes themselves (organizations with 20 different definitions of “customer” etc.), and are consequently much harder to fix. There’s also the problem of expectations: as soon as you provide better BI systems, business people can (and should) move on to new and even more difficult questions. I don’t believe people will ever be completely happy with their information systems (and if they were, it might be a sign that they needed more imagination!).

SAP is working hard to position HANA with its customers and in the market. Regarding its relationship with SAP’s BI stack of products, how can SAP HANA be a real game changer for SAP BO customers and SAP customers in general?

TE: SAP HANA combines a series of technologies (in-memory, column stores, in-database calculations, etc.) to create a truly innovative alternative to traditional BI infrastructures. Early customers are now starting to reap the benefits in the form of radically faster access to large quantities of data. This is allowing them to make better decisions, earlier, and more often, and fix potential problems in real time, rather than analyzing what failed in the past.

How does HANA modify the traditional BI cycle, and what is the impact on the business?

TE: I think the biggest benefit of HANA isn’t actually its speed—after all, every new generation of databases has been faster than previous versions. What’s different about HANA is the way it “collapses the layers” between data and analysis, and radically simplifies the implementation of new BI projects. When business people come up with a new analytic need, IT should no longer have to say, “Come back in six months when we’ve managed to get the data into the data warehouse.”

An analogy for how BI has changed would be the move from film to digital photography. In the old days, you’d have to buy film, load it into your camera, take pictures, send the film off to experts to get it processed, and after three days you’d get your pictures back—only to realize that they weren’t quite what you wanted. A lot of enterprise BI today works along exactly the same lines—as a business person, I have to rely on experts to get the solutions in place, it’s slow, and what I get back is often not quite what I need.

HANA is like the digital camera—it’s faster, but the real benefit is getting rid of the redundant layers in the process. Today, I can take a picture without an expert’s help, and if it’s no good, I can quickly take another while I still have the subject to hand: we’ve all become better photographers because of digital cameras, and better BI will be the result of in-memory technologies like HANA.

How about cloud computing? What is your view on SAP’s cloud service strategy, especially for BI and in light of SAP’s recent acquisition of SuccessFactors?

TE: It’s clear that cloud computing is the future, and it’s also clear that on-premise installations are going to be with us for a long, long time. SAP’s strategy of “orchestration”—helping organizations make the best use of the combination of technologies (increasingly including mobile)—sounds like the right approach to me. From an analytics point of view, BO was, and continues to be, a pioneer in on-demand business intelligence with our OnDemand platform, which now offers HANA-based BI in the cloud.

From your point of view, what is the difference between BI and business analytics, and the difference in the way they are applied by organizations?

TE: The “nomenclature wars,” as I call them, drive me nuts. People often conflate two things: the technology that is being talked about (this changes over time, requiring new terminology) and the underlying business needs that are being addressed (this doesn’t really change).

I read a lot of rubbish about how BI is “backward looking” and analytics is “forward looking.” I can assure you that BI has always been about actionable information. At the end of the day, what counts is using data to improve the way you do business. Call it whatever you like, but vendors in particular shouldn’t try to belittle what we’ve been doing for decades just because they have some new technology they want to sell.

What is your view on the general maturity level of businesses in regard to BI applications? Are there key areas for improvement organizations still have to address? Which ones?

TE: I present regularly on topics such as “why BI projects fail and what to do about it” and “how to implement BI competency centers.” Overall, there’s higher maturity in BI, but it’s widely scattered, with each new generation relearning most of the same lessons.

The key area of improvement that is required is to always remember that BI is about people and the business, not about the software architecture. The technology is, of course, often a challenge, but when BI projects fail, it’s almost inevitably a problem with organization, culture, expectation setting, and business alignment. If you run a BI project, you should be spending more time on these things than the underlying IT infrastructure.

What is your position regarding the adoption of big-data technologies (especially Hadoop) and SAP’s strategy for adopting these technologies?

TE: MapReduce, Hadoop, and related technologies have proven their worth in enterprise contexts surprisingly quickly, and every vendor in the BI space is busy providing tighter integration. The latest version of SAP’s Sybase IQ database has tight links with Hadoop, and you’ll see a lot more coming out this year, both in terms of integration and best practice (i.e., determining where it makes the most sense to use these new technologies).

What’s your vision for BI, your expectations for its future?

TE: As I sat down to gather my thoughts about BI in 2012, I quickly came up with the same long laundry list of BI topics as everybody else: in-memory, mobile, predictive, social, collaborative decision-making, data discovery, real time, etc.

All of these things are clearly important, and we’re going to continue to see great improvements this year. But I think that the real next big thing in BI is what I’m seeing when I talk to customers: they’re using these new opportunities to not only improve analytics, but also fundamentally rethink some of their key business processes.

Instead of analytics being something that is used to monitor and eventually improve a business process, I’m seeing analytics become a more fundamental part of the business process itself. One example is a large Telco company that has transformed the way it attracts customers. Instead of laboriously creating a range of rate plans, promoting them, and analyzing the results, it now uses analytics to automatically create hundreds of more complex, personalized rate plans. The plans are then thrown out into the market, monitored in real time, and those that aren’t successful are quickly culled. It’s a way of doing business that would have been inconceivable in the past, and will be a lot more common in the future.

What is your favorite wine?

TE: When at Business Objects we used our own technology to run things, we put a French spin on the phrase “eating our own dog food” and claimed that we were “drinking our own Champagne.” So that’s my answer!

Key texts:

• “Face-to-face conferences through television will be held coast-to-coast, and intricate calculations of quotas or sales by territories will be turned out at the touch of an assistant’s finger. Records will appear as if by magic from files automatically operated in the electronic age ahead.”
• “Television/telephone devices will eliminate distances”
• “All figuring will be done by miraculous electronic devices”.

Sure sounds like today’s analytics to me!

Ajay Ohri of DecisionStats.com has posted my email interview on Business Intelligence trends – you can read a copy below.

What do you think I missed?

Top five events in 2010:

(1) Back to strong market growth. IT spending plummeted last year (business intelligence continued to grow, but more slowly than previous years). This year, organizations reopened their wallets and funded new analytics initiatives — all the signs indicate that BI market growth will be double that of 2009.

(2) The launch of the iPad. Mobile BI has been around for years, but the iPad opened the floodgates of organizations taking a serious look at mobile analytics — and the easy-to-use, executive-friendly iPad dashboards have considerably raised the profile of analytics projects inside organizations.

(3) Data warehousing got exciting again. Decades of incremental improvements (column databases, massively parallel processing, appliances, in-memory processing…) all came together with robust commercial offers that challenged existing data storage and calculation methods. And new “NoSQL” approaches, designed for the new problems of massive amounts of less-structured web data, started moving into the mainstream.

(4) The end of Google Wave, the start of social BI. Google Wave was launched as a rethink of how we could bring together email, instant messaging, and social networks. While Google decided to close down the technology this year, it has left its mark, notably by influencing the future of “social BI”, with several major vendors bringing out commercial products this year.

(5) The start of the big BI merge. While several small independent BI vendors reported strong growth, the major trend of the year was consolidation and integration: the BI megavendors (SAP, Oracle, IBM, Microsoft) increased their market share (sometimes by acquiring smaller vendors, e.g. IBM/SPSS and SAP/Sybase) and integrated analytics with their existing products, blurring the line between BI and other technology areas.

Top three trends next year:

(1) Analytics, reinvented. New DW techniques make it possible to do sub-second, interactive analytics directly against row-level operational data. Now BI processes and interfaces need to be rethought and redesigned to make best use of this — notably by blurring the distinctions between the “design” and “consumption” phases of BI.

(2) Corporate and personal BI come together. The ability to mix corporate and personal data for quick, pragmatic analysis is a common business need. The typical solution to the problem — extracting and combining the data into a local data store (either Excel or a departmental data mart) — pleases users, but introduces duplication and extra costs and makes a mockery of information governance. 2011 will see the rise of systems that let individuals and departments load their data into personal spaces in the corporate environment, allowing pragmatic analytic flexibility without compromising security and governance.

(3) The next generation of business applications. Where are the business applications designed to support what people really do all day, such as implementing this year’s strategy, launching new products, or acquiring another company? 2011 will see the first prototypes of people-focused, flexible, information-centric, and collaborative applications, bringing together the best of business intelligence, “enterprise 2.0”, and existing operational applications.

And one that should happen, but probably won’t:

(4) Intelligence = Information + PEOPLE. Successful analytics isn’t about technology — it’s about people, process, and culture. The biggest trend in 2011 should be organizations spending the majority of their efforts on user adoption rather than technical implementation.

More content from Decisionstats.com:

• See the views of James Kobelius
• See the views of Jill Dyche

I attended the IDC BI Roadshow today in Prague, in the Czech Republic. Tom Vavra, the IDC research director for the CEMA region, started off the day with a presentation entitled “The Next Wave of Business Intelligence”. He was under unusual pressure, because (1) his family was in the room, and it was the first time they’d seen him speak, and (2) part of the room fell on another IDC employee in the middle of his speech (he literally “brought the house down”).

The presentation was full of interesting BI data nuggets, including:

• CEE IT spending dropped 13% in 2009, but returned to a predicted 10.9% growth in 2010 (Czech spending didn’t fall as fast, and won’t jump back as quickly – expected 6.4% growth this year).
• Business analytics was one of the only areas that still experienced WW growth (of 2.5%) last year.
• Interestingly, “new and exciting” advanced analytics only grew +0.6% last year, compared to “boring old” query and reporting’s +2.9% and data warehousing’s +2.5%
• BI is the #4 in European IT spending priorities after improving service quality, IT security, and IT cost reductions.
• In CEMA survey last year, 62.9% said number of users set to expand over the coming year. 34.6% said no change, only 2.5% saw a decrease.
• In terms of types of BI that companies are deploying, #1 was dashboards, followed by multidimensional analysis, collaboration, mobile devices, reporting, statistical analysis, search, and text analytics.

Tom showed how far we still have to go in using BI to actually support decision-making. When asked, business people cited the following, in order of importance:

• Attachments in email
• Phone conversations
• In-person meetings
• Emailing links to content
• Team workspaces
• Shared applications

The top two pain points of making decisions will be familiar to anybody who has used or implemented BI systems:

• Having to launch multiple disconnected applications
• Ability to find relevant information

But further down the list are some indications of areas where BI has to mature to become true DSS or decision-support systems (as the industry was known when I first joined it twenty years ago).

• Storing my thoughts with the information for future reference
• Knowing how a decision actually affected a project
• Ability to find colleagues with relevant knowledge / skills

Technology used for decisions – email attachments, phone conversations, in-person meetings, emailing links to content centrally, team workspaces, shared applications

Tom went on to cover changes to the BI landscape. The first is BI consolidation, with the WW BI tools revenue share of the top 10 vendors rising inexorably every year from 2003 (~58%) to 2009 (~74%). The second is the rise of on-demand or software-as-a-service BI, predicted to rise at 22.4% CAGR 2008-2013, compared to the general business analytics software market of “only” 7.2%

Next up was Dai Clegg, the EMEA Marketing Director for Netezza, who presented the benefits of their data warehouse appliance product:

“We do one thing, and hopefully we do it very well… we invented it, we deliver it, and we mean it: i’t’s a piece of equipment that you can just plug in, and it does the job” (Netezza’s 400 employees and $200M-growing-at-45% revenues are in the process of being acquired by IBM)

Dai did a good job of vaunting the benefits of the solution (but once you’ve said “it uses hardware/parallel processing/memory technology to go faster” there’s not necessarily that much to say of interest to a general BI audience).

Thirty minutes into the 25-minute slot, Kamil Matuska, the DW manager of T-Mobile in the Czech Republic was invited up to explain how his team had used the product. He uses a relational data warehouse with SAP BusinessObjects, and the Netezza appliance is currently operated in parallel, and has resulted in dramatic performance increases (operational reporting from several hours down to seconds). He hopes to be able to operate the data warehouse directly on the Netezza appliance within the coming year.

I liked this, from the Netezza brochure: “procedure for deploying a Netezza” (there’s not enough humor in enterprise applications!)

After the break, I gave my vendor-neutral Clear Intelligence future presentation (a 25 minute version), which can be downloaded as a PowerPoint file or a PDF document.

After my presentation, Evgeny Velesevich, an ex-Cognos employee, now in charge of sales in the CEE for IBM, talked about the IBM sales analytics package.

The presentation was a little heavy on sales information, but he did make the point that most organizations believe that they have to “build their own”, that they are uniquely qualified to put a BI solution together – which is a bit like building your own car: it might have been necessary a hundred years ago, but now most of us prefer to buy our cars as a complete package, because other people can do it much better than we could ever hope to be.

Finally, some HDR photos I took in Prague…

The next IDC CEMA BI Roadshow session I’ll be presenting at is in Moscow, on November 18th and then Athens, on November 19th (I think).

It was the Skyrr Fall Conference in Reykjavik a couple of weeks ago, and among the long list of sessions, I covered three topics:

• An evening executive session on “Why BI Projects Fail and What To Do About It”
• A vendor-neutral BI Trends keynote “Simple, Seamless, Social, and Strategic”
• An SAP BusinessObjects breakout session “Information to Insight”

Here’s the video of the keynote:

All the presentations are available for download (in PowerPoint format) below — please don’t hesitate to reuse the slides (if you do, please recommend this blog to your audience).

If you do ever visit Reykjavik, you MUST visit the blue lagoon. It’s possible to take a taxi from town to the pool, store your luggage, do a proper visit and swim, and take a taxi to the airport in just under two hours. It’s as amazing as it looks (although the pictures don’t convey the occasional whiff of sulphur/rotten eggs)

Finally, just to show that data quality problems are ubiquitous – in real life, data gets manually copied all the time, with the inevitable errors… Remember (for the sake of the children!) to include data quality in your BI project

I gave a presentation in Finland earlier this year as part of the Nordic “Butterfly” tour, talking about the future of Business Intelligence:

Ever since the first abacus, information technology has been an essential part of delivering timely information, staying accountable to stakeholders, reducing inefficiencies, and flexibility when faced with fast-changing environments. But for the first time in history, consumer technology interfaces have been outpacing what’s available to the average corporate knowledge worker.

How can we combine the best of enterprise technology and Web 2.0 to build greater visibility, transparency, and accountability into the way organizations work? Business intelligence technology needs to meet the demands of tomorrow’s “digital natives”; integrate seamlessly with cloud data and platforms; align people, conversations, and data with business strategy; and make the most of the infrastructures we have today:

• Simple: the right interfaces for the right people at the right time
• Seamless: tightly integrated with data sources, applications, and business processes
• Social: allow people to collaborate around analyzing information and making decisions
• Strategic: closing the loop between strategy to execution

The feedback from the audience was very positive, and so we’ve taken the 45-minute presentation and posted it to YouTube as a series of short, single-topic sections (see below). The presentation is available for download as an Adobe PDF document, and as the original PowerPoint presentation file.

The conference also included a more detailed BI presentation (not recorded) that focused on more leading-edge future BI topics such as social network analysis and augmented corporate reality. It is also available for download as an Adobe pdf file, and as a PowerPoint presentation file

Take a look, and if you find it interesting, please share with others in your organization! (and if you are interested in a tailored BI vision presentation for your company or conference, please contact me at telliott@timoelliott.com)

[Update: There’s now a nice convenient viewer for the various videos available:]

Part 1 Introduction (3:12 min)

Summary:

• High-level BI trends
• Brief summary of BusinessObjects porfolio

Part 2  Simple (9:05 min)

Summary:

• Taking BI to the next level: Simple
• Roadblocks to success
• Taking cues from the consumer world
• BI interfaces that you don’t need training to use
• Japanese picnics

Part 3 Simple Continued (4:23 min)

Summary:

• Adapting interfaces to end users
• Other interfaces, including mobile devices
• Going faster

Part 4 Seamless (9:33 min)

Summary:

• Taking BI to the next level: Seamless
• The importance of data
• Bridging the gap between central and personal data
• Text analytics
• BI OnDemand
• Embedded BI
• “Automagical” Text to Query

Part 5: Social (5:07 mins)

Summary:

• Taking BI to the next level: Social
• Collaboration is important
• Spitfire Marine example
• StreamWork demonstration

Part 6: Strategic (9:26 min)

Summary:

• Taking BI to the next level: Strategic
• Budgeting and finance
• Financial vs. other Risk
• Sustainability performance management
• Business applications of the future
• Conclusion

Here’s an interview he did with me last week covering trends in predictive analytics, cloud computing, social network analysis, etc.

Timo- I studied economics with statistics in the UK, but I had always been a closet geek and had dabbled with computers ever since I was a kid, starting with Z80 assembler code. I started my career doing low-level computer consulting in Hong Kong, and worked on a series of basic business intelligence projects at Shell in New Zealand, cobbling together a solution based on a mainframe HR system, floppy-disk transfers, and Lotus 1-2-3 macros. When I returned to Europe, I stumbled across a small French startup that provided exactly the “decision support systems” that I had been looking for, and enthusiastically joined the company.

Over the last eighteen years, I’ve worked with hundreds of companies around the world on their BI strategy and my job today is to help evangelize what works and what doesn’t, to help organizations avoid the mistakes that others have made.

When it comes to BI initiatives, I see the results of one fundamental problem almost on a daily basis: 75% of project success depends on people, process, organization, culture, and leadership, but we typically spend 92% of our time on data and technology.

BI is NOT about technology – it’s about helping people do their jobs. So when it comes to education, we need to teach our technologists more about people, not science!

Ajay- You were the 8th employee of SAP Business Objects. What are the key turning points or transition stages in the BI industry that you remember seeing in the past 18 years, and how has SAP Business objects responded to them.

Timo- Executive information systems and multidimensional databases have been around since at least the 1970s, but modern business intelligence dates from the early 1990s, driven by the widespread use of relational databases, graphical user interfaces, and the invention of the “semantic layer”, pioneered by BusinessObjects, that separated business terms from technical logic. For the first time, non-expert business people had self-service access to data.

This was followed by a period of rapid expansion, as leading vendors combined reporting, multidimensional, and dashboard approaches into fully-fledged suites. During this period, BusinessObjects acquired a series of related technology companies to complete the existing offer (such as the leader in operational reporting, Crystal Reports) and extend into enterprise information management and financial performance management.

Finally, the theme of the last few years has clearly been consolidation – according to Gartner, the top four “megavendors” (SAP, IBM, Microsoft, and Oracle) now make up almost two-thirds of the market, and accounted for fully 83% of the growth since last year. Perhaps as a result, user deployments are accelerating, with usage growth rates doubling last year.

Ajay- How do you think Business Intelligence would be affected by the following

a) Predictive Analytics.

Timo- Predictive analytics has been the “next big thing in BI” for at least a decade. It has been extremely important in some key areas, such as fraud detection, but the dream of “no longer managing by looking out of the rear-view mirror” has proved hard to achieve, notably because business conditions are forever changing.

We offer predictive analytics with our Predictive Workbench product – but I think the real opportunity for this technology in the future is “power analytics”, rather than “prediction”. For example, helping business people automatically cluster similar values, spot outliers, determine causal factors, and detect trend inflection points, using the data that they already have access to with traditional BI.

b) Cloud Computing.

Timo- In terms of architecture, it’s clearly not about on-demand OR on-premise: it’s about having a flexible approach that combines both approaches. You can compare information to money: today, we tend to keep our money in the bank rather than under our own mattress, because it’s safer, more convenient, and more cost-efficient. At the same time, there are situations where the convenience of cash is still essential.

Companies should be able to choose a BI strategy, and decide how to deploy it later. This is what we offer with our BI on-demand solutions, which use the same technology as on-premise. You can start to build on-premise and move it to on-demand, or vice-versa, or have a mix of both.

In terms of data, “cloud intelligence” is still a work in progress. As with modern financial instruments, we can expect to see the growth of new information services, such as our “information on-demand” product that provide data feeds from Reuters, Thompson Financial, and other providers to augment internal information systems. Looking further into the future, we can imagine new information marketplaces that would pay us “interest” to store our data in the cloud, where it can be adapted, aggregated and sold to others.

c) Social Media.

Timo- Conversations and collaboration are an essential part of effective business intelligence. We often talk about the notion of a “single view of the truth” in this industry, but that’s like saying we can have “a single view of politics” – while it’s vital to try to give everybody access to the same data, there will always be plenty of room for interpretation and discussion. BI platforms need to support this collaborative decision-making.

In particular, there are many, many studies that show up our all-too-human limitations when it comes to analyzing data. For example, did you know that children with bigger feet have better handwriting?

It’s absolutely true — because the children are older! Mixing up correlation and causality is a common issue in business intelligence, and one answer to the problem is to add more people: the more reviewers there are of the decision-making process, the better the decisions will be.

Analysis is also critical to the development of social media, such as analyzing sentiment trends in Twitter — a functionality we offer with SAP CRM — or tracking social communities. For example, Jive, the leader in Enterprise 2.0 platforms, offers our BI products as part of their solution, to help their customers analyze and optimize use of the system. Administrators can track if usage is trailing off in a particular department, for example.

d) Social Network Analysis.

Timo- Over the last twenty years, partly as a result of extensive automation of operational tasks with systems such as SAP, there’s has been a huge shift from “routine” to “non-routine” work. Today, fully 90% of business users say that their work involves decision making, problem solving, and the creation of new analysis and insight.

To help support this new creativity, organizations are becoming more porous as we work closer with our ecosystem of customers, partners, and suppliers, and we work in ever-more matrixed environments and cross-functional teams.

We’ve developed a Social Network Analyzer prototype that combines BI and social networking to create a “single view of relationships”. It can gather information from multiple different systems, such as HR, CRM, email distribution lists, project teams, Twitter, etc., to create a multi-layered view of how people are connected, across and beyond the enterprise. For more information, see the SAP Web 2.0 blog post, and you can try it yourself on our ondemand.com web site.

Ajay- What is the area that SAP BusinessObjects is very good at (strength). What are the key areas that you are currently seeking to improve ( opportunities)

Timo- Companies evaluating BI solutions should look at four things: product functionality for their users’ needs, fit with the overall IT architecture, the vendor’s reputation and ecosystem, and (of course) price. SAP BusinessObjects is the clear leader in the BI industry, and I’d say that SAP BusinessObjects has the best overall solution if you’re a large organization (or looking to become one) with a variety of user needs, multiple data sources, and a heterogeneous IT infrastructure.

In terms of opportunities, we have high expectations for new interfaces for casual users, and in-memory processing, which we have combined in our SAP BusinessObjects Explorer product. Initial customer feedback has been excellent, with quotes such as “finding information is as easy as using the internet” and “if you can use a computer, you can use Explorer”.

In terms of future directions, we’re taking a very transparent, Web 2.0 approach. The SAP BusinessObjects innovation center is modeled on Google Labs and we share our prototypes (including the Social Network Analyzer mentioned above) with anybody who’s interested, and let our customers give us early feedback on what directions we should go.

Ajay- What does Timo Elliott do for work life balance when not writing, talking, and evangelizing about Business Intelligence?

Timo- I’m a keen amateur photographer – seetimoelliott.com/personal for more!

Highly Relevant

Memory Spot. This miniature wireless data chip, 2mm to 4mm square, can be stuck on, or embedded in, any object. Prototypes of the chips can hold as much as 4Mbit and future versions are expected to store several megabytes. Relevance to BI: Seems curiously undersold in the Computerworld article (movie trailers on posters?!). RFID on steroids: when combined with cheap sensors, this would potentially allow any object to store vast amounts of information about itself and its interaction with other devices.

Apollo (honorable mention). This cross-operating system application runtime allows Web developers to use their existing skills to build and deploy rich Internet applications on the desktop, so users can engage with Web applications even if there is no Internet connection. Relevance to BI: BI is a great example of environment that needs to seamlessly switch between thin-client online access (accessing an alert) and rich local functionality (drilling down into causes) — expect to see Apollo or similar technologies take an increasing role in BI interfaces.

Data Governance

One of the winners and three of the “honorable mentions” are directly relevant to BI and data security. The phrase “Information is Power” is truer than ever, organizations are becoming increasingly porous, and it’s no longer enough to put in place simple restrictions. Basic access security is giving way to data governance, including the management of the complex real-life relationships between information and users. Healthcare is a great example — there are many, many different people that require some sort of access, there has to be privacy for individuals, but the same data is essential for clinical analysis — how can you ensure that researchers can never get enough data to compromise an individual’s privacy?.

Data governance will spawn an entire new industry. Tighter controls over data storage, archiving, and transmission, and managing identities and relationships will all be part of it. (By the way, just in case anybody is still fooled, retention policies are really “deletion policies”. Especially with new text analytic technologies, any incautious emails and documents can come back to haunt you. Don’t write anything, ever, that you wouldn’t like to see published on the web.)

An Identity Passport. This combination of services and software helps consumers manage their online identities and ensure security of online transactions, with a goal of creating a universally accepted identity system for consumers across all Web sites, similar to a passport. 

DataDefender. This information leak-stoppage appliance uses a digital fingerprinting algorithm to monitor information traffic and block confidential information from leaving the network. The tool combines insider threat management technology, including real-time breach monitoring and remediation capabilities.

Security Suite. BitArmor protects, tracks and manages data throughout the company at wire speed so users won’t notice any delay. The software protects data on laptops, desktops and application servers, and can seamlessly encrypt, classify, apply retention policies to, suspend access to and destroy any data stored anywhere in the organization. 

ActiveSentry .  This intelligent desktop security software prevents employees from accidentally or maliciously distributing private data to the outside world. ActiveSentry monitors a broad array of distribution methods, including e-mail, instant messaging, blogs, file transfer, printing and removable storage devices, such as memory sticks or CDs. Uses ContextIQ, a context-based engine that automatically understands a user’s intent or meaning and triggers real-time alerts.

Of Interest

Smart Talker. This intelligent command engine bridges natural language and computer language, allowing machines to “understand” the actual meaning embedded in a sentence. Relevance to BI: If it works, very relevant — but decades of previous failed attempts means that it should be taken with a pinch fistful of salt (will we ever interact directly with computers? will they be like Marvin or Eddie the shipboard computer?).

Web Surfing with Eye Gaze. EyePoint makes it possible for eye-gaze to be used as a viable alternative to a mouse. Relevance to BI: Part of the Matrix / Minority Report interface future?

Slice-and-Dice Dispersed Storage. Cleversafe slices, scrambles, compresses and disperses data over the Internet to disparate nodes (servers) on a grid. Relevance to BI: we’ll always be in the market for better, more secure storage of data

Power-Packed Memory. A memory compression technique that more than doubles the amount of usable memory in embedded systems such as cell phones without any changes to hardware, without any changes to applications, and with negligible performance and power consumption. Relevance to BI: today’s users expect data “ATAWAD” — any time, any where, any device. Anything that boosts device memory can only help speed mobile BI deployments.

Who Cares?

Wearable Gadgetry. Users can see schedules, phone numbers, addresses and recent e-mail messages without having to start up their laptops. Relevance to BI: Drill on alerts embedded in your jacket sleeve? I think not.

The Everywhere OS. Ghost moves the operating system onto the Web, providing users with a Ghost virtual computer — a free PC environment accessible from any browser.  Relevance to BI: ghostly, at best.

Observation Grid. Globus Medicus is a robust and user-proven method for sharing 3-D medical images on a grid. Relevance to BI: better network speeds? ho-hum.

SC 5832 (honorable mention). This complete cluster node on a chip. A SiCortex cluster node with DDR-2 memory consumes less than 20 watts of power, an order of magnitude less than the 250 watts used in a conventional cluster node, dramatically improving communication latency and bandwidth. Relevance to BI: so it’s faster, smaller, and greener — but what else do we expect?