Tag Archives: business intelligence

Denodo at BBBT: Data Virtualization, an Important Niche

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Data virtualization. What is it? A few companies have picked up the term and run with it, including last week’s BBBT presenter Denodo. The presentation team was Suresh Chandrasekaran, Sr. VP, North America, Paul Moxon, Sr. Director, Product Management & Solution Architecture, and Pablo Alvarez, Sales Engineer. Still, what I’ve not seen is a clear definition of the phrase. The Denodo team did a good job describing their successes and some features that help that, but they do avoiding a clear definition.

Data Virtualization

The companies doing data virtualization are working to create a virtual data structure where the logical definitions link back to disparate live systems instead of overlaying a single aggregated database of information. It’s the concept of a federated data warehouse from the 1990s, extended past the warehouse and now more functional because of technology improvements.

Data virtualization (and note that, sadly, I don’t create an acronym because DV is also data visualization and who needs the confusion. So more typing…) is sometimes thought of as a way to avoid data warehouses by people who hear about it at a high level, but as the Denodo team repeatedly pointed out, that’s not the case. Virtualization can simplify and speed some types of analysis, but the need for aggregated data stores isn’t going away.

The biggest problem with virtualization for everything is operational systems not being able to handle the performance hits of lots of queries. A second is that operational systems don’t typically track historical information needed for business analysis. Another is that very static data in multiple systems that’s accessed frequently can create an unnecessary load on today’s busier and busier networks. Consolidating information can simplify and speed access. Another is that change management becomes a major issue, with changes to one small system potentially causing changes to many systems and reports. There are others, but they in no way undermine the value that is virtualization.

As Pablo Alvarez discussed, virtualization and a warehouse can work well together to help companies blend data of different latencies, with virtualization bringing in dynamic data to mesh with historic and dimensional information to provide the big picture.

Denodo

Denodo seems to have a very good product for virtualization. However, as I keep pointing out when listening to the smaller companies, they haven’t yet meshed their high level ideas about virtualization and their products into a clear message. The supposed marketechture slide presented by Suresh Chandrasekaran was very technical, not strategic. Where he really made a point was in discussing what makes a Denodo pitch successful.

Mr. Chandrasekaran states that pure business intelligence (BI) sales are a weak pitch for data virtualization and that a broader data need is where the value is seen by IT. That makes absolute sense as the blend between BI and real-time is just starting and BI tends to look at longer latency data. It’s the firms that are accessing a lot of disparate systems for all types of productivity and business analysis past the focus on BI who want to get to those disparate systems as easily as possible. That’s Denodo’s sweet spot.

While their high level message isn’t yet clarified or meshed with markets and products, their product marketing seems to be right on track. They’ve created a very nicely scaled product

Denodo Express is free version of their platform. Paul Moxon stated that it’s fully functional, but it can’t be clustered, has a limitation of result set size and can’t access certain data sources. However, it’s a great way for prospects to look at the functionality of the product and to build a proof-of-concept. The other great idea is that Denodo gives Express users a fixed time pricing offer for enterprise licensing. While not providing numbers, Suresh stated that the offer was working well as an incentive for the freeware to not be shelfware, for prospects to test and move down the sales funnel. To be blunt, I think that’s a great model.

One area they know is a weakness is in services, both professional services and support. That’s always an issue with a rapidly growing company and it’s good to see Denodo acknowledge that and talk about how they’re working to mitigate issues. The team said there are plans to expand their capital base next year, and I’d expect a chunk of that investment to go towards this area.

The final thing I’ll note specifically about Denodo’s presentation is their customer slides. That section had success stories presented by the customers, their own views. That was a strong way to show customer buy in but a weak way to show clear value. Each slide was very different, many were overly complex and most didn’t clearly show the value they achieved. It’s nice, but customer stories need to be better formalized.

Data Virtualization as a Market

As pointed out above, in the description of virtualization, it’s a very valuable tool. The market question is simple: Is that enough? There have been plenty of tools that eventually became part of a larger market or a feature in a larger product offering. What about data virtualization?

As the Denodo team seems to admit, data virtualization isn’t a market that can stand on its own. It must integrate with other data access, storage and provisioning systems to provide a whole to companies looking to better understand and manage their businesses. When there’s a new point solution, a tool, partnerships always work well early in the market. Denodo is doing a good job with partners to provide a robust solution to companies; but at some point bigger players don’t want to partner but to provide a complete solution.

That means data virtualization companies are going to need to spread into other areas or be acquired. Suresh Chandrasekaran thinks that data virtualization is now at the tipping point of acceptance. In my book, given how fast the software industry, in general, and data infrastructure markets, in particular, grow and evolve, that leaves a few years of very focused growth before the serious acquisitions happen – though I wouldn’t be surprised if it starts sooner. That means companies need to be looking both at near term details and long term changes to the industry.

When I asked about long term strategy, I got the typical startup answer: They’re focused on internal growth rather than acquisition (either direction). That’s a good external message because folks who want a leading edge company want it clear that they’re using a leading edge company, but I hope the internal conversations at the CxO level aren’t avoiding acquisition. That’s not a failure, just a different version of success.

Summary

Denodo is a strong technical company focused on data virtualization in the short run. They have a very nicely scaled model from Denodo Express to their full product. They seem to understand their sweet spot within IT organizations. Given that, any large organization looking to get better access to disparate sources of data should talk with Denodo as part of their evaluation process.

My only questions are in marketing messages and whether or not Denodo be able to change from a technical sales to a higher level, clearer vision that will help them cross the chasm. If not, I don’t think their product is going anywhere, someone will acquire them. Regardless, Denodo seems to be a strong choice to look at to address data access and integration issues.

Data virtualization is an important niche, the questions remain as to how large is the niche and how long it will remain independent.

Data Governance and Self-Service Business Intelligence: History Repeating?

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Self-Service BI is a big buzz phrase these days even though many definitions exist. However, one thing is clear: It’s driving another challenge in the area of data governance. While people are starting to talk about this, it’s important to leverage what we’ve learned from the past. Too many technology industry folks are so enamored by the latest piece of software or hardware that they convince themselves their solutions are so new they are revolutionary, “have no competitors” or otherwise rationalize context. However, the smart people won’t do that.

A Quick History Lesson: The PC

In 1982, I was an operator at one of Tymshare’s big iron floors. It was a Sunday and I was reading my paper sitting at the console of an IBM 370/3033, their top of the line business computer. An article in the business section was an article titled something like “IBM announces their 370 on a chip.” I looked up at my behemoth, looked back at the article and new things would change.

Along came the PC. Corporate divisions and departments frustrated at not getting enough resources from the always understaffed, under financed and overburdened IT staff jumped on the craze. Out with the IBM Selectric and in with the IBM AT and its successors and clones.

However, by the end of the decade and early in the 1990s, corporate executives realized they had a problem. While it was great that each office was becoming more productive, the results weren’t as helpful. It’s a lot harder to roll-up divisional sales data when each territory has a slightly different definition of their territories, lead and funnels. It’s hard to make manufacturing budget forecasts when inventory is stored in different formats and might use different aging criteria. It’s hard to show a government agency you’re in regulatory compliance when the data in in multiple and non-integrated systems.

Data governance had been lost. The next twenty years saw the growth of client server software such as that by Oracle and SAP, working to link all offices to the same data structures and metadata while still working to leave enough independence. That balance between centralized IT control and decentralized freedom of action is still being worked out but is necessary.

While the phrase “single version of truth” is often mistakenly applied to mean a data warehouse and a “single source of truth,” that’s not what it means. A single version of the truth means shared data and metadata that ensures that all parties looking at the same data come up with the same information – if not the same conclusions from that information.

Now: Self-Service BI

Look at the history of the BI market. There have always been reports. With the advent of the PC, we had the de facto standard of Crystal Reports for a generation. Then, as the growth of packaged ERP, CRM, SFA and other systems came along, so did companies such as Cognos and Business Objects to focus on more complex analysis. However, they were still bound by the client/server model that was tied primarily to mid-tier Unix servers and Microsoft/Apple PCs.

What’s changed now are the evolution of the internet into the Cloud and phones into smartphones and tablets. Where divisions and departments were once leashed to big iron and CICS screens, divisions who have been more recently tied to desktops are feeling their oats and interested in quickly developing their own applications that allow their knowledge workers to access information while not seated in the office.

Self-Service BI (And, no, I’m not going to make an acronym as many have. Don’t we have enough?) is the PC of this decade. It’s letting organizations get information to people without waiting for IT, who’s still underfunded, understaffed and overburdened, distribute information widely. Alas, that wide distribution comes without controls and without audit trails. Data governance is again being challenged.

I’ve listened to a number of presentations by vendors to the BBBT, and there is hope. Gone are the days when all BI companies talked about was in helping business people avoid using IT. There’s more talk about metadata, more interest in security and access control, and a better ability to provide audit trails. There’s an understanding that it’s great to allow every knowledge worker to look at the data and understand those pieces of information arising that address their needs while still ensuring that the base data is consistent and metadata is shared.

Summary

We can learn from history. The PC was a great experiment in watching the pendulum swing from almost complete IT control to almost no IT control then back to a more reasonable middle. The BI community shows signs of learning from history and making a much faster switch to the middle ground. That’s a great thing.

Technologists working to help businesses improve performance through data, BI and analytics need to remember the great quote from Daniel Patrick Moynihan, “Everyone is entitled to his own opinion, but not his own facts.”

Tableau Software Analyst Briefing: Mid-size BI success and focus on the future

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Yesterday, Tableau Software held an analyst briefing. It wasn’t a high level one, it was really just a webinar where they covered some product futures under NDA. However, it was very unclear what was NDA and what wasn’t. When they discussed things announced at the most recent Tableau Conference in Seattle, that’s not NDA, but there was plenty of future discussed, so I’ll walk a fine line.

The first news is to cover their Third Quarter announcement from the beginning of the month. This was Tableau’s first quarter of over $100 million in recognized revenue. It’s a strong showing and they’re justifiable proud of their consistent growth.

Ajay Chandrdamouly, Analyst Relations, also said that the growth primarily results from a Land and Expand strategy, beginning with small jobs in departments or divisions, driven by business needs, then expanding into other organizations and eventually into a corporate IT account position. However, one interesting point is an expansion mentioned later in the presentation by Francois Ajenstat, Product Management, while giving the usual case studies seen in such presentations. He did a good job of showing one case study that was Land and Expand, but another began as a corporate IT account and usage was driven outward by that. It’s an indication of the maturity of both Tableau and the business intelligence (BI) market that more and more BI initiatives are being driven by IT at the start.

Francois’ main presentation was about releases, past and future. While I can’t write about the later, I’ll mention one concern based on the former. He was very proud about the large number of frequent updates Tableau has released. That’s ok in the Cloud, where releases are quickly rolled into the product that everyone uses. However, that’s a risk in on-premises (yes, Francois, the final S is needed) installations in the area of support. How long do you support products and how do you support them is an issue. Your support team has to know a large number of variations to provide quick results or must investigate and study each time, slowing responses and possibly angering customers. I asked about the product lifecycle and how they managed to support and to decide sunsetting issues, but I did not get a clear and useful answer.

The presentation Mr. Ajenstat gave listed six major focus themes for Tableau, and that’s worth mentioning here:

  • Seamless Access to Data
  • Analytics & Statistics for Everyone
  • Visual Analytics Everywhere
  • Storytelling
  • Enterprise
  • Fast, Easy, Beautiful

None of those is a surprise, nor is the fact that they’re trying to build a consistent whole from the combination of foci. The fun was the NDA preview of how they’re working on all of those in the next release. One bit of foreshadowing, they are looking at some issues that won’t minimize enterprise products but will be aimed at a non-enterprise audience. They’ll have to be careful how they balance the two but expansion done right brings a wider audience so can be a good thing.

The final presenter was Ellie Fields, Product Marketing, who talked more about solution than product. Tableau Drive is not something to do with storage or big data, it’s a poorly named but well thought out methodology for BI projects. Industry firms are finally admitting they need some consistency in implementation and so are providing best practices to their implementation partners and customers to improve success rates, speed implementation and save costs. Modern software is complex, as are business issues, so BI firms have to provide a combination of products and services that help in the real world. Tableau Drive is a new attempt by the company to do just that. There’s also no surprise that it uses the word agile, since that’s the current buzzword for iterative development that’s been going on long before the word was applied. As I’m not one who’s implemented BI product, I won’t speak to its effectiveness, but Drive is a necessity in the marketplace and Tableau Drive helps provide a complete solution.

Summary

The briefing was a technical analyst presentation by Tableau about the current state of the company and some of its futures. There was nothing special, no stunning revelations, but that’s not a problem. The team’s message is that the company has been growing steadily and well and that their plans for the future are set forward to continue that growth. They are now a mid-size company, no longer as nimble as startups yet don’t have the weight of the really large firms, they have to chart a careful path to continue their success. So far it seems they are doing so.

Magnitude/Kalido Webinar Review: Automated and Agile, New Principles for Data Warehousing

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I watched a webinar yesterday. It was sponsored by Magnitude, the company that is the result of combining Kalido and Noetix. The speakers were Ralph Hughes, a data warehousing consultant operating as Ceregenics, and John Evans of Magnitude.

Ralph Hughes’ portion of the presentation was very interesting in a great way. Rather than talking about the generalities of enterprise data warehouses (EDW) and Agile, he was the rare presenter who discussed things clearly and in enough detail for coherent thought. It was refreshing to hear more than the usually tap dance.

Webinar - Magnitude - Ceregenics slide

Ralph’s slide on the advantages of agile development for EDW’s is simple and clear. The point is that you don’t know everything when you first acquire requirements and then design a system. In the waterfall approach, much of coding, testing and usage is wasted time as you find out you need to do extra work for new requirements that pop up. Agile allows business users to quickly see concepts and rethink their approaches, saving both time to some productivity and overall time and effort of development.

After talking about agile for a bit, he pointed out that it does save some time but still leaves lots of basic work to do. He then shifted to discuss Kalido as a way to automate some of the EDW development tasks in order to save even more time. He used more of his presentation to describe how he’s used the tool at clients to speed up creation of data warehouses.

One thing he did better in voice than on slides was to point out that automation in EDW doesn’t mean replacing IT staff. Rather, appropriately used, it allows developers to move past the repetitive tasks and focus on working with the business users to ensure that key data is encapsulated into the EDW so business intelligence can be done. Another key area he said automation can’t do well is to manage derived tables. That still requires developers to extract information, create the processes for creating the tables, then moving the tables back into the EDW to, again, enhance BI.

Notice that while Mr. Hughes spoke to the specifics of creating EDWs, he always presented them in context of getting information out. Many technical folks spend too much time focused on what it takes to build the EDW, not why it’s being build. His reminders were again key.

John Evans’ presentation was brief, as I always like to see from the vendors, rounding out what his guest speaker said. He had three main points.

First, the three main issues facing IT in the market are: Time to value, time to respond to change and total cost of ownership. No surprise, he discussed how Magnitude can address those.

Second, within his architecture slide, he focused on metadata and what he said was strong support for master data and metadata management. Given the brief time allotted, it was allusion to the strengths, but the fact that he spoke to it was a good statement of the company’s interests.

Third, he discussed the typical customer stories and how much time the products saved.

Summary

The webinar was very good exposure to concepts for an audience thinking about how to move forward in data warehousing, whether to build EDWs or maintain them. How agile development and an automation tool can help IT better focus on business issues and more quickly provide business benefit was a story told well.

Revolution Analytics at BBBT: Vision and products for R need to mesh

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Revolution Analytics presented to the BBBT last Friday. The company is focused on R with a stated corporate vision of “R: The De-facto standard for enterprise predictive analytics .” Bill Jacobs, VP, Product Marketing, did most of the talking while Steve Belcher, Sales Engineer, gave a presentation.

For those of you unfamiliar with R as anything other than a letter smack between Q and S, R is an open source programming language for statistics and analytics. The Wikipedia article on R points out it’s a combination of Scheme and S. As someone who programmed in Scheme many years ago, the code fragments I saw didn’t look like it but I did smile at the evolution. At the same time, the first thing I said when I saw Revolution’s interactive development environment (IDE) was that it reminded me of EMACS, only slightly more advanced in thirty years. The same wiki page referenced earlier also said that R is a GNU project, so now I know why.

Bill Jacobs was yet another vendor presenter who has mentioned his company realized that the growth of the Internet of Things (IOT) means a data explosion that leaves what is currently misnamed as big data in the dust as far as data volumes. He says Revolution wants to ensure that companies are able to effectively analyze IOT and other information and that his company’s R is the way to do so.

Revolution Analytics is following in the footsteps of many companies which have commercialized freeware over the years, including Sun with Unix and Red Hat with Linux. Open source software has some advantages, but corporate IT and business users require services including support, maintenance, training and more. Companies which can address those needs can build a strong business and Revolution is trying to do so with R.

GUI As Indicative Of Other Issues

I mentioned the GUI earlier. It is very simple and still aimed at very technical users, people doing heavy programming and who understand detailed statistics. I asked why and was told that they felt that was their audience. However, Bill had earlier talked about analytics moving forward from the data priests to business analysts and end users. That’s a dichotomy. The expressed movement is a reason for their vision and mission, but their product doesn’t seem to support that mission.

Even worse was the response when I pointed out that I’d worked on the Apple Macintosh before and after MPW was released and had worked at Gupta when it was the first 4GL language on the Windows platform. I received as long winded answer as to why going to a better and easier to use GUI wasn’t in the plans. Then Mr. Jacobs mentioned something to the effect of “You mentioned companies earlier and they don’t exist anymore.” Well, let’s forget for a minute that Gupta began a market, others such as Powersoft did well too for years, and then Microsoft came out with its Visual products to control the market but that there were many good years for other firms and the products are still there. Let’s focus on wondering when Apple ceased to exist.

It’s one thing to talk about a bigger market message in the higher points of a business presentation. It’s another, very different, thing to ensure that your vision runs through the entire company and product offering.

Along with the Vision mentioned above, Revolution Analytics presents a corporate mission to “Drive enterprise adoption of R by providing enhanced R products tailored to meet enterprise challenges.” Enterprise adoption will be hindered until the products reflect an ability to work for more than specialist programmers but can address a wider enterprise audience.

Part of the problem seems to be shown in the graphic below.

Revolution Analytics tech view of today

Revolution deserves credit for accurately representing the current BI space in snapshot. The problem is that it is a snapshot of today and there wasn’t an indication that the company understands how rapidly things change. Five to ten years ago, the middle column was the left column. Even today there’s a very technical need for the people who link the data to those products in order to begin analysis. In the same way, much of what is in the right column was in the middle. In only a few years, the left column will be in the middle and the middle will be on the right.

Software evolves rapidly, far more rapidly that physical manufacturing industries. Again, in order to address their enterprise mission, Revolution Analytics’ management is going to have to address what’s needed to move towards the right columns that mean an enterprise adoption.

Enterprise Scalability: A Good Start

One thing they’ve done very well is to build out the product suite to attract different sized businesses, individual departments and others with a scaled product suite to attract a wider audience.

Revolution Analytics product suite

Revolution Analytics product suite

They seem to have done a good job of providing a layered approach from free use of open source to enterprise weight support. Any interested person should talk with them about the full details.

Summary

R is a very useful analytical tool and Revolution Analytics is working hard to provide business with the ability to use R in ways that help leverage the technology. They’re working hard to support groups who want pure free open source and others who want true enterprise support in the way other open source companies have succeeded in previous decades.

Their tool does seem powerful, but it is still clearly and admittedly targeted at the very technical user, the data priests.

Revolution Analytics seems to have a start to a good corporate mission and I think they know where they want to end up. The problems is that they haven’t yet created a strategy that will get them to meet their vision and mission.

If you are interested in using R to perform complex analysis, you need to talk to Revolution Analytics. They are strong in the present. Just be aware that you will have to help nudge them into the future.

MicroStrategy at BBBT: A BI Giant Working to Become More Agile

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Last Friday’s BBBT presentation was by Stefan Schmitz, VP Product Management, MicroStrategy. This will be a short post because a lot of the presentation was NDA. Look to MicroStrategy World in January for information on the things discussed.

The Company

The primary purpose of the public portion of the presentation was to discuss the reorganization and refocus of MicroStrategy. Stefan admitted that MicroStrategy has always been weak on marketing and that in recent years Michael Saylor has been focused on other issues. Mr. Schmitz says those things are changing, Saylor is back and they’re focusing on getting their message out. In case you’re wondering why a company that claims to be pushing marketing showed up with only a product management guy, they’d planned on also having a product marketing person but life intervened. Stefan’s message clearly had strong marketing input and preparation so I believe the focused message.

When we discussed the current market, Paul te Braak, another BBBT member, asked a specific question about where MicroStrategy saw self-service analytics. Stefan responded, accurately, it was self-service for analysts only and systems are too simple and miss real data access.

One key point was the company’s view of the market as shown below.

MicroStrategy market view

The problem I have is that data governance isn’t there. It’s in some of the lower level details presented later, but that’s not strong enough. The blend of user empowerment and corporate governance requirements won’t be met until the later is perceived as a top criticality by technical folks. MicroStrategy is a company coming from the early days of enterprise business intelligence and I’d expect them to emphasize data governance the way a few other recent presenters have done, and the lack of that priority is worrisome.

The Technology

On the technology side, there were two key issues mentioned in the open session.

The first was a simplification of the product line. As Mr. Schmitz pointed out, they had 21 different products and that caused confusion in the market, slowing sales cycles and creating other problems. MicroStrategy has simplified its product structure to four products: The server, the architect for developing reports and dashboards, and separate products for Web and mobile delivery.

The second is an AWS cloud implementation along with data warehousing partners in order to provide those products as part of a scalable and complete package. This is aimed at helping the company move downstream to address departmental, divisional and smaller company needs better than their history of mainstream IT sales has allowed.

This is still evolving and the company can give more information, as you’d expect.

More was mentioned but, again, it was under NDA.

Summary

MicroStrategy is an established BI vendor, one of the older group of companies and, unlike Cognos and Business Objects, still standing on its own. The management knows that the newer vendors have started with smaller installations and are moving towards enterprise accounts. It is making changes in order to go the other direction. The company wants to expand from the core enterprise space into the newer and more agile areas of BI. Their plans seem strong, we’ll have to watch how they implement those plans.

Yellowfin at BBBT: Visualization and Data Governance Begin to Meet

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Last Friday’s BBBT presentation was by Glen Rabie, CEO, and John Ryan, Product Marketing Director, from Yellowfin. I reviewed their 7.1 release webinar in late August but this was a chance to hear a longer presentation focused for analysts.

Their first focus was on the BARC BI Survey 14. One point is that they were listed as number one, by far, in how many sites are using the product in a cloud environment. That’s interesting because Yellowfin does not offer a cloud version. This is corporations installing their own versions on cloud servers.

A Tangent: Cloud v On-Premises?

That brings up an interesting issue. Companies like to talk about cloud versus on-premises (regardless of the large number of people who don’t seem to know to use the “s”) installations, but that’s not really true. Cloud can be upper case or lower. Upper case Cloud computing is happening in the internet, outside a company’s firewall. However, many server farms, both corporate owned and third party, are allowing multi-server applications to run inside corporate firewalls the same way they’d run outside. That’s still a cloud installation by the technical methodology, but it’s not in the Cloud. It’s on-premises in theory, since it’s behind the firewall.

Time for a new survey. We’re talking about multi-server, parallel processing applications verses single server technology. What’s a good name for that?

Back to Our Regularly Scheduled Diatribe

One bit of marketing fluff I heard is that they claim to be the first completely browser based UI. I’ve heard from a number of other vendors who have used HTML5 to provide pure browser interfaces, so I don’t know or care if they were first. The fact that they’re there is important, as is the usability of the interface. The later matters more. As I mentioned in the v7.1 review, they don’t hide that they’re focused on the business analyst rather than the end user, and for that target audience it is a good interface.

An important issue that points to a maturation of business intelligence in the market place was indicated by a statement John Ryan made about their sales. Yellowfin used to be almost exclusively based on sales to small pilot projects, then working to increase the footprint in their clients. He mentioned that they’ve seen a recent and significant increase in the number of leads that are coming into the funnel as full enterprise sales from the start. That’s both a testament to IT reviewing and accepting the younger BI companies and to Yellowfin’s increased visibility in the market.

“All About the Dashboard” and Data Governance

Glen and John repeatedly came back to the idea that they’re all about providing dashboards to the business user, focusing on letting technical people do discovery and the tough work then just addressing visualization for the end user. The idea that the technical people should do the detailed discovery and the business user show just look at things, slicing and dicing in a limited fashion, might be a reason they’re seeing more enterprise sales.

They seem to be telling IT that companies can get modern visualization tools while still controlling the end users. That’s still a priests at the temple model. That’s not all bad.

On one side, they’ll continue to frustrate end users by limiting access to the information they want to see. On the other side, many newer firms are all about access and don’t consider data governance. Yes, we want to empower business knowledge workers, but we also need to help companies with regulatory and contractual requirements for data governance.

Yellowfin seems to be walking a fine line. They have some great data governance capabilities built in, with access control and more. One very useful function is the ability to watermark reports as to their approved status within the company. It might seem minor, but helping viewers understand the level of confidence a firm has in certain analysis is clearly an advantage.

An interesting discussion occurred in the session and on Twitter about a phrase used in the presentation: Governed Data Discovery. Some analysts think it’s an oxymoron, that data discovery shouldn’t be governed or limited or it’s not discovery. I think it makes a lot of sense because of the need for some level of controls. Seeing all data makes no sense for many reasons, and governance is required. Certainly, too tight governance and control is a problem, but I like where Yellowfin seems to be going on that front.

But What About the Rest of BI?

As mentioned, Yellowfin is working to let analysts build reports and help knowledge workers consume reports. However, the reports are built from data. Where’s that come from? Who knows?

When I asked how they get the information, they clearly stated they weren’t interested in the back end of BI, not ETL, not databases. They’re leaving that to others. That’s a risk.

Glen Rabie pointed out, earlier in the presentation, that many of their newer clients are swap-outs of older BI technologies. For instance, he said two of his more recent clients in Japan had swapped out Business Objects for Yellowfin. Check the old Business Objects press releases from customers in the last couple of decades. The enterprise sales weren’t “Business Objects sells…” but rather “Business Objects and Informatica,” “Business Objects and Teradata,” etc. visualization is the end of a long BI process and enterprises want the full information supply chain.

As long as Yellowfin is both clear about its focus and prepared to work closely with other vendors in joint sales situations then it won’t be a problem as the company grows. They need to be prepared for that or they’ll slow the sales cycle.

Social Media Overthought

The final major point is about Yellowfin’s functionality for including social media within the product to enhance collaboration. While the basic concept is fine and their timeline functionality allows a team to track the evolution of the reports, I have two issues.

First, the product doesn’t link with other corporate-wide social tools. That means if a Yellowfin user wants to share something with someone who doesn’t need to use the tool, a new license is needed. I know that helps Yellowfin’s top line, but I think there should be some easy way of distributing new analysis for feedback from a wider audience without a full license.

Second, and much less important, is the mention of allowing people to vote on the reports. I was amused. It reminded me of a great quote from the late Patrick Moynihan, “Everyone is entitled to his own opinion, but not to his own facts.” I think the basic social tool in Yellowfin is very useful, but voting on facts seems a tad excessive.

Summary

Glen Rabie and John Ryan gave a great overview of Yellowfin, covering both the company’s strategy and the current state of product. Their visualization is as good as most others and they have some of the most advanced data governance capabilities in the BI industry.

There’s a lot of good going on down under. Companies wanting modern visualization tools should take a look, with one caveat. If you think that the power of modern systems means that functionality is clearly moving forward and should allow business users to do more than they have been able to do, Yellowfin might not match up with other firms. If you think that end users only want dashboards and want a good way of providing business workers with those dashboards, call now.

Webinar Review. Lyndsey Wise and Information Builders: Five Ways SMBs are Putting Information to Work

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This morning I attended a TDWI webinar with Lyndsay Wise, Wise Analytics, and Chris Banks, Information Builders, presenting the subject line topic. It was a nice change from the webinar earlier in the week.

Lyndsey Wise began by speaking about the differences between Small-to-Medium sized businesses (SMBs) and enterprises. While SMBs are smaller and have fewer resources than enterprises, they are also more adaptive and can more quickly make decisions that impact corporate infrastructure.

I’ll disagree with what she said in that description on only one point. Ms. Wise mentioned the lack of internal IT resources makes SMBs more comfortable with consultants, the Cloud and information appliances. Two out of three ‘aint bad. Appliances tend to be a capital expense made by enterprises wanting to retain control inside the firewall. They give enterprises more comfort. SMBs don’t typically want that kind of investment and overhead. She’s absolutely right that’s why many external IT consultants and web software vendors have successfully focused on the market.

She then turned to a discussion of the following five ways SMBs are better utilizing information:

  • Embedded BI within operations
  • Web portal expansion and information sharing
  • Mobilization of the workforce
  • Better flexibility in dashboard and analytics design – self-service and data discovery
  • Monetizing of data collected

The first point was that SMBs have had to deal far longer than did enterprises with separate operational and BI software that barely overlapped if you were lucky. Operational software companies have begun to add BI to their packages while BI vendors are better linking to operational systems, both at the data end and up front through single-signon and other interfaces enhancements that aid integration.

The growth of web portals is not new and not really in the pure BI space, but it is a key part of the solution, as Ms. Wise points out for the reason that it helps businesses share with customers, suppliers and other people and organizations in their ecosystems. I’m glad she had the point there because many people in tech sectors get focused just on their niche and don’t look at the full information picture.

Workforce mobilization issues are the same for any size business. The only difference I see is that SMBs have fewer resources for training. People wanting to focus on SMBs need to ensure that mobile apps go through user interface design cycles to present clear and easy understanding of critical information.

The fourth point is critical. It ties into what I mentioned in the previous paragraph. As Lyndsey Wise pointed out, SMBs don’t tend to have programmers, especially not ones with the inflated title of data scientist (full disclosure, “inflated” is my opinion not hers), That means UI, UI, UI. True self-service is a must for SMBs.

The final issue is another on which I’m on the fence as to the importance. Not that monetization is unimportant, just that monetization of information has been important to business for millennia before computers. All BI is ultimately about making better business decisions and that usually means a predominate roll in lower costs or increasing revenue. That’s information monetization. It’s not that the point is unimportant, it just seems redundant to me.

The presentation was then turned over to Chris Banks. Information Builders, one of the big first generation BI firms, seems to be making a big push to remind people it’s there. Given the short time frame, Chris intelligently shortened and breezed through his presentation. He gave a good overview of the breadth and depth of his company’s offerings.

The issue I have with Mr. Banks’ presentation is, no surprise to anyone who knows I focus on marketing, is how he presented the company. Information Builders, Cognos, Business Objects, et al, grew up in a time when enterprises were trying to understand the large amounts of data in multiple operational systems. They spent decades on an enterprise sell. Chris is working to position them to fit Wise’s SMB message, but he’s not there yet.

Showing a crowded diagram of the breadth of products is scary to SMBs, even with Chris’ caveat that he’d never expect anyone to buy all the products. He should have focused on a simpler slide showing how SMBs can quickly begin using his products.

Then he transitioned to a slide showing a portal, backing Ms. Wyse’s second point. Sadly, it was the Hertz portal. Not exactly an SMB play.

That continued with a NASCAR slide of global enterprise customers and a case study from a large US bank. It wasn’t until the very end that there was a case study on an SMB, a roofing contractor that achieved insight and business benefit from Information Builder’s tools.

Summary

Lyndsey Wise had a good overview of issues facing small-to-medium sized businesses when trying to better gather, manage and understand business information.

Information Builders is working to communicate with the SMB community and made an ok first stab. From the presentation, I’m not really sure how they can help, but I’m not convinced they can’t. There’s much more work to be done to better address and important market.

WhereScape at BBBT: Another Intriguing Product Without a Clear Message

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Last Friday’s BBBT presentation was by Michael Whitehead, CEO, WhereScape. The company seems to have a very interesting and useful product, but there’s a huge communications gap that needs to be addressed.

What They Do

One marketing issue to start was that I got most of this section from my own experience and WhereScape’s web site, not from Michael’s presentation. When someone begins a presentation by proudly announcing it is ““guaranteed there’s no corporate marketing in the presentation at all” while you’re presenting to a group of analysts, there’s a disconnect and it shows.

WhereScape has two products, Red and 3D, to help build and maintain data structures. The message is focused on data warehouses, but I’ll discuss that more in the next section. One issue was that their demonstration didn’t work as there seemed to be a problem connecting between their tablet and the BBBT display system, so much of what I’m saying is theory rather than anything demonstrated.

Red is their tool to build data warehouses. Other tools exist and have been around for decades, Informatica being just one competing firm.

3D is where the differentiation comes in. Everyone in IT understands that nightmare that is upgrading major software installations such as ERP, CRM and EDW systems. Even migrating from one version to the next of a single vendor can involve months of planning, testing and building, followed by more months of parallel runs to be safe. A better way of analyzing and modifying data structures that can compress the time frame can have a large positive impact upon a corporation. That’s what WhereScape is attempting.

What They Say

However, their message is all “Automation! Automation! Automation!” and the short part of the demo that worked showed some automated analysis but a lot of clicks necessary to accomplish the task. From what I saw, it will definitely speed up the tasks, if as advertised, with clear time and money savings, but it’s not as automated as implied and I think a better message is needed.

In addition, their message is focused on data warehouses while Michael said “We’re in the automation business not the data warehouse business,” which really doesn’t say anything.

Michael did talk for a bit about the bigger data picture that includes data warehouses as part of the full solution, but again there’s no clear message. While saying that he doesn’t like the term Data Lake, he’s another that can’t admit that it’s just the ODS. There’s also a discussion of the logical data warehouse, also not something new.

One critical and important thing Mr. Whitehead mentioned was something I’ve heard from a few people recently, the point that Hadoop and other “unstructured databases” aren’t really unstructured, they support late binding, the ability to not have to define a structure a priori but to get the data and then understand and define a useable structure for analysis.

What They Need to Say

This is the tough one and not something I’m going to solve in a short column. The company is targeting a sweet spot. Data access has exploded and that includes EDW’s not going away, the misnamed concept of Big Data and much more. Many products have been created to build databases to manage that data but the business intelligence industry is still in the place packaged, back-end systems were in the 1990s. Building is easier than maintaining and upgrading. A firm that can help IT manage those tasks in an efficient, affordable and accurate way will do well.

WhereScape seems to be aimed at that. However, their existing two-fold focus on automation and data warehousing is wrong. First, it doesn’t seem all that automated yet and, even if it was, automation is the tool rather than the benefit. They need to focus on the ROI that the automation presents IT. Second, from what was discussed the application has wider applicability than just EDW’s. It can address data management issues for a wider area of business intelligence sources and the message needs to include that.

Summary

Though the presentation was very disjointed, WhereScape seems to have focused on a clearly relevant and necessary niche in the market: How to better maintain and upgrade the major data sources needed to gain business understanding.

Right now, while there is a marketing staff at the company, WhereScape’s message seems to be solely coming from the co-founder and CEO. While that was ok in the very early days, they have some good customer stories, having led with Tesco’s success in this presentation, and it’s time to leverage a stronger and clearer core message to the market.

Where the issue seems to be is the problem I’ve repeatedly seen about messaging. The speed of the industry has increased and business intelligence is, on a whole, crossing Jeffrey Moore’s chasm. That means even younger firms need to transition from a startup, technically focused, message to a broader one much more rapidly than vendors needed to do so in the past.

While WhereScape has what seems to be the strong underpinnings of a successful product, they need to do some seriously brainstorming in order to clarify and incorporate a business oriented messaged throughout their communications channels – including in presentations by founders.

TDWI Webinar and Best Practices Report: Real-Time Data, BI and Analytics

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TDWI held a webinar this morning to promote their new Best Practices Report on real-time data, BI and analytics. It’s worth a glance.

The report and presentation were team efforts by Philip Russom, David Stodder, and Fern Halper. The report, as usual, was centered around a survey and was a survey of IT people rather than business users. The report relates, “The majority of survey respondents are IT professionals (63%), whereas the others are consultants (20%) and business sponsors or users (17%).” Not much room there for the opinions of the people who need to use BI. Still, for understanding the IT perspective, it’s interesting.

The most valuable pointer in the presentation was given by Dave Stodder, who pointed out what too many folks ignore: Much of the want for real-time data is bounded by the inability of the major operational systems, such as ERP and CRM, to move from batch to real-time support. While BI firms can prepare for that, it’s the other vendors providing and the users adopting systems that allow real-time extraction in an effective manner that is the big bottleneck to adoption.

One issue that the TDWI folks and many others in our industry have is a misconception around the phrase “operational systems.” Enterprise software folks have grown up thinking of operations as synonymous with business operations. That’s not the case. All three of the analysts made that error even while discussing the fact that the internet of things means more devices are becoming data sources.

Those people who provide manufacturing software understand that and have for years. There’s much that can be leveraged from that sector but I don’t hear much mentioned in our arena. Fern Halper did mention IT operations as an area already using basic analytics, but I think the message could be stronger. Network management companies have decades of experience in real time monitoring and analysis of performance issues and that could be leveraged.

Build, buy or borrow are options for software as well as other industries, but I only see people considering building. We should be looking more to other software sectors for inspiration and partnerships.

There was also a strange bifurcation that Dave Stodder and Fern Halper seem to be making, by splitting BI and analytics. Analytics are just one facet of BI. I don’t see a split being necessary.

At the end of the presentation, they reviewed their top ten priorities (page 43 of the report). Most are very standard but I’ll point to the second, “Don’t expect the new stuff to replace the old stuff.” It’s relevant to the discussion vendors seem to think that revolutionary trumps evolutionary. It doesn’t. Each step in new forms of BI, such as predictive analytics, extends the ability to help business users make better decisions. It’s layered on top of the rest of the analysis to build a more complete picture, it doesn’t replace it.