Filling in Big Data’s Missing Link: Making Big Data Pay for Itself

Say hello to Bashes — the first cloud-apps that enable companies to turn Big Data into new sources of revenue

I don’t want to sound overly dramatic, but today’s the day GoodData makes it possible for companies to finally monetize Big Data. That’s because today we unveil our first Bashes — cloud-based business mashups — on our platform that enable anyone, in any size business, to turn mountains of disparate data into insight that finds new sources of revenue, boosts profit and builds a competitive edge.

We call these new solutions Bashes because they combine the best elements of consumer apps with modern, enterprise-class technologies. That means consumer apps’ clean and intuitive user interface, ease of use and device independence, with cloud-based business technologies that collect and manage structured and unstructured data from hundreds of sources. With Bashes, businesses can discern meaning from all the data flooding in from emails, social media, enterprise software and cloud apps.

I firmly believe this is revolutionary. Bashes not only change the economics of the Big Data market, they also deliver on the promise that companies have struggled to fulfill for years.

Here’s what I mean: Today, everything is measurable, and everything is measured. As a result, Big Data is becoming big business. Market research firm IDC predicts the market for Big Data technology and services will reach $16.9 billion by 2015, from $3.2 billion in 2010, but much of this spending will focus on infrastructure — the plumbing that enables companies to download, collect and store vast amounts of structured and unstructured data. It’s as if companies are collecting data for a rainy day, with the hope that someone, somewhere, will help them figure out how to make money from all that data now that they have it.

In the immortal words of Yogi Berra, it’s like déjà vu all over again. After all, it’s why SAP paid $6.78 billion for Business Objects, Oracle acquired Hyperion Solutions for $3.3 billion and IBM spent $4.9 billion to buy Cognos — all makers of business intelligence infrastructure software designed to help IT and business analysts cull insight from data. It never worked as promised, primarily because of the expense, IT heavy lifting and technical expertise these infrastructure tools require.

Now, thanks to the cloud, everything has changed. Finally, we have the technology to pull in data from hundreds of sources — no matter if it’s social media, email, cloud-based apps, suppliers’ enterprise software or internal applications. At GoodData, we’re leveraging the cloud to offer pre-built apps for different functions — such as sales, marketing and customer engagement — and have created a platform that enables any company to add new apps for their specific needs.

Notice I said these are apps. That’s a key distinction because it allows each Bash to automatically present thought leadership by business function, with best practices that make it easy for business people to determine what really matters. Now contrast that to BI infrastructure tools from Oracle and others, where IT departments have spent years and millions of dollars trying to integrate products that were never meant to work together. Does that sound like a good use of time to you?

And because it’s the cloud, our apps and our platform are democratic. You don’t have to work in a large company, blow your budget or need a Ph.D. in computer science to recognize what all that data is telling you and make smart decisions, faster.

So when I say this is revolutionary, I mean it — literally. With our apps and our platform, we’re democratizing both data and business insight — so that any business person, in any company, on any device can turn Big Data into a competitive advantage. That’s power to the people, and I say let the revolution begin.

Is an Enterprise Twitter on the Horizon?

Twitter’s latest iteration of its site is great, but  it’s abundantly clear that the newly dumbed down design is aimed exclusively at the consumer.  But what about the enterprise?  Does the new Twitter design mean that ultimately, there will be a second conception of the beloved social networking tool, an enterprise edition?

Now, keep in mind, in this context “enterprise edition” does not mean a Twitter app built in ABAP that would require the user to navigate eleven screens in order to Tweet.  That would be the SAP version.  (They could call it “Sapper”, as in sapping the users’ energy and patience.)

No, an enterprise edition as it relates to Twitter would include the following, while maintaining its user-friendliness:

  1. Corporate policies and policy management.  Unlike regular Twitter, it wouldn’t do to have employees lobbing grenades at one another.
  2. Comprehensive data persistence and archiving. This would mainly be for auditing and compliance purposes.  And the company would want to make sure that everyone in the organization is keenly aware that if they Tweet “You looked really hot in the project planning session today” to a colleague, it’s stored and logged in the company’s database.
  3. Security (access controls, etc.) Users would only have access to the information that they would be permitted to see and/or act upon.
  4. Integration with anti-virus and content filtering tools. This one’s obvious.
  5. Application development (plug-ins, integration with productivity tools)
  6. Enterprise-class administration tools to support some of the above requirements.

The point would be to provide a simple and quick way (and just as importantly, a uniform and standardized format) for workers to communicate and share resources with each other.

Enterprise versions of social networking tools already exist, the most prominent being the very-successful startup, Yammer. (We use Yammer extensively at GoodData). There are numerous other players in the market place as well, including biggest Twitter competitor: Google+.

So, is Twitter poised to enter the fray?  It appears not.  As a matter of fact, the new design seems to fulfill one of Twitter’s main goals; to increase the simplicity of use.  And, at the recent Web 2.0 Summit in San Francisco, Twitter CEO Dick Costolo talked of many things, but an upcoming enterprise version of Twitter was notably not one of them.  With usage approaching 300 million tweets per day, for now, it appears, Twitter has other fish to fry.

Meet the new BI. Not the same as the old BI.

GoodData announced earlier today a $15M B-round of financing led by Andreessen Horowitz.   Mark, Ben and the rest of the team have managed to quickly build one of Sand Hill’s leading venture capital firms, but their influence is felt well beyond Silicon Valley.

Like a lot of entrepreneurs, I love reading Ben Horowitz’s blog, and since I’ve been selling to enterprise customers for over 20 years, I especially loved Ben’s post last November: Meet the New Enterprise Customer, He’s a Lot Like the Old Enterprise Customer

Ben argues that as much as we all like the consumerization of IT, real adoption in large enterprises will require a more traditional sales approach. We agree, and it’s why we are thrilled to be partnering with Andreessen Horowitz and adding general partner John O’Farrell to our board.

But disrupting the $25 billion BI and Data Warehousing space is going to take a little more than great enterprise selling. The BI vendor approval ratings are probably below those of the US Congress and most of the BI software ever sold ends up as a shelf-ware!

That’s why we’re going to balance traditional enterprise selling and a product-first customer experience. Unlike traditional BI, that still dump-trucks software onto the laps of unsuspecting enterprise buyers, we have to sell, deliver and delight our customers. We can’t just take the money and run; our SaaS business model keeps us honest.

So, how do we plan to overcome the challenges that Ben lists in his post? Let me focus on a few of his many killer quotes:

“Many companies literally do not know how to buy new technology products”

We see this clearly in the enterprises we are already selling. The BI technology stack is so convoluted that large companies often need to hire consultants simply to help them evaluate the BI products, organize the bake-offs and the selection process. No start-up is set up for success in a procurement process that is designed to avoid innovation, and that clearly advantages the incumbents.

To overcome this, we are not selling the traditional IT tools to IT audiences. GoodData is not another piece of the complex BI value chain. Our semi-official tagline is “GoodData equals BI minus BS”. Our economic buyer is the functional VP in a medium or large organization. It is the VP of Sales or Marketing rather than the head of the BI competency center. Our sales cycle usually takes less than six weeks rather than six months, and when we do sell directly to the IT department, they are usually in an S.O.L. situation.

Once deployed, enterprises develop great affection for the technology that runs their companies.

That’s the irony about BI. While technically deployed, it’s rarely actually used. Few organizations or practitioners have any affection for their BI vendor or their software sitting on the shelf. Unlike line-of-business, IT systems do not effectively run the business. There are few companies that can actually manage their business by the metrics, and few business users that can easily use a BI tool. And this is the problem we’re solving. We do this by making BI approachable and pervasive, through our pre-built analytics apps, and by integrating our dashboards into end-user applications and processes (such as or Zendesk) as much as possible.

Enterprise users are concerned with getting home to see their 8 year old’s pee wee baseball game

This is why we run a fully managed service. My vision for GoodData has always been of an end-to-end product that includes not only the infrastructure components (ETL, Data Warehouse, analytical engine…) but also the technical operations, support and best practices, so that we can deliver a complete service to our customers. We even publish our Operational & Service Performance here:

I could go on all day quoting more from this and other AH blog posts, but the fact of the matter is that the new enterprise customer needs new BI, and GoodData is here to help.

Mr. Jassy, Tear Down This Wall!

Andrew Jassy
SVP, Amazon Web Services

Hi Andy,

I am not going to ask you how are you doing. For everyone in the Amazon Web Services eco-system, the last 24 hours have been brutal. But I’d like to share my perspective with you, and offer a couple of suggestions:

I believe that in the long run this will be a positive day for the cloud computing movement. Naysayers seeking evidence to avoid the cloud have new ammunition, those hyping the cloud are experiencing its limitations, and the leading cloud provider, your company, is learning from the major outage the importance of being humble and cooperative.

I also believe that the way AWS behaves needs to change. You built the leading infrastructure-as-a-service provider with a level of secrecy typical of a stealth startup or a dominant enterprise software platform vendor. It works for Apple – they deliver a complete integrated value chain. But it is not your position in the cloud ecosystem. Today’s outage shows that secrecy doesn’t and won’t work for an IaaS provider. Compete on scale and enterprise readiness, and part of readiness is being open about your internal architectures, technologies and processes.

Our dev-ops people can’t read from the tea-leaves how to organize our systems for performance, scalability and most importantly disaster recovery. The difference between “reasonable” SLAs and “five-9s” is the difference between improvisation and the complete alignment of our respective operational processes. My ops people were ready at 1:00 am PT to start our own disaster recovery, but status updates completely failed to indicate the severity of the situation. We relied on AWS to fix the problem. Had we had more information, we would have made a different choice.

This brings me to my last point: communication. Your customers need a fundamentally different level of information about your platform. There are some very popular web sites that try to re-engineer the way AWS operates. These secondary sources – based on reverse engineering and conjecture – provide a higher level of communication than we get directly from the AWS pages. We live in the Twitter, Facebook, Wikipedia and Wikileaks days! There should not be communication walls between IaaS, PaaS, SaaS and customer layers of the cloud infrastructure.

Tear that wall of secrecy down, Mr. Jasse. Tear it down!


Roman Stanek
CEO and Founder, GoodData (2009 AWS Startup Challenge winner)

P.S. I am publishing this letter on my blog. It’s part of open communication between our companies.

The Masses Against The Classes

“When you open BI to the masses, people get a taste of what they can do and start demanding more and more information and analytics” Dan Vesset, IDC analyst, Computerworld, June 21, 2004

“Let them eat cake”. Marie Antoinette, Versailles, 1789

I’ve always found the BI industry’s fascination with elitism a throwback to the old days of IT. It seems that most of the industry calls users with no access to their tools “the masses”. And it gets worse. Bloggers from Endeca call them half jokingly “the angry mobs” and SAP has BI for “the rest of us”. All these words describe a business user who doesn’t have the time or skills to operate a complex BI solution designed for electrical engineers (who go by the name of IT). BI has penetration rate of 10% and everybody else is “the rest of us”.

It’s not just BI. The telco industry thinks their customers reside in “the last mile” – as far away from what’s important (the core of the network) as you can get. Shouldn’t their customers be in “the first mile”? And now BI is adopting the same “last mile” language, and the intent is the same: “keep my business users as far away as possible so I can focus on the core of my BI system.”

Making BI accessible to the “angry mobs” is in contradiction with BI industry’s quest for ever more complexity and hype. Petabyte warehouses, data visualization, social media analytics, predictive clustering, corporate performance management are the current industry buzzwords. Press releases and PowerPoint charts are full of names like Pig, Hadoop and Hive. These trends and tools were designed for the selected few; not for the average business user.

My vision for GoodData was always very different. Our goal is to get rid of the convoluted BI value chain. We are using the economics of the cloud to offer a service that can be used by a business audience. I am on a personal mission to support “the masses against the classes” and to build BI that is not a dumbed down version of an expensive, complex and brittle enterprise solution. I’ve always believed that the enterprise data warehouse is the place where data goes to die, leaving the poor business users with Excel spreadmarts.

This is why we just announced a fully integrated and free service: GoodData for Zendesk. Every Zendesk Plus+ customer gets free analytics from us; and the setup time is less than 5 minutes. And why free? We actually believe in what Dan Vesset wrote back in 2004. That once our users get a taste of what they can do with it they will start demanding more and more information and analytics. GoodData is BI for the business user. Something the elitist industry will call BI for “the masses”, “angry mobs” or even “the rest of us”…

With friends like Forrester and Gartner, IBM and SAP don’t need enemies…

The Innovator’s Dilemma by Clayton M. Christensen is my favorite business book – its main idea (disruptive technologies serve new customer groups and “low-end” markets first) was the guiding principle of all my startups. The best part is that even though everybody can read about the power of disruptive technologies, there is no defense against them. Vendors can’t help themselves. They study The Innovator’s Dilemma, pay Christensen to speak to their managers, but their existing customer base and “brand promise” prevent them from releasing products that are limited, incomplete or outright “crappy.” That’s what makes them disruptive. And industry analysts seem to be the only hi-tech constituency that has either never read Christensen, or is still in absolute denial about it. It makes sense: a book claiming that “technology supply may not equal market demand” is heresy for people who spend their lives focused primarily on the technology supply side.

Christensen argues that vendors no longer develop features to satisfy their users, but just to maintain the price points and maintenance charges (can you name a new Excel feature?). But in many cases the vendor decisions are driven more by industry analysts and their longer and longer feature-list questionnaires. The criteria for inclusion into the Gartner Magic Quadrants and Forrester Waves seem to be copied straight from Christensen’s chapter: “Performance oversupply and the evolution of product competition”. Analysts are the best supporters that startups can have: they are being paid by the incumbents to keep them on a path of “performance oversupply”, making them so vulnerable to young vendors “not approved” by the same analysts!

Forester BI analyst Boris Evelson gives us a great example of this point in his blog about “Bottom Up And Top Down Approaches To Estimating Costs For A Single BI Report”. While Boris is a super smart BI analyst, he somehow failed to observe that his price point of $2,000 to $20,000 per report opens a huge space for economic disruption of the BI market. Anybody interested in power of disruptive technology in BI should listen to a recent GoodData webinar with Tina Babbi (VP of Sales and Services Operations at TriNet). Tina described how the economics of Cloud BI enabled her to shift TriNet’s sales organization “from anecdotal to analytical”. This would not be possible in the luxury-good version of BI, where each report costs thousands. Fortunately, Tina is paying less for a year for a “sales pipeline analytics” service delivered by GoodData than the established vendors would charge for a single report.

I hope Boris’ blog post will appear in one of the future editions of The Innovators Dilemma as a textbook example of how leading analysts failed to recognize that established products are being pushed aside by newer and cheaper products that, over time, get better and become a serious threat. And with friends like Forrester and Gartner, the incumbents don’t really need young and nimble enemies…

You will not see us in your accounts

The analyst firm The 451 Group asks technology companies “Who else do you see in your accounts?” Being “seen in the account” is perceived as a sign of market presence and ability to execute. And the opposite is true as well. Not being seen in accounts is sign of weakness and lack of market penetration. It’s also a proxy for the longevity question: “Will they even survive if they are not on anybody’s radar screen.”

My perspective is completely different. I believe that being seen in the accounts of large competitors is a sign of confusion and a complete waste of time and money. Startups are best when they disrupt existing markets, not attack them head on. Any sufficiently disruptive technology should be first deployed in a market segment that is seen as secondary or completely irrelevant by the big guys.

Established companies often compete on feature/functionality depth — delivering more features at an ever diminishing rate of value to customers to extract more money from them. Clearly not an interesting place to be for a young company.

I would like to promise here to our large competitors: You will not see Good Data in your accounts if:

  • your customers believe in a single version of truth
  • you deal with BI and data warehousing “experts” who attend TDWI seminars
  • Inmon Vs. Kimball matters to you
  • your projects are measured in months or six figure dollar numbers
  • you engage in star-versus-snowflake schema debates
  • your product offers 30 ways to format a decimal number
  • producing 1,000 different reports a day is one of your product claims

I could go on and on. Simply put – every time we read that competitor XYZ doesn’t see us in their accounts, we consider it a small victory. We don’t want to be seen in your accounts. At least not until we are ready…

Entrepreneur Country – Land of Opportunity

I spoke at the Entrepreneur Country forum at Institute Of Directors in London earlier today. The event was organized by Ariadne Capital (Disclosure: I am one of Ariadne investors). Here is the feedback from the audience via Twitter and below is my keynote:

“Business-IT Chasm”: The Business Perspective

My plan for today was to write more about the “Business-IT chasm” but I came across a great blog post written by Jorge Camoes that reveals the business perspective of this divide. There is nothing better than the first hand experience:

IT will try to change your project, naturally. Try to avoid the “security bomb” (their favorite). You know how poor their expensive BI toys are, and you should know what they can and can’t do with them. Minor concessions can earn you some points. When they tell you they can’t implement your core ideas be prepared to fake genuine surprise, compare costs (again) and emphatically say that their options clearly don’t meet the organization’s needs.

My suspicion that business has limited ability to influence the electrical engineers is demonstrated by this quote:

Pissing off the IT department is one of the most enjoyable games in corporate life, but be a gentleman and don’t make them look stupid. They don’t usually have a good sense of humour and take their quest to conquer the world very seriously. If you really want to implement the dashboard, don’t make it an island if you can avoid it (connect it to the tables in the IT infrastructure, instead of copy/pasting data).

Here is the link to the full post.

The New Chasm

I believe that readers of my blog are familiar with the chart below. It is the classical “Crossing the chasm” diagram from Geoffrey A. Moore’s book Crossing the Chasm: Marketing and Selling High-Tech Products to Mainstream Customers. This book was published back in 1991 and it is still number two on “Twelve Business Books in One Hour for the Busy CEO” list. The main argument that Geoffrey Moore makes here is that the “early adopters” have no ability to influence “early majority” and it leads to a chasm that is very difficult for startups (or any company with disruptive technology) to cross:

Adoption Cycle

This book was written in the days when startups typically sold to electrical engineers (a.k.a. IT) and Brad Burnham described it well in his recent post:

In the old days, electrical engineers focused on getting computers to work not on getting people to engage with the systems built on top of those computers. The folks that built enterprise software were vaguely aware that their systems had to be accessible to the humans that used them but they had a huge advantage. The people who used them did so as part of their job, they were trained to use them and fired if they could not figure them out.

This is why even Wikipedia uses the following example to describe the end-user:

The end-user or consumer may differ from the person who purchases the product. For instance, a zookeeper, the customer, might purchase elephant food for an end-user: the elephant.

But virtually no startup gets funded today if it sells directly to electrical engineers. Innovation happens in the consumer space anyway and so the assumption is that any disruptive technology (social networks, SaaS, web2.0…) gets adopted first by the end-users and then it is picked up by the IT. But here comes the new chasm: low ability of end-users to influence IT:

Reversed Adoption Cycle

This chasm is the new manifestation of the classical “Business-IT” gap but this time is the innovation flow reversed: business leads and IT follows. And this new flow doesn’t make it any easier to cross the new chasm

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