Author Archives: David Teich

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.

Webinar Review: Big Data addressed poorly

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I’ve been in computing business for almost thirty five years, but until this year it was always working for vendors or systems integrators. As a newly minted analyst, I’ve stayed away from very negative reviews. I’ve watched a few bad webinars recently and made the choice not to blog about them. However, as I’ve seen more and more, I’ve realized that doesn’t help the industry and I can’t remain silent.

On Tuesday, I watched a webinar by David Loshin, President of Knowledge Integrity, and Ramesh Menon from Cray. It was not pretty.

Let’s take, for instance, David Loshin’s five points for big data:

  • Plan for scalability
  • Go heavy on Memory
  • Free your applications from the Hadoop 1.0 Execution Model
  • Real-time ingestion and integration
  • Feed the SQL need

The first item has been around since client/server application first came to the fore. Big data has grown, in part, because of its ability to scale large volumes of data. This is nothing new.

Memory? It was a great point years ago, with Tableau and others having pushed it for quite a while. However, the last year or two we’ve been hitting the limits of pure memory solutions and I’ve seen a number of presentations from vendors focused on better integrating memory and disk depending on data latency needs. David’s statement that ““We will start seeing more applications using memory rather than disk,” is wrong. We’ll see more applications better leveraging memory, but disk isn’t going anywhere.

The Hadoop organization’s release of Hadoop v2, YARN, is a clear indication of the limitations of 1.0 and why people have also been talking about it for years. However, in the presentation, leading with 2.0 would have been better than again being a laggard about the known issues with 1.0. Either people use Hadoop and already know the issues or haven’t yet used it and will start with 2.0.

It’s not real-time ingestion the critical issue and I would have liked to see him focus more on the second half of the fourth bullet. Real-time extractions of information are moving much more rapidly than the ability to integrate it with the rest of corporate information and to provide analytical to that information.

David’s final point is the only timely one. People have recently begun to remember that evolution is easier than revolution and I’ve seen a number of vendors begin to focus on providing access to the new data sources via SQL. A lot more people providing business insight to corporations know SQL and that needs to be made available. Ramesh Menon said it better, but the point is here.

The biggest problem I had was with Loshin’s forward looking statement. I’ll almost ignore that nonsense about data lake, he’s not the only one busy trying to use a new, supposedly fancier, term for the ODS, but I’ll mention it anyway. The issue was that he claimed he saw data management moving away from the data lake as we move to in-memory. Really? The ODS isn’t going anywhere. It’s nonsense to thing that every bit of corporate information needs to reside in memory, just in case it might be needed. The ODS is becoming the central source of all operational and business data. Individual business intelligence tools and needs will drive in-memory usage for near real-time needs of specific departmental, divisional or corporate level analytics needs, but there will always be a non-memory source for all that information in order to provide consistency, appropriate levels of control and to handle data governance issues.

Now we turn to Ramesh Menon. His presentation was better than David Loshin’s, but not by much. I’m sorry, there’s no excuse for someone who puts himself forward as a voice of the industry to not understand the difference between a premise and a premises. Considering he used premise correctly in his presentation, it was terrible that it was used three times before that while describing “on-premise” computing. Everyone in our industry needs to sit down, focus and practice saying the right word.

His customer use case was a very jumbled story and an overcrowded slide with the main point being “the customer had a lot of data.” I wouldn’t have guessed. He needs to talk more about solutions, how Cray address the data.

As mentioned above, Ramesh had a very clear point about the difference between data scientists and business analysts being one reason that Hadoop 2.0 is important. The move from batch to lower latency access is part of the difference between a data scientist, someone wanting to be the priest at the temple, and a business analyst, a much larger group working to provide wider access to business information. Updating Hadoop is critical to the ability to keep it relevant.

That was a key point, the problem is that Ramesh isn’t the analyst, he’s Cray’s spokesperson. The discussion shouldn’t have been about generalities but about how Cray must have focused on Hadoop 2.0 for the Urika-XA appliance – but that wasn’t made clear. It was in the data sheet images plopped into the presentation, but reasons and results should have been openly discussed.

I’ll end with the one very interesting point from Mr. Menon’s presentation. He had a slide where he discussed four phases in the analytics pipeline: ETL, algorithms, analysis and visualization. His point is that there are very different resource requirements for each phase of the pipeline. This could be an entire presentation itself and Ramesh could focus and expand this, explaining how Cray helps to address part or all of those requirements to help present Cray to the industry.

Summary

The analysis got a couple of things right, but was mostly too late or wrong. The corporate presentation didn’t clearly link Cray to the issues involved. Both presentation halves were far to generic and descriptive with almost no descriptive takeaways. Furthermore, you could tell that neither presenter seemed to have put much time and effort into the webinar by both the content and presentation styles.

People need to learn that “there’s no such thing as bad press” is only something said by entertainers. It’s not enough to have a webinar to get your name out there. Lots and lots of companies are doing that. Thought needs to go into the presentation and practice needs to go into delivery.

There were some good tidbits in the presentation, but overall it was a mess. I was very disappointed in the hour that I lost.

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.

An ODS by any other name still smells like data

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Data warehouse theory originally posited extracting data from systems, performing transformations on them and loading the resulting schemas into the data warehouse. It was a straight flow of information. However, the difference between theory and practice quickly reared its head. Today, people are talking about Data Lakes and Data Swamps. They’re not new, they’re just the ODS updated for modern data.

Data Warehouses and the ODS

Academics don’t have to deal with operational systems. In the 1980s and 1990s, those systems were growing, with ERP, CRM and other systems increasing the complexity and volume of data. Those mission critical systems, however, weren’t designed for extraction of information. They were primarily running on RDBMS systems that had locking schemas that could grind process and transactional systems to a halt while and extraction program kept open large blocks of records while transforming basic data in star schemas. Something needed to be done.

There was also a secondary effect that was very important to some people. IT, just as with ever other department in a large enterprise, isn’t monolithic. The people managing the operational systems knew their systems were mission critical and also knew how, in reality, those systems were big but fragile. They weren’t happy with opening their operational systems to other IT folks who were interested in non-operational things. Those folks answering other business problems? They were viewed as intruders, getting in the way of the “real work.”

For both reasons, intrusions into the operational systems were something to be kept to a minimum. IT organizations began using an Operational Data Store (ODS) to quickly open the operational systems, suck all the data out, willy-nilly (yes, I decided to use that term in a tech article…), and then go back to prime performance in an isolated system.  ODS 1

It was then the ODS that was the source of the data warehouse ETL process. On a tangent, this is why the people now arguing about ETL v ELT amuse me. It’s been ELETL for decade, if we want to be honest; but who cares? I’d rather have a BLT than spend so many cycles over slightly different acronyms for concepts that ETL handily describes, even in permutations.

The ODS comes into its own

The IT folks who were working to provide reports for mid- and high-level managers were always trying to tweak enterprise software reports, trying to extract nuggets of value. The data warehouse was a step forward and helped build a bigger picture. However, the creation of star schemas and other DW techniques aggregated data and lots a lot of detail. A manager would see an issue and want to backtrack, to drill-down into the data to know more.

The ODS became the way to do so. Very quickly, the focus changed from ODS in front of the data warehouse to both working side-by-side. Having all that raw data available gave the business analysts a way of providing much more detail and information to the business user. The first big BI companies, those such as Cognos, Business Objects and more, leveraged the two data stores to provide an ability to drill down past the aggregate information into the more detailed data.ODS 2

Having that large volume of data from multiple operational systems also intrigued people who weren’t data warehouse focused. They wanted to sift the raw data for technical or performance trends, things that weren’t of interest to the typical DW designers and users, but were important to mid-level management in manufacturing, marketing and other departments. Business analysts supporting those people began to turn to more and more analysis directly on the ODS data

The ODS comes to the fore – by another name

That was happening in the 1990s, at the same time another key phenomenon was growing: The Web. The growth of the web meant a lot more data about a lot more things. Web sites are operational systems to marketing in just as critical a way as an assembly line is to manufacturing. People became interested in ensuring that what visitors to web sites did was captured and available for analysis. However, as the volume of web traffic grew exponentially, new issues had to be looked at to handle that data.

Columnar databases were one solution, a way to speed up analysis of dimensions of information across individual records. The vastly larger amount of data also helped push emerging MPP technologies and drove creation of Hadoop and other technologies that could manage much larger data sources much faster and more cost efficiently than could individual Unix servers.

However, the web folks were new to IT and grew up in a different generation than the folks who designed and drove data warehousing. It’s natural to ODS 3want to take ownership of concepts, especially those on the edge. So the folks working with these new data sources began talking about Big Data as somehow completely different than what came before. If that was the case, they needed to think of some term for the database where they dumped all the data extracted from web sites. Data Lakes became one term. We’ve heard data swamp and other attempts to create unique terms so a company can differentiate itself from others. However, there’s already a name.

The ODS exists. It’s evolved. It’s moved forward. But it’s still the ODS.

Yes, really

“But,” you say, “an ODS is operational information and the data lake is so much more!” Well, not quite. There are two main problems with that argument.

First, times change. When the ODS was coined, the focus was on the back-end systems such as ERP, CRM, accounting and other fairly closed systems. It was before the web, before the ubiquity of mobile devices, before the wall between back-end and customer-facing systems was destroyed.

As mentioned, not just web sites are but even the internet is an operational system for your business – and not just for ecommerce companies. From lead generation, to maintenance and training, the internet is a key tool for providing operational support and generating business critical operational details.

Second, just as ETL can mean a number of things, so can ODS extend past a pure theory while still being relevant. CRM systems are considered operational but still contained sentiment and other information in comments fields. Just so, the vast volume of data from a call center’s voice recording system being dumped into the ODS have two components. There are basic details about the operation of the call center, things such as number of calls, call length and other details that are purely operational. There are also additional details about customers that can be distilled for strategy purposes, including the ability to provide sentiment analysis. Just because an operational system captures data that can be used for more than purely operational decision making doesn’t obviate that the information extracted resided in an ODS.

Summary

It’s a need of information technologists from all generations to realize that things change but retain context. The ODS isn’t what it was thirty years ago, but the data lake also isn’t some new creation born full blown from the web. There are few truly revolutionary technologies. You can be a brilliant person and contribute much to technology and business and still not be a revolutionary.

The ability to manage the vastly larger amounts of data than we had twenty years ago is critical. There are many innovative things being done. However, I consider the first expert systems, the first MPP algorithms and other similar technologies to be revolutionary. The fact that what is being done to allow business to gain insight combining more and more data from even more diverse sources is no less valuable to the industry because it is instead an evolutionary change.

The ODS has evolved. It doesn’t need a new name, just a tad more respect.

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.

Qlik Sense at the BBBT: Setting Up for the Future

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Qlik was at the BBBT last week to talk about Qlik Sense. The presenters were Josh Good, Director of Product Marketing, and Donald Farmer, VP of Innovation and Design. It was a good presentation and Qlik Sense seems like the start of a good product, but let me start by discussing a tangent.

A startup’s voice: A marketing tangent

Startups usually have a single voice, the founder, CTO or somebody who is the single and sole owner of the vision. Sometimes it’s somebody who is put forward as the visionary, correctly or incorrectly. It takes a level of maturity in a company to clarify a core message to the level where it’s replicable by a wider variety of people and for the original spokespeople to let go. While the modern BI industry is still fairly young and every analyst group talks about the untapped market, Qlik is one of the biggest players in our nascent business.

Donald Farmer is a great presenter, a smart man and has been, until recently, the sole Qlik voice I hear in every presentation. While I don’t always agree with him, he’s a pleasure to hear. Yet I continually thought “why him, always?” There might be somebody else briefly doing a demo, but he was THE voice of Qlik.

It’s not only because of my product marketing experience that I was pleased to hear from Josh. He wasn’t the demo dolly, but let the presentation with Donald chiming in. They worked well together. It’s clear that both of the startup issues I mentioned are being addressed by a maturing Qlik marketing organization who are now using multiple voices well.

Qlik Sense

I’ve blogged about other companies recently, talking about the focus on UI. Thankfully, it’s spreading. Companies who focused, in the early days, on the business analysts are realizing that they need to better address the business knowledge worker. Qlik Sense has a nice, clean interface. It’s nowhere near the overcrowded confusion of most products from a few years back. For those who want to see it, the client software is freely downloadable to you can try it out.

The one issue I have is, again, the same one I’ve mentioned with many other vendors: ETL. Josh was another person who started the demo by importing a spreadsheet. Yes, I know there’s a lot of data in them and all products need to access spreadsheets, but it’s one way of avoiding the ETL issue. Other than very basic, departmental data, more complex decision making always involves other sources. It’s the heterogeneity of data that is today’s big issue. However, that’s a weak spot hidden by just about everyone.

What was nice was the software’s intelligence in building an initial data relationship diagram base on field name relationships. It’s a start and if they keep at it the feature can grow to something that can more easily show the business user the links between different pieces of information.

A number of vendors have recently begun to have their software look at data and propose initial visualizations based on data type. It’s an easy way for users to get going. Qlik Sense doesn’t do that and the response was marketing fluff, but the display to choose types is better than most. Rather than drop down to select charts, it displays the types with mini-images. That will do for now.

Mobile done well

One fantastic part of the demo was in how well they’ve integrated mobile into the system. They were going to show it anyway, but before Josh could get to it there was a problem with his PC. He quickly pulled up his iPad and, using the same account, continued on his way with the same information that was well formatted to the new display. A key point to that is that Qlik isn’t just using mobile devices for display, he was working to create visualizations on the device.

That other data…

I’ve already mentioned heterogeneity. A number of younger companies, focused on the Cloud, have created clear links to Salesforce and other cloud data sources to easily let SMB and departments access those data sources. Qlik does not have that capability, furthermore access to major ERP and CRM systems. That will still take strong interactions with IT to create links and access for the users.

That matters to me, for one example, because of the repeated demo examples from the sales arena. Yes, sales managers remain heavy users of spreadsheets, but SFA systems have made strong inroads and the ability to combine those sources quickly for sales management is critical.

Data Governance: Thinking ahead

One area where Qlik seems to excel is in thinking about the issues of data governance. Even in this early version of Qlik Sense they’ve included some powerful ways of controlling access, both from administration and a business user standpoints. I’ve seen other vendors talk about it and only some of them willing to show if questioned. Josh and Donald brought it up as part of their basic presentation and showed a nice interface.

Just as with the growth of PCs giving individuals power while hurting data governance, BI needs to get ahold of those issue and help the end user and IT work together to manage corporate data to follow business and legislative polices. Qlik’s focus on that is an important differentiator.

Summary

Qlik Sense is a new product. It has very good visualization, which should be expected from Qlik, and has moved forward to an improved UI for ease of use. While they still have issues of concern with data access, their data governance implementation seems to be ahead of the curve and is well thought out. It’s an early generation product, so it doesn’t bother me that it has some holes. The critical thing is to look at the products in the perspective of your timeframe of needs and see if it’s right for you.

Just as importantly, from my marketing perspective, is the maturation of the marketing message and team. I’m hearing multiple voices speaking the same message. On the product and corporate fronts, Qlik is moving ahead in a good direction.

SiSense at the BBBT: High Performance BI at Low Cost?

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The latest presentation at the BBBT was by Amit Bendov, CEO, Sisense. First marketing warning: If you’re going to their web site, be prepared. Maybe it’s only for some weird Halloween thing, but the yellow and black background of the web site is the one of the ugliest thing I’ve seen for a professional company. However, let’s look under the covers, because it gets better.

The company was founded in 2004 and Amit says the first sales were in 2010. There’s a good reason for that delay. They are yet another young company who talks about being a full stack BI provider, being more than a visualization tool but also supposedly providing ETL, data storage and the full flow for your information supply chain from source systems to display. That technology took a while to develop.

Technology: Better integration of memory and Disk

The heart of their system is a patent pending technology that tightly integrates cpu cache, RAM and disk to better leverage all storage methods for higher performance. The opportunities that theory provides are enough that they’ve received $50 million (USD) in venture funding, $30 million in their latest round, earlier this year.

As they are a startup, it’s no surprise that the case studies given were for SMB or departments within enterprises. That’s the normal pattern, where a smaller group takes advantage of flexibility to try new products to solve focused problems. As their customer list includes companies such as Ebay, Wix, ESPN and Merck, companies with lots of data, those early entrants increase the potential if Sisense continues to perform.

Another key technology component is their columnar database. They created a proprietary one to be able to support their management technology. That’s completely understandable as their database isn’t purely on disk or memory, but in a combined mix that needs special database management.

The final key to their technology is that they worked to ensure the software runs on commodity chips from the X86 heritage. That means it runs on normal, affordable, off the shelf servers, not on high priced appliances.Sisense hardware price comparison

The combination of the speed and affordability of the technology is justification for the rounds of funding they’ve received.

Really full stack?

One fuzziness that I’ve mentioned with other full stack vendors is the ETL side of the process. The growth of Cloud companies such as Salesforce, and the accessibility of their APIs, means that you can get a lot of information out of systems aimed at SMB. However, true enterprise ETL means accessing a very wide variety of systems with much less easy or open APIs. When Mr. Bendov talked about multiple systems, it seems, from presentation and demo, that he’s talking about multiple instances of simple databases or open APIs, and not a breadth of source types. There wasn’t a lot of choice in the connection section of his application.

That’s not a problem for companies at Sisense’s state of maturity, as long as there’s a business plan to expand to more enterprise sources. They need to focus on proving the technology in the short term and having more heterogeneous access in their tool bag for the future.

Another issue is the question of what, exactly, their database is. Amit Bendov made a brief comment about not needed data warehouse, but as I and others quickly brought up, there are two problems with that statement. First, they would seem to be a data warehouse. They’re extracting information from source systems, transforming that information even if not into the old star-schema structures, and providing the aggregate information for analysis. Isn’t that a high level description of a warehouse? Second, as they’re young and focused on SMB or departments, as with other companies who serve visualization, they might need to look at customer demands and get access to corporate data warehouses as another source.

The old definition of a federated data warehouse seems to be evolving into today’s environment where sometimes an EDW is a source, other times a result and sometimes it’s made up of multiple accessible components such as Sisense and other databases. Younger companies who disparage EDWs need to be careful if they wish to address the enterprise market. The EDW is evolving, not dying off.

User interface and more

One of my first trips to Israel was, in part, when my boss and I had to bring a couple of UI specialists to show Mercury Interactive’s programmers why it might be nice to rethink application interfaces. It’s wonderful what twenty years have wrought. Amit Bendov says that Sisense has one UI specialist for every two programmers, and the user interface shows that. While I mentioned that they need broader ETL access, the simplicity of getting to sources is clear. While you still will need a business analyst to understand some column names, it’s a very easy to use interface.

The same is true in the visualization portions of their application. While it’s still a simpler tool, it has all the basics and is very clear to understand and use.

Paving the way for their spread into enterprise, the Sisense team also supports single-sign on, basic data access control, both in global administration and in the user interface, and other things that will be needed to convince a larger corporation to spread the technology.

Summary

Sisense looks like a startup in a great position. Their technology is well thought out and seems to be performing very well in the early stages. Affordable, fast, business intelligence is something nobody will turn down.

The challenge is two-fold:

  • Do they have the technology plans to help them address larger enterprise issues?
  • Do they have the mindset to understand the importance not only in marketing, but in changing the marketing to a more business focus?

This is the same refrain you’ve heard from me before and which you’ll hear again. This is the Chasm challenge. Their technology has a great start, but their web site and presentation show they aren’t yet thinking bigger and we’ll have to see what the future holds both for the technology and the messaging.

Business intelligence is a very visible market and one growing quickly. While small companies need to focus on the early adopters, they must very rapidly learn how to address the enterprise, both in products and marketing.

High performance BI at a reasonable cost is a great sell, but Sisense isn’t yet read for full enterprise. Sisense has a great start but life is fluid.

Logi Analytics at BBBT: Strong user interface, weak message

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Logi Analytics visited the BBBT last Friday. The presenters were Brian Brinkman, VP Products, and Charles Caldwell, Principal Solutions Architect. Logi Analytics is another player in the front end, the user interface to provide useful and timely information to the business user.

The Good Looking Product Side

I’ll start with the demo, though it came last, to begin with what I liked.

Logi Analytics is rightfully proud of their user interface. During the presentation, Brian and Charles mentioned their focus on usability and that the company had UI experts and customers work to drive the creation of the interface. It shows.

It’s not flashy nor is it kludgy. It’s a pretty clear and easy to use interface for starting with tabular views of data and quickly creating graphics to display the information. One little feature I really liked was an intermediary step that really helps users review information. You can have a column after a data column which displays a slider showing where that data fits in relations to the rest of the rows, below or above average.

That and many other features show that business folks used to spreadsheets can begin to look at what they know and more naturally move to modern visualizations.

The one nit I have is that their focus on the front-end means they didn’t really show how their technology supports IT and business analysts behind the scenes so they can support the business users. They’ve done a great job on the interface, but I’m not sure if there’s a lot of meat underneath.

The Questionable Business Side

They’ve been around since 2000 and, according to one slide and a brief message, their early focus was on XML to provide information from business systems to web applications. Their October 2013 round of investment doubled their previous total and brought investments to slightly over $50 million. So, for a 14 year old company with that much money and a focus on business users, one question immediately pops up for me when I look at their leadership page, one you’ve heard me ask of other small companies: Where’s marketing? A lot of people to build product and a couple to sell product, but nobody listed at the highest level who is focused on ensuring a match between products, market needs and messages to bridge that.

The lack was demonstrated by the presentation. They performed some surveys, but they don’t know how to bubble up the ideas on clear slides, with the information remaining far to technical and often hard to read. There was one comment about a term when the presenter said “what my marketing people call…” That shows they have some marketing and that they don’t think much of the organization nor is the team in the field willing to use consistent terms as a corporate image and a unified team.

In addition, they make the claim they’re a market leader while, since they’re private, refusing to give any details to substantiate that claim. They did tell us that around 1/3 of their business is OEM, which is very good for a company determined to expand BI into more business areas.

Then there’s getting their message straight. One overbuilt slide showed survey results implying that IT emphasized dashboard building much more than business users cared. Logi Analytics took that as a way to better focus on business user needs but only a few slides later they showed a continuum of self-service analytics they want to provide and three of the five boxes emphasized dashboards.

Defining Self-Service Analytics is Key

Back to something being done well. Everyone talks about self-service analytics but there’s no consensus on a definition. Logi Analytics is taking an honest look at the issue.

The best discussion in the presentation was on the continuum mentioned above. They were the BBBT presenters who best provided a definition similar to mine. They point out that self-service is in the analytics, in the data discovery and wandering through data. The background of getting it and the formality of accepted reporting being controlled by central authorities are something IT will always remain strongly involved in providing. It’s the ability to independently surf the information that needs to be enhanced. They’ve made a great start in clearly defining what self-service really is so they can address how that matters to end users rather than slapping a whole lot of information into the tool so business analysts can get into details but knowledge workers get confused.

That also ties into my mention of the nit on the demo section. It’s well and good to provide a great interface for the business knowledge worker. However, they still must be supported by analysts and IT staff. A strong platform and suite will have the ability to provide that. Logi Analytics might, but it wasn’t seen. Make sure you ask.

Summary

It’s the usual conundrum for startups. They have the beginnings of a strong product and the founders seem to have a good vision and are on their way to clarifying that vision. However, it’s still the focus of founder->developer->sales without marketing to look at it all, collate what everyone’s doing and build better corporate and product foundations which will help grow. It’s a crowded market and a lot of weeding out will happen within the next three to five years.

Marketing’s job is to combine vision, technical knowledge, and market information to create a holistic view of where the company show go and how to get there. Sadly, too many folks in high tech (and, honestly, elsewhere) think it’s only about pretty graphics and words. While other groups focus on development, sales, OEM relations, support and more, marketing’s needed to be the generalists.

They have a good start, but without more priority on that core marketing task, they’ll be at risk. The chasm approaches and the startup mindset rarely gets companies over it.