Years ago, I had a great boss. Very smart, good people manager, understood strategy and tactics. There was one flaw. One joke was that head never use a sentence if a paragraph would suffice. That showed most clearly is the voluminous number of slides that would be part of any presentation.

He comes to mind because I attended Tableau Software’s presentation to the Boulder BI Brain Trust (BBBT). 93 slides. Yes, 93. Even if folks were not familiar with BI, I think the presentation would have been a bit, shall we say, extensive. Just like that boss, the presenters had a lot of very interesting to say, but finding it was often hidden in too much explanation. So I don’t make the same mistake while describing the presentation, here are my key takeaways:

• Balanced on-premises and Cloud strategy.
• Strong forethought about changing relationship between IT & business users.

Everyone even vaguely involved in BI should already be familiar with the basics of Tableau. It is one of the leaders in the latest generation of BI solution providers. They are known for their visualization skills yet haven’t scrimped at the technology needed to manage large data sets. They had a tag team of four presenters for the presentation. The first presenter was Suzanne Hoffman, Sr. Director of Analyst Relations, who gave the overview of company growth since last year’s BBBT presentation.

Francois Ajenstat, Sr. Director, Product Management, then followed with, as would be expected from product management, a review of products including a discussion of v8.1. In a review of a number of things, the one item that caught my attention was the extension of their Cloud packages. It was clearly stated that the product wasn’t redesigned for the Cloud, just moved outside the firewall to a hosted environment, but that’s a fine first step considering the rest of the work they’ve done. What’s critical is they’ve thought through the Cloud business model and how that is different than what’s needed for purchased software.

The one issue I have, from an analyst perspective, was the very brief discussion of the supposed success and early adoption of their 8.1 offering. While describing the number of companies who have rapidly adopted it, there was no breakdown. How many were new customers versus old? Were they larger or smaller companies? While it is to be expected that newer companies and departments, as well as smaller companies, would be the first to adopt, and while that’s not necessarily an issue, clarity would have helped.

In a look ahead about v8.2, which we were told is not under NDA was a look at what seems to be an extremely professional Mac port. It’s not just moving what was on MS Windows to the Mac, as many companies do. It looks like a product designed for the Mac that will make very happy any user of that platform. While Francois did a good job explaining why they wanted to port to a platform that has 10% of the business market, I think Tableau should be more explicit on who that 10% is and why that matters. Marketing. Yes, I know, I’m biased towards marketing, but think about the fact that marketing was the home of the Mac during the lean years. Why? Because the Mac has always been better for visualization, so marketing continued to use the platform for creating ads, graphics, charts and more. Providing a great Mac port enhances the ability of marketing to serve good analytics and presentations to the rest of the firm.

The presentation was then handed to Robert Kosara, a research scientist, to talk about visual storytelling. Here, again, there were too many examples and a blurred message. While trying to describe how the concept was different than the visualization theories that have happened from Tufte onwards, the difference wasn’t made very clear. There seemed to be two main takeaways. First, they’re only describing the fact that modern BI allows isolation of and drill down into segments of the visualization, things that aren’t possible in old-line static print medium. That seems intuitively obvious rather than a giant leap forward. The second part of it isn’t with theory but with some of Tableau’s plans (again, we were told that this level isn’t under NDA) to provide technology that merges visualization with presentation layout, where the application will be able to take the equivalent of slides of the visualization to increase the presentability of analysis. That’s still early in work but could be very interesting as it matures.

The final presenter was Ellie Fields, VP of Product Marketing. Maybe I’m biased, as my background is in product marketing, but I wish this section had not been last. The most important thing is her presentation was what I think best brings out why Tableau is a leader. Her section focused on the changing environment for BI implementations. Everyone in the industry acknowledges the power of the BI front-end is giving business users more and more ability to be involved in creating and managing their own analytics. We know that IT is going to have to change from a more controlling focus to one of service. Ellie Fields has thought this through and clearly defined how the change doesn’t obviate the need for IT but only changes the relationship between the two sides. The most important slide in the deck is the one below, where a high level description of that partnership is presented.

The past growth of Tableau Software has clear reasons. It was a good technology introduced to the market at the right time. What they’ve done so far is a sign of management’s ability to understand an early market. Continued growth is across Moore’s Chasm and a longer term strategy is critical. In my (probably not so humble) opinion, while technology is critical there are far too many technology companies that failed with great products. It’s the vision shown in both Francois Ajenstat’s discussion of managing both on-premises and Cloud markets combined with Ellie Field’s understanding of how to position the company to help businesses through a major change in how IT and business users will relate that show the strength of the company moving forward.

I just wish we heard that information bubbled and  more visible rather than lost in a bunch of other words that weren’t really needed.

This is the third and final blog in my series about last week’s Salesforce1 event in Philadelphia.

I’ve discussed the growth of the Salesforce ecosystem and how the company is bringing back the integration because SFA, CRM and help desks to ensure customer facing systems work together. They also have partners with applications such as accounting, quoting and other add-ons to the full process. The final big issue is how that needs to change reporting.

It’s easy to create charts and desktops for single applications focused on a department or function. That’s not why business intelligence exists. Upper management needs to better understand how their organizations are performing, and that means analyzing information that comes from multiple systems. BI’s goal is to provide actionable information about the business. That’s why it grew alongside data warehouses that gathered information from disparate systems. Now that Salesforce is clearly creating an integrated environment, are their analytics growing apace? Sadly, no.

“Analytics Unleashed” was the key session that interested me above all others. However, to paraphrase Gertrude Stein, there wasn’t much there there. It looked like simple reports slapped into basic dashboards with no real drill down or data discovery capability. Admittedly, the major part of their demonstration didn’t work and it might have been in that, but I didn’t see anything on in the exhibit hall to make me think there was.

Well, not from Salesforce directly, but don’t be without hope. I’ve talked about the ecosystem they’ve clearly built with Salesforce1, and that comes with advantages. One of those advantages is Birst, a business intelligence firm.

Birst is a Salesforce partner who, unlike a number of other partners at the road show, isn’t exclusively focused on Salesforce. They are in the new generation of BI firms who are working to modernize the market. They work to eliminate the need to have separate ETL and BI vendors, providing a platform to integrate that then directly supports leading edge analytics capabilities.

That ability combines with a SaaS architecture to allow Birst to work well with Salesforce1. I talked with them at their stand and the integration seemed clean from a UI standpoint. I’d have to dig deeper to understand how well Birst helps Salesforce integrate with other systems, but things look hopeful.

Salesforce seems to be viewing BI the same way as the other large companies. Even with their more modern history, advanced SaaS architecture and appropriately Web nimble interfaces, Salesforce still thinks of analytics as reporting. If “we” get all applications under our control, we just extend our reporting. That’s not BI. Analytics is a more advanced way of providing better information for decision making.

At some point, I’m sure Salesforce will come to that understanding, and then who knows what will happen. Until then, Salesforce customers can still access the next generation of BI and analytics through the ecosystem that allows Salesforce and Birst to work in concert.

When I studied artificial intelligence (AI) in the mid-1980s, an argument was raging about whether or not it could ever be solved. That argument continues to occur, but it’s intriguing to understand why. It’s not that we have made no progress, it’s about the real, underlying definition of what we think of as AI. If both academics and practitioners were honest, they’d admit that the definition of AI is “Getting machines to do the rest of what we call human intelligence that we haven’t yet figured out how to do with machines.” Notice that it’s a negative definition, AI is what we still don’t know. Therefore, until we have AI it’s always unsolved.

Vision, robotics and other full-fledged disciplines were considered AI in the early days. When we understood the problems well enough to solve chunk or at least to investigate them as specific units of study, they became their own area. What was left was still AI, the “unsolvable problem.”

I bring this up because my area of interest in AI was expert systems. I had the honor of working on a project under Bruce Buchannan, one of the creators of Dendral and MYCIN (two of the earliest expert systems). It was a business application of expert systems, using rules to get a computer to plan and budget. Working to get the professor’s brain onto the white board is was what made me realize I wanted to be on the business side of computing rather than the computing side of business.

Expert systems as a whole were oversold, and earned a bad reputation. So, just as rap became hip hop, other terms were used. Today we talk about “rule based systems,” “knowledge systems” and other similar techniques to help analyze Big Data. Companies talk about “intelligent agents” for customer support and prospect advice. There are a plethora of terms to describe what are, essentially, expert systems.

Why does that matter? While we might be able to solve new problems in business, adding significant value to software, most of what we do is evolutionary rather than revolutionary. That’s a good thing, as IT and most of the mass market want to know that they can add new capabilities without having to spend time, money and mental anguish over “transforming your organization!”

When looking at  the new techniques for better understanding data, for predictive analysis and for other areas of business applications, know that knowledge systems have a long and strong history, regardless of a founder’s or a marketing organization’s addiction to a revolutionary message. Spend time to see if the vendor sees past his revolutionary message to the evolutionary solution needed by most firms.