BI Scorecard Blog

Tableau: On a Mission for Everyone to See and Understand Data

By Cindi Howson, BI Scorecard

Tableau continues strong momentum in visual data discovery and outlines its themes for its next release

The Tableau conference rocked Seattle last week with a record 5500 customers, partners, and employees in attendance. Tableau has rapidly become the darling of Wall Street and data lovers, growing at a rapid 82% year-over-year, faster than any other BI vendor. And yet, co-founder and vice president of product development Chris Stolte says, "We're in inning number one. We are constantly thinking about what's the next big thing we need to address to fulfill our mission" to help the world see and understand data.

Their Secret to Success

Tableau's success to date can be explained by three main factors: ease of use, agility, and visualization. BI adoption has been stubbornly flat for years, in part held back by hard-to-use tools that remained predominantly in the hands of power users. Tableau is easy to deploy, easy to learn, and easy to use. At the same time, the need for faster access to data, new data sources beyond a centralized data warehouse, and a fiercely competitive business environment have led agility to trump perfectly architected. As one customer summed up at the conference this week, "Business questions have a shelf life." The window of opportunity from a decision or insight seems increasingly shorter. Finally, while many BI tools have long supported the ability to create charts, Tableau's charts have been the primary display rather than an afterthought. With its origins in Stanford and Disney's Pixar, their visualizations have combined entertainment with expertise in visual perception. A number of other visual data discovery vendors, namely Qlik and TIBCO Spotfire, have gained traction for these same three reasons, but with varying strengths. In the last few years, BI platform vendors have been adding visual data discovery capabilities to their portfolios, but it is hard to hit all three high notes equally well. And Tableau has had an eight-year head start.

Key Investment Areas

Much of the product news centered on incremental improvements, with perhaps one item I would dub a break through. CEO Christian Chabot kicked off the keynote declaring the company is on track to invest more R&D in the next two years than it did in the last ten. He outlined seven main investment areas:

1.    Visual Analytics

2.    Performance

3.    Data preparation

4.    Storytelling (see my article on 4 approaches to storytelling)

5.    Enterprise

6.    Cloud

7.    Mobile

Here is my take on three of those areas.

Data Preparation

The three areas that most got my attention were data preparation, enterprise enablement, and mobile. In the era of big data and agility, business needs access to more data sources, faster. Data can come from the web, machines, suppliers, and customers. That data can be messy. Tossing it over to IT for extensive ETL does not lend itself to agility. Giving business users the ability to do simple clean up, such as split columns or unpivot crosstab tables is a better approach, particularly for departmental data sources and/or data sources of unknown value. These are areas that competitors SAP (in Lumira) and Microsoft (in Power Query) have been a step ahead of Tableau. The biggest wow, though, was the ability to take web-based data with blank rows, merged cells, and distributed tables (think of an SEC 10Q) and import it into Tableau in a single click. While I was impressed with the demo, I will remain skeptical that it's truly that easy until I've tested it.

At first blush, I thought the new data prep features could be bad news for partners Alteryx, Paxata, and Trifacta. But these vendors are able to do such business data preparation across multiple data sources, whereas Tableau seems to be working off a single source.

Visual Data Discovery Across the Enterprise

Enterprise enablement and balancing control with freedom was a theme of many of the track sessions at the conference. Customer Deloitte is one of the largest deployments, with 40,000 named users. Maintaining permissions for so many users is not an easy task in any BI tool. Here, Tableau showed how they are using their visualization expertise to better help administrators visualize those permissions and usage. The following image shows a screenshot of a heatmap of user permissions and how they got it: either explicitly or inherited via a group membership.

Mobile

Mobile has been an area of relative weakness for Tableau. Customer Ancestry.com cited limitations in mobile as a specific reason they have multiple BI tools. Tableau expects to add offline capabilities in the next release, with a scheduled synchronization. However, the initial release for the offline dashboard is expected to be static. The company also introduced project Elastic. In their mission to help all people use their data, Tableau is targeting mobile users who receive tabular data via email, Dropbox, or apps that use Health Kit on a tablet device. Project Elastic is a Tableau app that takes that tabular data and immediately renders it as a bar or line chart. Users can swipe the data to filter and drill. This app goes far beyond the current business user base to casual consumers.

Room for Improvement

Tableau is focusing on improving its core capabilities, but I was disappointed there was no mention of Search or of better scheduling options. Customer Facebook gave a presentation on how they have developed their own scheduling solution and intends to share it with the community via their blog. Other attendees were frustrated by the lack of clarity on release dates and capabilities, a transparency they have enjoyed in the past when the company was privately held. In this regard, Tableau has said that its next major release, version 9, will ship in the first half of next year. They won't say for sure what's in that release as they have moved to a more agile development methodology.

Combining Inspiration and Education

As user conferences go, Tableau knows how to capture the spirit of a passionate group of customers. It's not just an educational and networking experience; it feels more like a pep rally, with Tableau employees manning the conference. Quite frankly, it is reminiscent of a number of BI conferences before the industry consolidation in 2008. One of my favorite parts is the Tableau Doctor where developers meet one on one with customers on their particular questions and dashboard designs. The guest speaker keynotes were inspiring, starting with Dr. Tyson, host of the Cosmos TV series, talking about telling stories with science. Author Michael Lewis (Moneyball, BlindSide, and Flash Boys) shared his experiences with disrupters and the backlash when people don't like what the data is saying. (Did you know the Blind Side almost wasn't made, as producers cited no commercial potential? The film was bootstrapped?!) I missed author John Medina of Brain Rules, but his book is a must read for understanding how we learn, think, and retain information. And for those of us who wish we could clone ourselves to attend competing track sessions, all of them were recorded to be viewed on demand post conference.

Getting Girls into IT: Don’t Blame Silicon Valley

By Cindi Howson, BI Scorecard

Since Silicon Valley released their diversity numbers in June, I've watched the reactions with a mixture of optimism and dismay. As a woman in IT, the disclosures have heightened my hope that there will be a more concerted effort to improving diversity. But I'm dismayed that everyone is blaming Silicon Valley when the blame lies squarely with the girls, present party included.

Girls Are Leaving IT, so the Boys' Club Grows

Women once accounted for 37% of computer science degrees in the mid 1980s, to now less than 20% (source: NCWIT.org).

Yet people are crying foul about the low representation of women in high tech companies, particularly in technical jobs and leadership roles. Complainers are saying the Silicon Valley demographics should reflect their respective customer base. Um, is anyone demanding more female car mechanics simply because more women drive cars? I don't think so.

Company	Women in Tech Jobs	Women in Leadership	Women Overall
Apple	20%	28%	30%
Facebook	15%	23%	31%
Google	17%	21%	30%
Twitter	10%	21%	30%
Yahoo	15%	23%	37%
SAS	30%	35%	40%

(source: table at http://pxlnv.com/blog/tech-company-diversity-stats/ and individual company web sites).

Sparking an Interest Earlier

Part of the problem is that these next-generation companies say they represent a meritocracy, where all have equal opportunity and succeed on merit, versus the old-boys network. Frankly, I think there is an equal opportunity for women, but not an equal interest or awareness. My niece, who will be starting her degree in Computer Science at Northeastern University in Boston this fall, is a prime example of why girls are not majoring in computer science. Jennie has always been a math whiz and gadget girl. She could command the table in Poker, assemble a 1000-piece puzzle or Lego set faster than anyone. But until she began looking at colleges, she was never aware of computer science as a particular field to major in. A campus tour sparked her curiosity and led to her taking a class in computer science her senior year in high school. It bothers me that her guidance counselor never before suggested the class. Bothers me too that she was but one of only 3 girls in a class of 14, a record high at the school, and very much consistent with the Silicon Valley demographics. How can we expect girls to major in computer science when we aren't introducing them to the subject in high school?

And even though I work in IT now, my path to business intelligence and big data has not been a direct one. I have always enjoyed and excelled at math, but my first passion was writing. As high school electives go, my high school did offer a computer science class back in the 1980s, but no way would I have opted for that over a writing class. For sure, neither my counselor nor parents ever recommended computer science as a way to use my analytic skills. It was only through writing classes in college and multiple crashes of the then new Local Area Network, that I learned how to recover those 50-page documents I was so desperate not to retype. In my first job, writing and tracking proposals for a consulting company led me to discover Lotus 123, Dbase, and personal computers. An avid reader, I devoured user manuals and my career hummed along, self-taught with a few vendor-specific certifications. Yes, those Novell Network Administrator manuals were as engrossing as a Ken Follett spy novel. I did eventually go back to school and get an MBA in Management Information Systems; the rest is history.

Glimmers of Success

High tech firms are not the ones to blame here. In part, I fault our education system for not exposing students —girls and boys—to computer science at an earlier age. Given the U.S. Education system is so poorly ranked in the basics of math and science, perhaps it's too much of a stretch for them to tackle technology too. Here is where Silicon Valley can do more by offering after school clubs and early camps to interested students. A few groups have emerged in the last two years to address this challenge. For example, She++ started in 2012 at Stanford University for female computing engineers. She++ founder Ayna Agarwal was one of the Millenial speakers who kicked off SAP's Sapphire conference this year. Girls Who Code was also founded in 2012, and this summer offered camps in 19 tech companies around the country. Sponsors included some of those companies such as Twitter and Facebook who have recognized the diversity problem. And don't let the names of these organizations mislead you: coding is but only one possible job in information technology.

While college students seem pressured to declare a major increasingly earlier in their secondary education, I've been impressed with those universities that guide students to their talents and to the job opportunities. University of Texas System recently launched an application to provide prospective students, parents, and the public with access to data on degrees, salaries, and jobs. For example, the below bubble chart nicely shows the higher earnings for a grad in computer science (the blue bubble) versus an English major (the red bubble).

Silicon Valley could also take a page from software giant SAS, based in North Carolina. The company has long tracked its diversity numbers and been recognized as one of the best places to work by multiple rankings. Everything from flexible work hours, to on-site gym and day care, to keeping non-core jobs like landscapers in house pays off in attracting talent across multiple demographics. SAS does significantly better for women in tech and leadership roles (data for U.S. based employees only; global data not reported for international privacy laws), as the table below shows. At North Carolina State University, only 9% of computer science graduates are women, so SAS actively works with the university to foster interest through an R3 summer student program: Recognize, Recruit, and Retain. Women and minority students have the opportunity to work on projects to gain real-world experience in analytics and technology.

Company	Women in Tech Jobs	Women in Leadership	Women Overall
SAS	30%	35%	40%

The University of Miami also recently launched an initiative to pair current STEM college students with high schools in low-income neighborhoods. Students partner with high school teachers to enhance the curriculum, give guest lectures, and mentor high school students.

Hire a Girl … or Not.

Diversity is important for creativity and equal opportunity. Recognizing the problem is an important first step for companies recruiting and hiring, and the outcry from the published demographics has raised awareness. It's up to minorities – whether by gender or ethnicity – to seize the career opportunity. Silicon Valley and high-tech firms can partner with universities and high schools to spark minorities' interest in such careers earlier in their education.

Ultimately, I don't ever want to be hired because I'm a woman. I only want to be hired because I'm good at my job. For that to happen, we have to foster a more diverse talent pool, beginning in high school. Silicon Valley has a vested interest in making that happen; so do the girls.

Related articles

Quinn: Fixing Silicon Valley's diversity problem

EBay tops other Silicon Valley tech firms in gender diversity

The workforce demographics of Silicon Valley startups

What’s in a Story (and a Name)?

By Cindi Howson, BI Scorecard

Story telling capabilities are fast becoming table stakes in visual data discovery tools, but not all stories and storyboards are the same. Here's a look a look at four vendors' approaches.

It would be nice to think that most data analyses end with a value added decision or action. But really, many BI analyses end with a Power Point, finely tuned for board room presentations. Data is explored, analyzed, filtered, transformed, and then exported into a story telling medium where it becomes static. The PowerPoint may be used to support or refute a hypothesis or to provide a status update.

But what if that same data could remain within the BI tool, with board room presentation quality? Could those meetings of death by PowerPoint become more effective, interactive work sessions? Can the data be better presented not only to support a hypothesis, but also, to guide a decision-maker to a logical conclusion that compels action? This is the vision behind recent innovations in a number of visual data discovery tools. Tableau and Qlik call them story points and storytelling, respectively, SAP calls it storyboards and infographics. SAS, meanwhile, brings live integration within Power Point itself. While each vendor's feature has slightly similar names, the capabilities differ greatly.

Tableau: Story Points

Tableau released the concept of Story Points in version 8.2 in June this year. With a story, a user can insert a visualization onto a canvas, with the saved filters. The idea of story points is to provide users with the ability to present the data as a story, with a beginning, middle, and end. The banner of the canvas can include a long-text that is clickable. For example, in the below story, "Profits are increasing" is a clickable title. Multiple visualizations can be linked together to create a PowerPoint-like slide show. Within each page, users can adjust the filters. "The data tells you what's happening, but the story guides you to an understanding of why," Tableau says in its white paper, "Data Storytelling."

Qlik: Story Telling

Qlik Sense Desktop was released in July 2014 as a free, desktop visual discovery tool based on the vendor's next-generation interface. The vendor has not announced release data for Qlik Sense for the enterprise, currently in beta. In Qlik Sense Desktop, dashboards and individual visualization can be added to a story. Compared to Tableau, Qlik Sense has a few more bells and whistles to its stories. First, each page of the story can contain multiple visualizations and/or snapshotted images, with the drill point and filters saved. Also, there is an "effect" option that automatically recolors a chart so top (or bottom) performers stand out (in the below image, higher salaries are highlighted). Additional text can be added to the story, whether a simple annotation or a full paragraph. Images and shapes can also be added to the canvas to create a type of infographic. In play mode, each slide nicely transitions to the next. Dashboards remain interactive.

SAP Lumira: Storyboards and Infographics

Earlier this year, SAP added the concept of storyboards to Lumira. While the name may suggest similar capabilities to Tableau and Qlik story telling, in SAP, storyboards are better described as dashboards with multiple visualizations on a single page. Up until that release, Lumira lacked the ability to create these simple dashboards, a capability in most other visual data discovery tools. In addition to visualizations and filters, Lumira storyboards also support text boxes for titles or paragraphs, and images.

Meanwhile, in version 16, released in June this year, SAP added infographics— the ability to add pictograms and shapes to the storyboards. As shown below, there is also a preview ability to see how the infographic will appear on various devices. With infographics, users can also set the color options for the images, background, and some charts. This, of course, should be an expected feature in any BI tool but was lacking in earlier Lumira releases. The infographic capability is an interesting concept, but I found the capabilities too immature to replace PowerPoint. For example, in trying to add a callout, the callout does not natively support text; the text has to be added in a separate text box. As well, the callout pointer cannot be repositioned to connect to the particular image or outlier within the chart.

SAS Visual Analytics: Power Point

The SAS Add-In for Microsoft Office is a little-known but powerful add-in that lets users access and interact with BI content directly from within Excel, Outlook, and PowerPoint. With this approach, users create a visualization within SAS Visual Analytics. Then within PowerPoint, there is a Visual Analytics toolbar that lets them insert the visualization onto the PowerPoint canvas. The visualization is a direct query, not a static export, so it can be refreshed. Users have all the PowerPoint abilities to add text and additional images.

Stories: More to come?

While each of these innovations goes by a similar sounding name, the capabilities differ. All reflect a growing trend of how to better present data, findings, and inflection points into a cohesive story. I suspect story capabilities will continue to emerge in other visual data discovery tools. Like any first novel, I suspect the second releases of these stories will only improving over time.

 

Definitions

Dashboards: multiple visual indicators on a single page

Infographic: visual representation of information, used beyond quantitative data such as in subway maps, weather patterns, and so on

Story: collection of thoughts with a beginning, middle and end

Actuate: Can Free and Robust Spur Growth

By Cindi Howson, BI Scorecard

Actuate was once the king of production reporting. But the rise of self-service BI tools, BI suites, and industry consolidation made Actuate a bit player in the larger BI market. Over the past several years, the company has been re-inventing itself and hopes its new "fremium" iHub offering will allow it to capitalize on millions of BIRT developers.

Actuate is the sponsor of open source BIRT, the Business Intelligence Reporting Tool, used by an estimated 3.5 million developers. Actuate also have a complete BI solution, based on its iHub server, that customers can buy on a perpetual or subscription basis. Many of the BIRT developers are unaware of Actuate's broader BI offerings. Others find the move from free open source, to paid premium capabilities too steep.

With the iHub F-Type, customers get all the capabilities offered in the paid-for iHub server–interactive reporting, scheduling, security–for free. The catch? Customers are limited to 50 MB per day. The usage resets itself each day, and there's a nice thermometer to advise how much disk space is currently used by reports (note: screen shot below based on 500 MB license). Customers can then buy additional capacity at $500 per month per 50 MB.

The iHub F-Type also has a really nice pop up tutorial that guides the developer through the most compelling capabilities of the server. In the screen below, note the buttons on the left pane. The Interact button will show the developer how with the iHub F-Type, a previous static report is now interactive with a pop-up menu to sort or filter, requiring no new programming. The interactive reporting capabilities are a strong-point of the platform (see the BI Scorecard summary and detailed scores for more information), and a core aspect of self-service BI that many vendors are overlooking.

 

Pay-as-you Go the New Norm

Actuate is betting big on iHub F-Type. It's also betting big on a move to subscription-only pricing. Previously, Actuate offered both subscription and perpetual licenses. In the company's last quarterly investor call, CEO Pete Cittadini said that "going cold turkey to subscription … was the right thing to do." The move to subscription-based pricing is also a stated direction from competitor TIBCO in its acquisition of Jaspersoft in April this year. With BI cloud gaining momentum, customers and vendors alike seem more accepting of the pay-as-you-go model. I have always liked about subscription-based pricing for ensuring customers don't buy any more BI than they need, and conversely, for keeping a vendor focused on meeting the customer's needs. With perpetual licensing, customers risk shelf-ware and when dissatisfied with a product, the license is a sunk-cost with leverage only on a typical 22% annual maintenance fee.

Embedded BI: The Next Wave

Self-service BI and visual data discovery have been all the rage the last two years. These tools typically meet the needs of business analysts trying to mash multiple and new data sources together. At the other end of the user spectrum, front-line workers often consume data embedded within operational applications. In the past, reports and nuggets of data embedded within operational apps may have been custom developed. As these applications get refreshed, and with the growth of start-ups, embedded BI may be the next wave of BI growth. It is a BI segment that Actuate is specifically targeting, along with several other vendors: Jaspersoft, LogiAnalytics, Information Builders, and Oracle has identified this segment as a future direction.

To make embeddability easier, in Actuate's F-Type, an "Integrate" button nicely allows a developer to cut and paste the requisite Java Script into custom apps or portals.

 

Actuate may not have the mindshare of some of the bigger BI vendors, but they certainly have sown millions of seeds of developers. This latest offering seems a strong move to allow them to capitalize on that base of developers.

Lumira is the Headline but Enterprise BI, the Bread and Butter

By Cindi Howson

Please note: this blog site has been migrated and will be discontinued in the near future; please access new site at www.biscorecard.com/blog.

Sapphire this year was all about simplicity, the cloud, and millenials. That's the message that CEO Bill McDermott wanted to drive home in his keynote. BI, meanwhile, took a back stage to HANA and Cloud announcements.

At SAP, all roads lead to HANA, whether for BI or for transaction processing, on-premises or in the cloud. HANA is just three years old, and as an in-memory appliance, SAP has rapidly seeded the market with developers, fostered its partner network, and introduced new products that leverage the speed of in-memory. Customer Norwegian Cruise Lines spoke of how HANA allowed them to better analyze their data, faster than a previous data warehouse, and saving $700 million annually. Most interesting to me is how Norwegian Cruise Lines hadn't used anything from SAP before HANA, a proof point that HANA is not only for big ERP customers. The NFL with its fantasy football app is leveraging HANA, mobile, predictive, and Lumira to support its millions of fans, a customer base of millions and growing in the 25% to 50% range annually. Seoul University Hospital reduced its query time from hours to seconds, with a 147% return on investment in HANA. More importantly, CIO Dr. Hwang, said HANA allows them to analyze comments that were never before accessible.

While all the news with HANA seemed positively glowing, news on the leadership and BI front in particular was a bit more fractured. Last month, CTO Vishal Sikka abruptly resigned, amid speculation that he was frustrated the position of CEO was not in his future. In the BI space, two key people with Adam Binnie and Jason Rose also recently moved on. Insiders say the timing is coincidental. Outsiders worry about the impact on the BI roadmap for a product line that is one of the most complex in the industry. McDermott's vision for simplicity has a long way to go in BI.

Jayne Landry, newly appointed General Manager of BI and taking over from Binnie, outlined the BI roadmap. She conceded that for most BI segments, there are two, sometimes three, products (visual discovery includes Explorer and Lumira; dashboards includes Design Studio and Dashboards a.k.a. Xcelsius). The vision to simplify the product line was clear; the execution of how and when to get there was anything but.

Dashboard users were assured there would eventually be a migration utility to Design Studio, the strategic product, and in the interim, were told to check out a product from partner APOS. Landry conceded that killing Desktop Intelligence was a mistake. At issue is how to support existing investments, while focusing resources on moving forward. In empathy for SAP, who could have predicted that Apple would kill Flash, a technology on which Dashboards is based?

Long-time customers have been rightfully worried that SAP cares more about newer products HANA and Lumira than about the mature and broadly deployed SAP BusinessObjects. Judging from the headlines and excitement around these newer products, they might be right to worry. However, Landry shared a pie chart describing the company's three areas of analytics: enterprise BI, agile analytics, advanced analytics.

Category	Main Products	Developers	Release Cycle
Enterprise BI	SAP BusinessObjects Crystal Reports Dashboards Design Studio	600	6 to 12 months
Agile Analytics	Lumira Explorer	200	6 to 8 weeks
Advanced Analytics	Infinite Insight (KXEN) Predictive Analysis	100

Enterprise BI then is clearly getting the lion's share of development resources, but is indeed on a slower release cycle. Speaker Ty Miller, Senior Director of BI, likened Lumira to the shiny new Tesla—innovative engineering, new technology, disruptive— while the BI Platform is like the tried-and-true Porsche. It's an apt analogy.

It would seem then that it's not that SAP cares more about Lumira, but rather, that there's more frequent news as it's on such a rapid release cycle. To that end, the noteworthy new features in version 17 (due out this month) includes (refer to BIScorecard.com for a detailed review):

• InfoGraphics, an evolution to Stories that combines visualizations, with text and images, and a greater degree of formatting
• Direct connect to on-premises HANA and BW data from Lumira Cloud
• Support for MAC , with the beta available mid June

Customer Daimler Trucks gave a great demo of their Lumira application for dealers.

Also around the corner is a new release of Mobile, in which WebIntelligence reports can be filtered with a tap, even in offline mode. Users can save those filters to create a customized view of their reports. For offline users, they also can now set an option so that reports are automatically refreshed when connected, ideal for sales people who need to be sure they have the latest content cached.

Stated improvements to the BI platform (but with no specific timeframe) include:

• Free hand SQL. This is huge, but as I've heard it as a roadmap item for a couple of years now, I won't hold my breath until I see the beta.
• Live Office support for newer universes created in 4.x (.UNX); this has been a hole in the product portfolio since version 4 was first released in 2012. Microsoft added support for universes in Power Query last month, a partial solution for long-time Live Office users.
• Parity in the DHTML and Java client WebI interfaces

SAP seems to be at a cross roads in the BI and business analytics space; trying to innovate at the pace of smaller, more nimble competitors such as Tableau and Qlik, while also serving and enhancing the bread and butter enterprise BI and ERP customers. HANA, HANA Enterprise Cloud, Business Suite on HANA, and Simple Finance are the bigger ticket items and next generation platforms that have been a mainstay of SAP for forty plus years. Straddling both worlds is not easy.

BI Adoption Remains Flat

By Cindi Howson, BI Scorecard

(Please note new blog address:  http://www.biscorecard.com/blog/.  This blog will no longer be updated.)

The world of business intelligence has been revitalized by the buzz of big data, the promise of personalization, and the agility of visual data discovery. Yet many companies struggle with the basics of accessing data, particularly new data sources. BI has long been considered a tool for power users and for management to run the business, but easier-to-use tools, mobile BI, and visual data discovery have allowed new classes of users to exploit the value of data.

BI Scorecard's annual survey of BI users, administrators, and directors shows success rates have remained flat since the survey was first conducted in 2006 (based on 513 respondents). Success is defined by BI's ability to improve access to data, decision-maker's perception of value, and impact on revenues, customer service, and operating efficiency. However, the portion of customers saying BI has delivered significant business impact declined in 2013 by six percentage points to only 28% -- the lowest since the survey began. While there are some very successful and impactful BI deployments, the majority are stuck in the middle, with respondents reporting only slight to moderate success and business impact. On the bright side, few respondents (3%) reported outright failure.

BI adoption as a percentage of employees remains flat at 22%, but companies that have successfully deployed mobile BI show the highest adoption at 42% of employees. (see Figure)

Survey respondents say that if they had appropriate budget, clean data, and organizational policies that support BI, 50% of employees on average should be using BI. The gap between deployed BI and potential BI users shows that companies are not tapping BI's full potential. While much of the industry focuses on software and technical innovations, the main barriers are organizational and cultural, according to 84% of survey respondents.

Executives can address organizational and cultural challenges, making leadership the most important organizational criterion for success. Aligning BI efforts to business goals is the second most important success factor. Alignment requires a strong business/IT partnership and ongoing dialogue, something many companies lack. BI teams that report directly to the CEO or to a line of business show the most significant business impact. However, strained BI resources make it increasingly difficult to expand the reach of BI or for companies to take advantage of new innovations. As demand for new data sources, more users, and analytic complexity increase, BI teams have to work smarter, and business users have to embrace self-service BI.

Most companies (66%) have standardized on a BI platform across the enterprise or per line of business. However, the companies that deploy tools from specialty vendors report higher success rates and business impact than companies that use one BI platform exclusively.

Big data stole most the headlines in 2013, but dashboards, new data sources, and self-service BI are the main priority for investments in 2014, followed by mobile BI, visual data discovery, and upgrading to the latest BI releases

I have long advocated that customers should evaluate the quality of customer account management and technical support. The greater the partnership between a BI vendor and a customer, the greater the likelihood that both sides will manage—and meet— expectations.

Overall, customers of specialty BI vendors such as Tableau and Qlik had higher satisfaction rates, while those of larger BI vendors Oracle and SAP were less satisfied. However, the size of the BI vendor alone does not equate with lower satisfaction, as Microsoft, for example, scored well on quality of technical support. The quality of technical support has a huge influence on success and business impact. We are talking software, and sometimes disparate components, so it's almost a certainty that BI teams will encounter problems.

The difference among BI vendors is in how quickly and adequately those problems are resolved. And yet, the quality of technical support for some BI vendors has only gotten worse as they've built broader portfolios and experienced high employee turnover. How much does it matter? Customers who rate the technical support as very good to excellent, also have the highest degree of business impact, with 45% rating BI's impact as significant, compared to the survey average of 28% rating the impact as significant.

The BI Scorecard Successful BI survey is not sponsored by vendors. The full report can be purchased here. For a free copy of the 30-page highlights, take next year's survey. Sign up here to be notified of when the survey opens.

Big Trends in BI for 2014

By Cindi Howson, BI Scorecard

Note: this blog is being migrated to a new site. If you have this on an RSS feed, please visit new location for continued updates: http://blog.biscorecard.com/

In some respects, 2014 echoes some of the same themes as 2013, but faster and louder when it comes to visual data discovery, cloud, and mobile. Big data will also continue to garner attention, but with a more pragmatic view. Simplicity, meanwhile, experiences a second coming. Here are the top five trends for 2014.

1. Visual Data Discovery and Self-Service BI

Visual data discovery took center stage in 2013, with specialty vendors (Tableau, QlikView, TIBCO Spotfire) growing rapidly and mega vendors (SAP, IBM, Microsoft, Oracle, MicroStrategy, SAS) stagnating. BI heavyweights have taken notice that more agile and visual solutions have eaten into their bread-and-butter, query-and-reporting market share. All have responded with new interfaces and solutions. The intial releases of visual data discovery solutions from mega BI vendors tended to have limited capabilities, but the gap is slowly closing. Both the specialty vendors and the heavy weights -- are trying to find the balance between agile yet trusted data -- user driven but IT controlled. It's not an easy line to straddle.

The entire BI tools market was largely founded on the concept of self-service BI: let users create their own queries without having to know SQL. The difference is in how much IT is involved upfront and how much users are able and willing to do themselves. Visual data discovery tools have brought a greater degree of ease, appeal, and flexibility than other BI modules such as production reporting, business query, and dashboards.

Tip: If you haven't already made visual data discovery part of your BI portfolio, your company is missing an opportunity to empower business users. Make it a priority to adopt in 2014.

Here's what you can expect from vendors in the year ahead:

• Tableau , TIBCO Spotfire, and MicroStrategy released major new versions in 2013 that they will be pushing customers to adopt in 2014. Actuate also released a new version of its platform, Actuate Analytics, with integrated, advanced capabilities for customer segmentation.
• QlikView Next, currently in beta, brings a next-generation architecture to market and is expected to become generally available this year.
• LogiAnalytics released a new LogiVision interface in early January aimed at the business user and competing with visual discovery solutions.
• The concept of story telling is increasingly appearing in BI products in which information and analyses are presented to support a decision-making process -- a bit like PowerPoint. Look for this in the latest SAP Lumira, Tableau, and QlikView.Next products due in 2014.
• As visual data discovery deployments expand, roles and responsibilities for BI teams must change to ensure business agility doesn't degenerate into chaos. BI teams that have taken a hands-off approach to visual data discovery tools need to support data provisioning and best practices; conversely, users who have relied on IT for every last sort, filter, and customization will need to learn to fish for themselves.

2. Cloud

Cloud has been hot in almost every software segment except BI. Salesforce.com and NetSuite have put a dent in sales of business application market leaders SAP and Oracle. But the same cannot be said in BI, where cloud BI vendors such as Birst, GoodData, and Indicee have remained niche players.

I think 2014 will be the year that cloud finally takes hold in BI. Part of the change will be due to market maturity, but also, the degree of pain and opportunity cost for BI teams to maintain their own infrastructure has reached a tipping point. BI resources are limited. Would your company rather have that available talent spend time accessing and exploring data, testing innovative ideas, and bringing in more data; or do you want them bogged down maintaining infrastructure and upgrading software?

What are the signs that 2014 will be a pivotal year in cloud BI?

• Birst and Gooddata gained additional VC funding in the second half of 2013
• JasperSoft's Cloud Analytics launched in 2013 as a pay-as-you-go option on Amazon Web Services and it's showing strong momentum.
• Look for MicroStrategy to unveil a similar initiative to make their software available through a broad set of public cloud providers, such as Amazon Web Services (AWS), with users subscribing by the month, day or even hour.
• Microsoft Power BI, a SaaS solution for self-service business intelligence, currently in technology preview, is expected to be available in 2014
• Oracle intends to launch a SaaS-based BI offering in 2014
• IDC predicts cloud spending overall will grow 25% in 2014.

With more choices and scalable databases offered in cloud environments, concerns about data scalability seem less valid than in the past. Some BI vendors let you keep your data on premises while using the cloud for software delivery, giving customers the best of both worlds.

Tip: To get started in cloud, consider a proof-of-concept project for a line of business looking for particular functionality not available through your on-premises BI platform.

3. Mobile

For years we've been hearing "mobile first" from a number of BI vendors, so you'd expect a degree of maturity and stability in this segment. However, the market is still debating how to deliver mobile, what capabilities to offer, and which devices to support. For many BI teams, mobile BI is still something you have to push users to embrace, despite the industry hype.

There's significant room for improvement in mobile BI, with ig big differences in functionality remaining in four areas:

• HTML5 versus native apps: To date, native apps have provided the best user experience, but might 2014 be the year that HTML5 takes over? Developers would like to develop once and deploy anywhere. Users, meanwhile, want the best user experience, with full touch-screen functionality, rich graphics, and great performance.
• Security: Mobile Device Management systems allow customers to grant authentication at the device level in addition to supporting user names and passwords. They also support remote wipe and lock out in the event a device is lost or stolen. Some BI vendors provide this functionality within their own platforms, and others rely on third-party MDM vendors.
• Interact or author: I've surveyed many users and found that for now, they primarily want interactive consumption of BI in the form of view, refresh, sort, filter, and drill. Authoring reports and capturing new data may be cool features, but most BI users are still waiting for the basics to be covered.
• Offline: Airplane mode aside, there are also many locations -- remote buildings, warehouses and so on -- with limited cell service. For these situations, offline capabilities are important for mobile BI, yet few vendors provide this functionality. In particular, consider whether the offline support that is available is viewing of static page images or an interactive app that can explore cached data. When offline use is supported, security clearly needs to be robust.

Tip: Just because users aren't asking for mobile BI doesn't mean there is no business value. Identify mobile workers and pilot the capabilities so users understand the potential.

4. Big Data and Little Data

Big data may be mainstream news, but it's nowhere near mainstream deployment. According to a recent TDWI survey, only 10 percent of companies have deployed big data technologies, and a similar finding from a Tech Target survey puts the number at 14 percent.

As I discuss in my book, Successful Business Intelligence: Unlock the Value of BI & Big Data, there is still confusion about what "big data" means. Many consider it synonymous with Hadoop and NoSQL technologies and, in the early days, predicted the demise of the data warehouse. Fortunately, even providers of Hadoop solutions, such as Cloudera, are increasingly recognizing that Hadoop is only one part of a big data ecosystem. Analytic appliances such as IBM PureData System for Analytics(formerly branded Netezza) , Pivotal Greenplum, and HP Vertica (to name a few) are also part of the big data market. In-memory computing with the likes of SAP Hana, Oracle Exalytics, and Microsoft Hekaton (due in 2014) also supports big data analysis.

The earliest adopters of these technologies may have large data volumes, but others have small data volumes. These organizations are looking to mine insights from unstructured content such as sensor data, tweets, Facebook posts, and email messages that arenot so easy to explore with traditional relational databases. They, too, need new technologies even if it's not about "big data."

In the year ahead:

• Expect tighter integration between Hadoop technologies and traditional data warehouse storage with a greater emphasis on the right use cases.
• Look for better support from BI vendors for a wider range of big data sources.
• In the Hadoop-only world, specialty solutions from startups such as Datameer, Platfora, as well as new entrants will mature.
• SAP, Oracle, and Microsoft continue the quest to run transactional applications all in-memory, threatening traditional disk-based storage.
• Vendors will be innovating, but BI teams are largely still getting educated.

5. Simplicity

My dad was a disc jockey when I was growing up, and our stereo system, with so many knobs and dials, was so complicated that I didn't dare go near it. In much the same way, many business people tend to shy away from BI tools. There have been attempts to achieve simplicity in BI, but with lackluster success.

Expect 2014 to be the year that the new face of BI will be simple -- without sacrificing smarts. These products will be driven in part by visual data discovery, but also by search, improved dashboard interfaces, and embedded BI.

In the area of search, the year ahead will bring:

• Oracle Endeca 3.0 (released in late 2013), with cleaner visualizations and faceted navigation of both structured and unstructured content.
• Microsoft Q&A, an interface for the upcoming PowerBI release that will let users enter simple search terms to find existing content or to create data visualizations.
• IBM Project Neo, a SaaS-based offering that combines search, smart visualization, and advanced analytics
• Startups NeutrinoBI and DataRPM are using search and natural language processing to bring simplicity to a broader base of users.

Other trends

In writing this article, I started first with what was top of mind and tried to hold myself to five – a tough constraint. I also had a look at what I thought would be big in 2013 and whether or not those trends proved to have staying power. Last year, I wrote about next-generation dashboards, and vendors certainly delivered in that space. In-memory as a computing approach was more of a headline last year that has become integral to big data, cloud, visual data discovery, and mobile. I've held my list to the top five trends for 2014, but a top-10 list would have to include advanced analytics, collaboration, social data, the talent shortage, and privacy. We saw a lot of activity in 2013 in advanced analytics with SAP acquiring KXEN in 2013 and broader support for R. Companies still seem to be struggling with basic data access though, and limited expertise and talent shortage is limiting broader adoption of advanced analytics. Vendors are trying to address this by embedding the smarts directly in the software. At the same time, I'm encouraged by the number of universities beefing up their BI and analytics curriculum.

I would think that with all the success of Facebook and most recently a Twitter IPO, collaboration in the BI world would now be showing strong momentum. It made my top trend list last year, and yet, that social influence has not yet gained traction in BI. It's continuing to emerge, but business users seem disinterested. I attribute the slow adoption to a combination of product immaturity and requisite change in workflow and culture. While collaborating around data is lackluster, mining social data has become part of the savvy marketer's toolkit. I've seen good solutions from BI vendors, particularly Information Builders and IBM, but also from Attivio that integrates with a number of visual data discovery vendors. Privacy though can through a big wrench in all this big data and social data. From Snowden and the NSA phone tapping to the Target data breach, individuals have gotten a big education on just how much data we are creating, how much it's being mined, and how easy it is to steal. The greater good for all this data needs to be weighed against the need for privacy. Expect some more breaches and backlash.

IBM Neo Heats Up Competition in BI Search

By Cindi Howson, BI Scorecard

I wrote last week that one of the big trends in big data was a resurgence in the use of search and natural language processing for making BI as easy as Google. Last week at IBM's annual Information on Demand conference, IBM announced project Neo, heating up competition in BI Search and cloud BI.

Neo starts with a simple search box in which users can ask a question. In this screenshot, "what is the relationship between Budget, Gross Domestic Sales, by Story type. Neo will present a list of possible data sources that can answer the question. For now, these data sources are restricted to data sets loaded to the cloud, in a DB2 columnar data store. IBM concedes that for the product to be fully embraced, Neo will need to support on-premise data sources as well, and has said that is part of the product roadmap.

Once the user selects the optimum data source, Neo generates an interactive visualization. For example, a user can refine the question by change "budget" to "units sold," for example. The visualization can also be changed to display as a trend rather than a bubble chart. In addition to the visualization, Neo generates a number of infographics (shown along the top)based on statistical algorithms that might be relevant. So even though the user didn't ask about seasonality, the data is showing there is a pattern with Fall being the best season for sales (early holiday shoppers, perhaps?).

Neo brings together a lot of intellectual property that IBM has acquired in recent years. The visualizations are powered by RAVE (Rapidly Adaptive Visualization Engine) technology and skills acquired through SPSS. The infographics are based on some of the capabilities in Analytic Catalyst, a module released in June of this year that makes advanced analytics easy for a casual business user. The natural language processing leverages Vivisimo, later rebranded Infosphere Data Explorer.

Not surprisingly, the initial demos of Neo are impressive. It's easy, visual, and powerful, for the most casual of decision makers. It could do for data what Google has done for the Internet. Today, the industry average for BI adoption is at 24% of employees, and ease of use is an oft-cited barrier to broader BI (take this year's survey to rate your BI adoption and ease of use).

What wasn't shown, though, is how the data sources get indexed and loaded to the cloud. IBM Cognos has previously tried to leverage the simplicity of search with its Go! Search interface launched in 2006. With that tool, content in PowerCubes and reports had to be indexed on a periodic schedule. Search was limited to key words, and the interface was existing reports, not nearly as visual as Neo. So Go! Search had a degree of complexity to implement, was less intuitive, appealing, and smart. Perhaps these are all reasons why it wasn't widely adopted? Just how well Neo overcomes the past limitations of Go! Search will only be known once the beta launches in January.

IBM also announced another new product, IBM Concert, that brings collaboration, workflow, and mobile together in a SaaS solution. This product is expected to be available in December. I see collaboration as still an emerging capability that customers are trying to figure out. Recognizing the influence that vendors like Facebook and Twitter have had on consumers, social and collaboration capabilities have began appearing in BI tools and enterprise apps a few years ago. SAP first launched Streamwork, then later acquired Success Factor's Jam, while Microsoft acquired Yammer, and TIBCO launched Tibbr. IBM has had strong collaboration capabilities in its Lotus Connections product, whose technology was first integrated with IBM Cognos in its version 10 release back in 2010. But I haven't found a single customer using those capabilities. Again, it's not clear if that's because it was poorly marketed and BI teams have other priorities, or if it reflects a larger, industry-wide problem. Collaboration around data today is usually offline from the data, whether via email or in meeting rooms or conference calls. So first, capturing comments in collaboration software is a change in the current work flow. Second, making comments publicly requires an analytic culture in which it's safe to voice opinions, dissentions, and to ask tough questions. Just imagine, if 30 years ago, the engineer who was worried about the Space Shuttle Challenger posted a comment in the data analysis of O-ring tests to the effect of, "the data shows we shouldn't launch. Too cold out." In those days, the engineer could barely voice a concern in whispers and only to his direct supervisor. (If you're as fascinated about that story, culture, and decision making catastrophe as I am, I'll be watching the Science Channel's documentary this Saturday). How far have we come since then? Is social something reserved more for personal and public opinion, or is it something that the industry is ready to embrace in BI?

I look forward to watching both new products enter the market!

Big Data’s Big Themes at Strata in New York

by Cindi Howson, BI Scorecard

Big Data took New York by storm last week at the annual Strata conference, and coincidentally, on the anniversary of Super Storm Sandy.

The conference was sold out weeks in advance to 3400 attendees. At a conference that drew only 700 people just a few years ago, the attendance reflects the interest, enthusiasm, and innovation in big data.

Some key trends from this year's conference was a dose of big data reality, solutions to help business analysts get to all data, the ease of search, and visualizing big data.

Big Data Grows Up

A few years ago, some people in the big data world were predicting that Hadoop and NoSQL technologies would bring the end to the data warehouse as we know it. Slowly, there seems to be a more pragmatic view of the role that Hadoop has in the enterprise. Facebook Chief Analytics officer Ken Rudin, formerly of Zynga, declared that "big data isn't about the technology—it's about the business needs." He described how Facebook started their analytics with Hadoop, but hassince added a traditional data warehouse to their analytics portfolio. It's all about the right technology for the particular data and type of analytics, and while Hadoop may be great for storing data, it's not so good for the analytics. To that end, MongoDB gave a great presentation on how they see their best fit as in the real-time storage of big data, while Hadoop is better suited to offline data. As examples, two case studies in my just-published book (Successful Business Intelligence 2/E: Unlock the Value of BI and Big Data), reflect exactly these use cases. FlightStats, who tracks thousands of flights in realtime is using MongDB to serve up that information to millions of customers. University of California, Irvine Health, on the other hand, is using Hadoop to store patient medical records, saving hundreds of thousands of dollars versus storing data in the electronic medical records system that runs on a relational database.

Cloudera's Chief Strategy Officer Mike Olson announced Cloudera 5, which acts as an enterprise data hub from which the data warehouse can draw granular data on demand. It includes better security and data lineage. Also announced was Cloudera in the Cloud via its partners, initially Verizon and IBM.

Business Analysts Unleashed

Much of the big data community has initially catered to the statisticians and data scientists, who are skilled in math, statistics, programming, and the business. It's a job that requires a broad range of skills and expertise that is in short supply. In trying to address that short supply of talent, a number of vendors are bringing capabilities to the business power user, but without the need to write SQL or MapReduce jobs. The original BI module that first helped unlock data in relational databases in the 1990s was the business or ad hoc query tool. A semantic view or business meta data layer helped these power users get to their data without knowing SQL, but only once that data was loaded into a data warehouse or mart. But the semantic layer and the data warehouse has gotten increasingly bogged down and maintained by IT. At the same time, power users are trying to get to a broader range of data sources, from Hadoop to relational to XML files, cleansed, transformed, and mashed together on their own terms. These power users are not data scientists who want to code in MapReduce or SQL; they still want to point and click, wherever the data lives. I'm dubbing this new category of tools "Business ELT"

New solutions in this category include Microsoft PowerBI, touted in the keynote, its cloud-based self-service BI solution, currently in community preview. The Power Query module allows a business user to connect to multiple data sources, transform and cleanse the data, and create a view that others can readily consume via native Excel or Power View, its visual data discovery solution. (For a detailed discussion of capabilities, strengths and weaknesses, purchase the review on BI Scorecard).

Meanwhile, Dell acquired Quest Software last year, best known for TOAD that helped DBA's write and optimize SQL queries. TOAD BI, however, is aimed at the business power user, allowing them to mash together multiple data sources and rapidly create subject areas. TOAD BI also has a good differentiator in that it can access an SAP BusinessObjects universe or Oracle BI EE data model, leveraging existing semantic models.

Start-up vendor Paxata show-cased what they describe as the" industry's first adaptive data preparation platform for business users." The tool has built in algorithms so it detects both join relationships between tables as well as potential data quality issues. What's nice about this solution is that they also have partnered with QlikTech and Tableau so that once the business power user has extracted and transformed their data, they can use an established visualization and dashboard front end.

BI Search 2.0

The concept of bringing the ease of use of Google to BI has had a couple attempts in the BI space, going back to 2006 when Google first released Google One Box for enterprise customers. A couple BI vendors were quick to embrace this approach, feeding BI report meta data and in some cases cube structures to the search engine. It all sounds like a great idea. And yet, few customers leveraged this approach for a variety of reasons, some of which have been poor marketing and high licensing costs, and in other cases, difficulty implementing. But we seem to be on the cusp of a second breath of search-based BI. Here, Microsoft showcased its Power Q&A, a module of Power BI, that allows users to ask simple questions like "What are my sales in New Jersey this year?" It returns a dynamically-created, interactive visualization in which the casual user can refine the question and criteria.

Also at Strata was start-up DataRPM, currently in beta and expected to be generally available in the first half of 2014. They also are leveraging natural language processing, not just indexed key words, with two key differentiators. First, they work on top of both structured and unstructured data. Secondly, they embed search within existing processes, not as a separate BI solution. I met with DataRPM at the end of a long day, and they still managed to get a wow out of me. I look forward to seeing how this vendor hits the market.

Although not at Strata, I've also been tracking a start up out of the UK, Neutrino BI who also brings the concept of NLP and search to their dashboard solution. (Catch them live at TDWI in Orlando in my Cool BI class).

With BI adoption still stuck at a paltry 24% of all employees (tell me your BI adoption in this survey, and for a limited time get a free copy of the 2012 report), the ease of use BI search has the potential to bring BI to more mainstream users. It also might unlock data that users currently struggle to find and access.

Visualizing Big Data

There are still two main camps in the visualizing of big data: traditional BI vendors who can access relational data sources as well as Hadoop, and those who access primarily Hadoop. Tableau, QlikTech, TIBCO Spotfire, and MicroStrategy fall into the first category. DataMeer, Platfora, and Karmasphere fall into the latter.

DataMeer has differentiated itself on its ability to generate MapReduce jobs directly, without having to go through a slower HIVE interface that other BI solutions may rely on. It has tripled its customer base in the last year and sees four key use cases: customer analytics, web log file analytics for IT operations, fraud detection, and lowering the cost of data storage. With DataMeer, the data scientist interacts with the Hadoop data via a spreadsheet interface and can then present the results via simple and appealing Info Graphics.

Platfora, in beta at last year's conference, is now generally available and announced version 3 of its product, due in Q1 2014. Platfora creates a type of view, which it calls a lens, to data in Hadoop. Data is loaded into its own in-memory engine where business users can visualize and interact with the data. New capabilities in version 3 allow users to organize the data into events, (such as store visit versus web visit), and the ability to do iterative customer segmentation. Some early users of Platfora include Disney, Netflix, and Shopify.

MicroStrategy Analytics – Free and Easy

By Cindi Howson, BI Scorecard

MicroStrategy has established its reputation as one of the most innovative BI heavyweights – early to adopt mobile, in-memory, and cloud. The product is known for enterprise scale, but also was known for its complexity to implement. In truth, it's not so much that the product itself was harder to implement than comparable BI platforms, but rather, that it required a clean data model, with conformed dimensions. Customers who didn't have an enterprise data warehouse usually sought alternatives from more flexible BI platforms or newer visual data discovery vendors.

With MicroStrategy's latest release, the vendor has gone a long way to improving the ease of use and has now set its sights on engaging even the every-day decision maker, with free versions of MicroStrategy Desktop and MicroStrategy Express. MicroStrategy Desktop is a new product aimed at the individual BI user based on its Visual Insight product, competing most directly with the likes of Tableau. Users can import data (modeled or not) and immediately create interactive visualizations and dashboards. Dashboards can be emailed as a PDF to other users.

Although MicroStrategy has branded this new product as "Desktop," it shouldn't be confused with the earlier and original Desktop interface of MicroStrategy. This version installs locally and creates an internal website on the local desktop, so users still work through a web-based browser to create content, the same interface that MicroStrategy Express and Enterprise users access. This approach makes for a more consistent user interface across the product line and a transition path to a larger deployment. However, compared to other BI products that are truly desktop-based, the start-up process is slower.

MicroStrategy Express – the cloud version of the product -- has more robust capabilities than Desktop that also include highly formatted reports, report scheduling, and file sharing. The vendor has announced that it will make MicroStrategy Express free for the first year, with no future commitment or cap on the number of users. The main limitation here is that data has to be loaded to the cloud, whereas the fee-based MicroStrategy Cloud enables data to be left on premise.

In addition to an overall face lift, all versions of the product now support data blending, in which users can mash together data from multiple data sources. Data can come from a flat file, spreadsheet, dozens of relational databases, Hadoop and Hive, or existing MicroStrategy reports. In the past, the inability for users to blend or mash their own data sources together has been one of MicroStrategy's biggest limitations, and a strength of competitors Tableau, QlikTech, and TIBCO Spotfire. This improvement boosts MicroStrategy's flexibility for individual report authors. Meanwhile, more scalable and centrally controlled data federation at the server level continues to be supported through MicroStrategy's Multi Source option.

In making these two versions of the product free, MicroStrategy is clearly trying to seed the market and get customers to take a second look at the new MicroStrategy. The vendor has tried this seeding approach once before with Reporting Suite that met with mixed success, mainly because that version was harder to deploy and lacked dashboards. With the ease of use and flexibility addressed in the latest release, the vendor's seeding strategy could provide a big boost in its competitive position. MicroStrategy's moves are one more proof point that visual data discovery is one of the hottest segments of the BI market.

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