Winning MicroStrategy Business Partner award

We're incredibly thrilled with the Business Partner award that MicroStrategy awarded Kognitio at their London Symposium event. As you know, we have been working with MicroStrategy and their front-end mobile, cloud and web-based BI applications for some time as a complementary technology to our high performance in-memory analytic database, WX2.

Over the years we have advocated to end-user organizations the benefits of using MicroStrategy on top of Kognitio to accelerate their efforts to understand more about their large and complex data volumes - or Big Data - in shorter timescales and with greater ease.

Big Data Analytics in the Cloud is definitely here to stay and we can think of no better or efficient solution for organizations to tackle their Big Data analytics needs than with Kognitio and MicroStrategy. Thank you again MicroStrategy!

For the full news release, click here

Driving successful BI and analytics projects

The amount of data being created and used in business is growing at a phenomenally fast rate. Whether from inside and outside the enterprise, whether click-streams, transactional data, RFID data, customer data or social behavior information, the challenge for businesses to make sense and derive value from it all can seem daunting.

But it needn't be. For years, Kognitio has been working with global organizations to store, process, integrate and analyze their ever-increasing Big Data volumes. In fact, we're passionate about helping businesses mine, analyze and get demonstrable value from their large data sets that they can then turn into actionable intelligence.

Our high-performance in-memory analytic database platform, Kognitio WX2, helps organizations around the globe to understand more about their business and their customers in shorter timescales and at a price that does not break the bank. From large corporates to smaller businesses, companies of all shapes and sizes run Kognitio WX2 to analyze Big Data sets quickly and efficiently, allowing them to make more informed, better business decisions that help them to drive growth and reduce costs.

As the data explosion continues, organizations count on Kognitio and its in-memory analytic database solution to get comprehensive answers to their questions. Where other solutions cannot cope with overwhelming data volumes and force the user to rely on data samples, Kognitio has helped numerous customers survive the Big Data phenomenon and analyze whatever, whenever and get answers to complex questions in sub-second response times.

Although Kognitio offers its WX2 database as an on-premise solution either as a software-only license or as a fully configured data warehouse appliance, Kognitio also allows companies to get the analytical insight they need for a low-cost monthly fee via the Kognitio DaaS Cloud. The DaaS Cloud offers WX2 as a secure “private cloud” solution providing maximum flexibility for a low cost of entry into data analytics and warehousing.

WX2 complements and drives the analytic stack:

Counting triangles - new performance study, Kognitio triumphant

Following the challenge thrown down by Vertica and then by an Oracle member of staff, Kognitio decided to rise to the occasion and prove how its WX2 in-memory analytic database would perform against a 86 million row data set. The data was provided by Vertica and is publicly available. The benchmark that was run using Vertica and Oracle also included other technologies such as Hadoop and PIG.

The tests themselves centered around counting triangles in an undirected graph with reciprocal edges, the idea being to queries to find out the quantity of vertexes and edges, which edges are joined and which vertexes join which edges, which is regarded as a computationally intensive exercise. Such a concept can be used to understand social networks and how people are connected and interact with others.

All the tests were run on the same hardware configuration, essentially a cluster of 4 nodes. The results were astounding and are as follows:

• Kognitio WX2 - 11.48 seconds
• Oracle, post a re-write of SQL - 14 seconds
• Oracle, pre the re-write - 90 seconds
• Vertica - 97 seconds
• PIG - 2,151 seconds
• Hadoop - 3,900 seconds

We're extremely excited that Kognitio WX2 won out and would also like to extend our thanks to Vertica for setting the data warehousing community abuzz with this challenge. Similary, for providing the data set as well as the SQL language statements. And for the sake of transparency, here are the links to the research as well as more details on what hardware and software was tested on the 86 million row dataset.

Kognitio ran the tests using WX2 on 4 HP servers, each with 128GB of RAM and 24 cores per server.

Vertica ran the tests using Vertica, PIG and Hadoop on 4 HP servers, each with 96GB of RAM and 12 cores per server. Results can be found here: http://www.vertica.com/2011/09/21/counting-triangles/

Tests were run using Oracle Exadata 2-2 hardware with 2 socket, 12 core Westmere-EP nodes and Oracle Database 11.2.0.2. Results can be found here: http://structureddata.org/2011/10/17/counting-triangles-faster/?utm_source=rss&utm_medium=rss&utm_campaign=counting-triangles-faster

To download the data set used in all tests, go to:
http://www.vertica.com/benchmark/TriangleCounting/edges.txt.gz

To download the query statements, go to:
https://github.com/vertica/Graph-Analytics----Triangle-Counting

New report on Big Data Analytics

We are proud co-sponsors of a new report from TDWI on the subject of Big Data Analytics. Published late September 2011, the report is written by expert Philip Russom and he conducted a survey of 325 data warehousing professionals on the topic of Big Data Analytics. There are some interesting statistics in the report and they support the recent emergence of topics such as big data, analytics and the Cloud.

In particular:

- only 7% of those asked had never heard of or hadn't got a "big data" problem

- other terms used to describe the phenomenon include: big data analytics; advanced analytics; large data set analytics, a pain in the a... (seriously....)

- the barriers to adopting a solution for big data analytics include cost, skill set, staffing and scalability

- while 70% regard big data as an opportunity, 30% see it as a pain

- in 3 years time, 31% of those surveyed believe 10-100 TB will be the size of their data warehousing environments

- a third of those asked think they will replace their analytic platform in the next 3 years

- 30% would prefer a cloud-based analytic platform as opposed to on-premise

- drivers to replacing their platform include "cannot scale up with existing platform" (42%) and "need/want a cloud/SaaS platform (15%)

- over the next 3 years, respondents will adopt: a private cloud (22%); in-memory database (26%); data marts for analytics (38%)

- "clouds", "SaaS" and "analytic DBMS" are deemed areas of "good potential growth"

Feel free to download the report from the Resource area of our website.

MapReduce won’t overtake the EDW anytime soon

Is MapReduce the Holy Grail answer to the pressing problem of processing, analyzing and making sense of large and growing data volumes? Certainly it has potential in this arena, but there is a distressing gap between the amount of hype this technology – and its spinoffs – has received and the number of professionals who actually know how to integrate and make best use of it.

Industry watchers say it’s just a matter of time before MapReduce sweeps through the enterprise data warehouse (EDW) market the same way open source technologies like Linux have done. In fact, in a recent blog post, Forrester’s James Kobielus proclaimed that most EDW vendors will incorporate support for MapReduce’s open source cousin Hadoop into the heart of their architectures to enable open, standards-based data analytics on massive amounts of data.

So no more databases, just MapReduce? I’m not so sure. But don’t misunderstand. It’s not that MapReduce isn’t an effective way to analyze data in some cases. The big names in Internet business are all using it - Facebook, Google, Amazon, eBay et al - so it must be good, right? But it’s worth taking a more measured view based both on the technical and the practical business merits. I believe that the two technologies are not so mutually exclusive; that they will work hand-in-hand, and in some cases, MapReduce will be integrated into the relational database (RDBMS).

Google certainly has proven that MapReduce excels at making sense out of the exabytes of unstructured data on the web; which it should, given that MapReduce was designed from the outset for manipulating very large data sets. MapReduce in this sense provides a way to put structure around unstructured data. We humans prefer structure, it's in our DNA. Without structure, we have no real way of adding value to the data; unstructured data analytics is something of an oxymoron for a pattern seeking hominid.

MapReduce helps us put structure around the unstructured so we can then make sense of it. It creates an environment wherein a data analyst can write two simple functions, a "mapper" and a "reducer," to perform the actual data manipulation, returning a result that is at once both an analysis of the data it has just mapped and summarized, as well as the structure for further analysis that will help provide insight into the data. Whether that further analysis is done in a MapReduce environment might be the more appropriate question.

From an infrastructure standpoint, MapReduce excels where performance and scalability are challenges. Applications written using the MapReduce framework are automatically parallelized, making it well suited to a large infrastructure of connected machines. As it scales applications across lots of servers made up of lots of nodes, the MapReduce framework also provides built-in query fault tolerance so that whatever hardware component might fail, a query would be completed by another machine. Further, MapReduce and its open source brethren can perform functions not possible in standard SQL (click-stream sessionization, nPath, graph production of potentially unbounded length in SQL.)

So what’s not to love? Well, at a basic level I believe the MapReduce framework is an inefficient way of analyzing data for the vast majority of businesses. The aforementioned capabilities of MapReduce are all well and good, provided you have a Google-like business replete with legions of programmers and vast amounts of server and memory capacity. Viewed from this perspective, it makes perfect sense that Google developed and used MapReduce: because it could. It had a huge and growing resource in its farms of custom-made servers, as well as armies of programmers constantly looking for new ways to take advantage of that seemingly infinite hardware (and the data collected on it), to do cool new things.

Similarly, the other high-profile adopters and advocates are also IT-savvy, IT-heavy companies and, like Google, have the means and ongoing incentive to get a MapReduce framework tailored to their particular needs and reap the benefits. Would a mid-size firm know how? It seems doubtful. While it is claimed that MapReduce is easy to use, even for programmers without experience with distributed systems, I know from field experience with customers that it does, in fact, take some pretty experienced folks to make best use of it.

Projects like Hive, Google Sawzall, Yahoo Pig and companies like Cloudera all, in essence, attempt to make the MapReduce paradigm easier for lesser experts to use and, in fact, make it behave for the end user more like a parallel database. But this raises the question, Why? It seems to be a bit of re-inventing the wheel. IT-heavy is not how most businesses operate today; especially in these economic times. The dot com bubble is long over. Hardware budgets are limited and few companies relish the idea of hiring teams of programming experts to maintain even a valuable IT asset such as their data warehouse. They’d rather buy an off-the-shelf tool designed from the ground up to do high-speed data analytics.

Like MapReduce, commercially available massively parallel processing databases specifically built for rapid, high volume data analytics will provide immense data scale and query fault tolerance. They also have a proven track record of customer deployments and deliver equal if not better performance on Big Data problems. Perhaps as importantly, today’s next-generation MPP analytic databases give businesses the flexibility to draw on a deep pool of IT labor skilled in established conventions such as SQL.

As mentioned above, unstructured data seems like a natural for MapReduce analysis. A rising tide of chatter is focused on the increasing problem – and importance – of unstructured data. There is more than a bit of truth to this. As the Internet of everything becomes more and more a reality, data is generated everywhere; but our experience to date is that businesses are most interested in data derived from the transactional systems they’ve wired their businesses on top of, where structure is a given.

Another difficulty faces companies even as MapReduce becomes more integrated into the overall enterprise data analysis strategy. MapReduce is a framework. As the hype and interest have grown, MapReduce solutions are being created by database vendors in entirely non-standard and incompatible ways. This will further limit the likelihood that it will become the centerpiece of an EDW. Business has demonstrated time and again that it prefers open standards and interoperability.

Finally, I believe a move toward a programmer-centric approach to data analysis is both inefficient and counter to all other prevailing trends of technology use in the enterprise. From the mobile workforce to the rise of social enterprise computing, the momentum is away from hierarchy. I believe this trend is the only way the problem of making Big Data actionable will be effectively addressed. In his classic book on the virtues of open source programming, The Cathedral and the Bazaar, Eric S. Raymond put forth the idea that open source was an effective way to address the complexity and density of information inherent in developing good software code. His proposition, “given enough eyeballs, all bugs are shallow,” could easily be restated for Big Data as, “given enough analysts, all trends are apparent.” The trick is – and really always has been – to get more people looking at the data. You don’t achieve that end by centering your data analytics efforts on a tool largely geared to the skills of technical wizards.

In summation, MapReduce-type solutions as they currently exist are most effective when utilized by programmer-led organizations focused on maximizing their growing IT assets. For most businesses seeking the most efficient way to quickly turn their most valuable data into revenue generating insight, MPP databases will likely continue to hold sway, even as MapReduce-based solutions find a supporting role.

Celebrating Pablo and Virtual Cubes

Virtual cubes seminar, Sep 13-14, NYC - putting an end to your OLAP cube nightmares

We're excited about our upcoming Virtual Cubes seminar in New York City on September 13-14 - register here. Why? Because our Pablo feature of WX2 is resonating well with organizations that are struggling to keep up with the demands of business users who are used to running and querying data from physical OLAP cubes. You'll already know that Pablo was launched back in July to respond to the question from many enterprises that have made a major commitment to OLAP-based services, but who want to eliminate the logistical issues of designing and populating cube data sources. And we all know just how many OLAP cubes you have to build and constantly re-populate. Imagine if you could benefit from in-memory and zero population virtual cube builds instead.

So if you're one of those sufferers out there that wants to benefit from virtual cubes, sign up to attend our free seminar in New York City. On September 13 we're in Midtown, on September 14 we'll be on Wall Street. Learn more at www.kognitio.com/stopdreaming.

It's time to stop dreaming about virtual cubes and experience them for real. Just think about that: no more physical cubes to create, administer, refresh or repopulate. Your OLAP cube headaches will be gone forever. See you at the seminar!

Exclusive clouds: the next evolution of private clouds

There’s no doubt cloud-based Data Warehousing as a Service (DaaS) lets you do large-scale data analytics on-demand, at low cost, and with little upfront capital investment. But despite the benefits, the two predominant cloud platform choices – public or private clouds – still don’t sit well with organizations like financial services that face tough privacy and regulatory compliance constraints.

Laws such as Sarbanes-Oxley and BASEL III make it difficult for organizations to take responsibility for who can access data, how they use it, and how it’s stored …when it’s in the cloud. The policies were originally written with the presumption that IT resources were on premises and under tight internal security procedures.

Public clouds, where servers, storage and other DaaS resources are shared by many, are obviously a non-starter for these kinds of organizations. But even private clouds such as Amazon’s Virtual Private Cloud Service simply fence off a section of the public cloud so that workloads can be moved between internal and external data centers in a more secure way. It’s difficult to survive a compliance audit when where your data resides and how it’s managed remains a mystery in the cloud.

That’s why we at Kognitio are big supporters of the “exclusive cloud” model, where the data warehouse still physically resides within the organization’s firewall, but functions as a cloud DaaS service from the organization’s perspective. It’s a completely hands-off solution in which the IT resources are installed, managed and protected by a service provider and served up as an on-demand, pay-per-use cloud service. As with a traditional cloud offering, organizations gain all the benefits of flexible self-servicing. There is no overhead of implementing a data warehouse on site, it’s highly scalable, and no IT involvement is required in managing the database or hardware on which it’s running. Yet the organization meets its data storage and security compliance requirements.

So while traditional public and private clouds can satisfy the needs of many companies, regulated companies have a higher level of burden to protect privacy and data from falling into the wrong hands. The risk to IT for regulatory compliance requires a new cloud strategy that delivers all the benefits of the cloud while keeping safe within the firewall.

Coming together with MicroStrategy to solve Big Data problems

We announced today that more and more and more organizations worldwide are deploying Kognitio WX2 as the underlying analytical database to their MicroStrategy front-end BI platform in order to access and query “Big Data” data volumes. And we’re truly excited about it; not only is WX2 fully optimized to show off MicroStrategy’s applications, but our joint customers are seamlessly integrating both technologies to run analytical queries against massive amounts of data and make informed business decisions within seconds. And they are doing this fast. Usually, it is unheard of that users deploy large-scale data warehousing and BI projects within a few weeks, but not so with the MicroStrategy-Kognitio solution. In fact, one joint customer in the gambling and gaming sector deployed both WX2 and MicroStrategy’s application in just ten weeks. Compare and contrast this with the 12-18 months that large-scale data warehousing and BI projects usually take and you can see the huge difference that this makes.

Our partnership with MicroStrategy is successful because MicroStrategy’s flexible reporting capabilities work seamlessly with our WX2 analytic database to help business people create and refine their own web- or mobile-based reports on query results without IT involvement. Now in its 7th generation, WX2 uses in-memory processing and unprecedented query speeds to obtain results in a fraction of the time and cost of competing products. Together, the technologies enable businesses to conduct complex analysis on ever increasing data volumes to solve time-sensitive problems that were previously unachievable.

And that’s why we’re excited to be at the forthcoming MicroStrategy World event in Monte Carlo, Monaco from July 11-14, 2011. If you are at the show, stop by and see us. We’d be delighted to tell you more about how Kognitio and MicroStrategy is the perfect marriage between data analytcs and BI.

Meanwhile, if you want to read more on the partnership between Kognitio and MicroStrategy, click here.

In-memory analytics beat the odds

Today’s business landscape is both dynamic and data rich. Technology advances present new threats and opportunities almost simultaneously. World events – from wild weather to unexpected political developments and shifting consumer sentiment – can disrupt even the best laid plans. When it comes to understanding what it all means for the bottom line and re-calculating your odds of success, mastering Big Data analytics is key, a truth that online gambling and gaming businesses have been quick to acknowledge.

Online gambling and gaming sites are more popular than ever. More than 3.2 million people gambled online last year according to Nielson Media; a 40% jump from the previous year. Online gambling growth is even outpacing social network sites like Facebook. And big betting events like the Kentucky Derby, X Factor and the 2012 Olympics are sure to sustain that healthy growth rate.

This bettors’ tsunami is a big data challenge for gaming sites. Keeping track of who signs up, what they bet on and the slew of other factors that impact a game or event are critical to calculating the correct odds. The slightest miscalculation can result in lost revenue or angry customers.

That’s why gambling site businesses have become some of the most advanced power users of data analytics. The ability to crunch the data and calculate the odds quickly and accurately allows them to respond instantly to ever-changing information -- from an injured race horse to changing weather to the betting popularity of athlete. Accurate, competitive odds keep their customers happy and revenue streams flowing.

The biggest challenges gambling sites face with traditional approaches to analyzing big data are a) the analytics systems take too long and too much money to deploy and b) running queries could often take days, even weeks. In an industry that thrives on real-time and predictive information, speed means everything.

These real-time businesses need solutions that let them continuously query data effortlessly, quickly and accurately as soon as the questions arise. In-memory analytical platforms can be deployed within days, creating an environment where they can start analyzing data within seconds. In-memory analytics enable ‘train-of-thought’ analysis in which betting data can be updated and queried in real-time, keeping the odds continuously updated.

Knowledge truly is power in the gambling industry. Without recognizing this, online gaming sites risk alienating their customers and losing revenue – a gamble they’re not willing to take in today’s economy.

The database ego problem - it's not the size, it's what you do

In a week where adjectives were flying around to describe a certain relationship between a President and a Prime Minister (is it "special" or now "essential"?), it would appear that in the world of data warehousing and analytics, a few adjectives are also being thrown around to describe the huge challenge that faces organizations as they try to make sense and derive competitive advantage from their ever-increasing corporate and customer data volumes.

Is it a case of "big" data? Or "large" data? "Massive" data or "extreme" data? Or is the adjective used to describe the issue at hand just plain irrelevant? After all, it's all relative and it's more than just a size issue. Hence the title of this blog; for one man's big data is another man's small data mart. Indeed, just how much is considered as "big"? And how do you quantify "massive"? You can't. Surely, the question is how you approach the whole issue at hand. How do you even begin to get value from such an amount of data when it is more than just a case of volume. There's the issue of complexity - just how many disparate data types do you have? Where are they located in your business, across multiple systems perhaps? Then comes the question of variety - what do you exactly want to get from your data? A marketing professional will want very different information from what the CFO demands. Then you have to think about velocity - how quickly do you need or want to get to all of your data, and how fast does your business need to get the insight in order to remain competitive?

Therefore, it's all much more than a case of size and therefore ego. Whether GBs, TBs or PBs, it's not the adjective that is important, it's what you need from your data and how you can perform the analytics on it that is much more essential.

Latecomers to the in-memory party

As a company focused on analytic database technology that has always run in-memory, it’s gratifying to see new arrivals to this market recognize that the future is in-memory and that the future is now. Whether it’s Dell or HP or some other standard platform – hosted, in-house, appliance, etc. – the larger message is that hardware trends have finally caught up with analytic aspirations. Abundant, inexpensive RAM harnessed to massively parallel processing capabilities means spinning disk speed is no longer the query gating factor it was in even the early part of the decade. Kognitio WX2 has been at the leading edge of this trend for years.

In fact, Kognitio WX2 has always been and always will be in-memory. To the latecomers, we say: "Welcome to the party!"

We're happy to be nominated, but...

Big speculation once again rippled through the Big Data vendor landscape after the recent acquisitions of Vertica (by HP) and AsterData (by Teradata). Those-in-the-know say it’s a foregone conclusion that further consolidation is just ahead because Giant Vendors X,Y and Z clearly need a Big Data play to counter these recent rival moves and gain a foothold in what is one of the growing major trend markets. Kognitio has even made the speculative short list of likely targets. Flattering, but what if the inevitable isn’t?

Often when these types of acquisitions are made the term “game changer” is tossed about, but it’s not typically the large, acquiring companies that change the game in technology. They’re usually just trying to keep abreast of a suddenly hot, rapidly changing market space; hoping to fabricate a suite of offerings that convinces businesses of a larger vision worth buying into. In truth, the game is more often changed by independent companies possessing the luxury of focus and agility. It’s why start-ups get bought in the first place.

It’s also why buying from “built-to-sell” start-ups is a bit of a risk. Beyond the lack of a track record and concerns over their funding viability, an acquisition typically means the end of the product and its assimilation into a larger vendor’s agenda – and pricing schedule.

For a company like Kognitio, these realities present a compelling case for independence. We’re not exactly a start-up. Formally named in 2005, our technology history traces back some 20 years. We have a proven track record of success, including working for more than a decade with global telco player BT, and our focus on data and analytics has kept us on the leading edge of innovation. We were ahead of the curve with in-memory analytics, data warehousing as a service and now, the elimination of physical OLAP cubes with Pablo.

We know that Big Data analysis is more than a passing trend – it’s a fundamental and growing business need. While for many vendors, grow and sell is the preferred (and well trodden) path to success, history shows that a company with innovative technology and good execution can become just as successful as a stand-alone venture. We believe we are ready to make history.

Kognitio tagged as 2011 "Vendor to Watch"

Information Management magazine recently announced the top 40 vendors that they are watching in 2011, and it's a testament to the recent customer wins and product developments at Kognitio that the good folks over at the NY-based magazine have tagged Kognitio as one of the technology houses to keep an eye on. Indeed, you can see the Kognitio entry here.

The addition of Kognitio to this year’s list was prompted in part by the recent unveiling of Pablo, making WX2 the industry’s first analytic database that creates “virtual” cubes at the data’s source without compromising performance. Moreover, the fact that Kognitio customers have more than 1 petabyte of data under active, licensed management and more than 1 trillion database rows are being analyzed using our WX2 in-memory analytic database, shows the market that Kognitio is being increasingly deployed as the analytical platform that performs.

For more information on Information Management's top 40 vendor list, click here.

The End of Traditional OLAP? New Approach Spells Death for Physical Cubes

Several new data-management approaches are challenging the long-standing process of delivering Business Intelligence solutions via OLAP cubes built atop Data Warehouses. While the warehouse will surely never go away, and cubes certainly expedite queries, the shortcomings in time, collaboration and synchronicity associated with the traditional model have become downright burdensome in many cases.

One new approach for avoiding such bottlenecks uses a combination of in-memory power and Massive Parallel Processing (MPP). When implemented properly, this solution solves many of the limitations tied to the old model, including latency, inaccuracy and scalability.

View this Briefing Room Webinar to learn from veteran Analyst Robin Bloor, who explains how and why the world of information management is changing, then offer insights on what you can do. Bloor was briefed by John Coppins of Kognitio, who showcased the company’s latest offering Pablo, which creates a virtual marshalling area for metadata and super-charged “cubes” -- thus circumventing many of the issues that companies encounter with cube maintenance and proliferation. Furthermore, Pablo embraces Excel as the front-end, thus catering to many non-technical business users.

Announcing Kognitio Pablo - putting an end to OLAP cube nightmares once and for all

If you are struggling to keep up with the demands of business users who are used to running and querying data from physical OLAP cubes, then you need worry no more. Kognitio is proud to be launching Pablo, an extension to its WX2 database platform. Intended for use by enterprises that have made a major commitment to OLAP-based services, Pablo dispenses with the logistical issues of designing and populating cube data sources. Instead, Pablo enables turbo-charged train-of-thought analytics on extreme data through the use of in-memory and zero population virtual cube builds.

And now, using mass market tools such as Microsoft Excel or other front-end BI applications, frontline users can access larger data volumes more quickly with 100% drill-down capabilities. Gone are the headaches of cube proliferation, multiple versions of the truth as well as data strewn throughout your business.

And because there are no more physical cubes to create, administer, refresh or repopulate, your cube headaches are gone forever. To find out more about Kognitio Pablo, go to www.kognitio.com/pablo

Kognitio positioned as Visionary player in Magic Quadrant report

We are extremely delighted that Kognitio has been positioned in the visionaries quadrant in Gartner's latest Magic Quadrant report on data warehouse database management systems (DBMS), published January 28th, 2011.

As our customers have come to expect, Kognitio is committed to offering a high quality analytic database platform that is resilient, robust and feature-rich. Our mature WX2 solution is just that, and with quality support on hand to ensure that our customers are successful in their efforts to get competitive advantage from their data, we are thrilled that the leading analyst firm has recognized our efforts as well as vision in the data warehousing market place. Indeed, Kognitio was the first to introduce many of the innovations that have driven the business intelligence and data analytics markets forward, including in‐memory database capabilities, Data Warehousing as a Service (DaaS) and the industry’s first data warehousing appliance.

To read more about Kognitio's position in the report, please go to our website and see our news release. To access the full report, please go to www.gartner.com

Kognitio customer TRA to speak at Gartner BI Summit 2011 in London

We're pleased to announce that Kognitio customer, TRA, is speaking at Gartner's Business Intelligence Summit 2011 in London, which takes place from January 31 - February 1, 2011, where Kognitio is a platinum sponsor of the event.

Mr. Mark Lieberman, CEO of media monitoring and market research agency TRA, will discuss how the organizaion has created new revenue streams in just weeks by running deep-dive analytics on large and complex data sets using Kognitio's WX2 in-memory analytic database.

During the presentation at the show, Mr. Lieberman will discuss how TRA has harnessed the power of next-generation data warehousing and analytical platform - Kognitio WX2 - to build its own product called Media TRAnalytics, and how this has helped it to slash internal costs, accelerate the creation of new revenue streams, and allow its customers to get more actionable information on TV viewing habits and consumer spending behavior much more quickly.

So if you are headed to the Gartner BI Summit, be sure to catch this exciting presentation. Mr. Lieberman will be speaking on Tuesday, February 1, 2011 at 11.30am GMT.

And be sure to stop by the Kognitio stand on the solution showcase showfloor where you can learn more about Kognitio's solutions, including a sneak preview of something exciting that is coming down the line.

Kognitio to present at MicroStrategy World 2011

Kognitio will present at MicroStrategy World 2011 on big data and deep-dive analytics next week in Las Vegas. If you are at the show, be sure to stop by session 2 on Tuesday, January 25 and learn how Kognitio customer, TRA, has created new revenue streams in just weeks by using Kognitio's WX2 in-memory analytic database to perform deep-dive analytics on large and complex media and advertising data.

During the presentation - entitled "TRA - how deep-dive analytics on big data helped a media monitoring and market research agency to create new revenue streams in just weeks" - you will learn how TRA has harnessed the power of next-generation data warehousing and analytical platforms (Kognitio WX2) to build its own product, Media TRAnalytics, and how this has helped the company to slash internal operating costs, accelerate the creation of new revenue streams, and allow its customers to get more actionable information on TV viewing habits and consumer spending trends much more quickly and efficiently.

The presentation takes place Tuesday, January 25th at 2.15pm PT (track 12, session 2). We look forward to seeing you there!

A fantastic start to 2011

Happy New Year to everyone - we hope you all had a great festive break! And what a fantastic way it is to start 2011 with the news that Kognitio has received substantial funding from CFP & Founders Investments, which will help Kognitio to continue its global expansion, as well as invest in new R&D and partnership efforts.

CFP & Founders Investments believes Kognitio is the industry's fastest and lowest TCO data warehousing solution and intends to support Kognitio with expertise, commercial contacts and management capacities over the next couple of years.

For more information on this great news, be sure to check out our news release here:
http://www.kognitio.com/kognitio-secures-funding-from-cfp-founders-investments

Happy Holidays from Kognitio!

Dear reader

From all of us at Kognitio, we would like to wish you all the very best this holiday season and for the New Year. We would also like to thank you for your continued support throughout 2010. It's been another great year for Kognitio and we're very grateful to all of you for our continued growth - new products, new awards, new customers and new partners.

As you know, we're committed to helping organizations derive more value and actionable insight out of their ever-increasing data volumes at a considerably lower cost. So if you're faced with the challenge of implementing or running analytic solutions that won't cost you a fortune, then come and talk to us.

Here's to an even better 2011!

Festive greetings and warm wishes from the entire Kognitio team

2010 highlights for Kognitio Product news:
:: WX2 Appliance range
:: Kognitio wins Vision award
:: Kognitio wins Innovative award

Featured customers:
:: Segmetrix' Match2Lists.com
:: American Access Casualty Company
:: bet365

New partners:
:: Hosted Solutions - DaaS hosting
:: Capgemini - cloud computing alliance
:: Panopticon - visual analysis tool
:: Quomation - DaaS pricing service
:: ITB - South Africa
:: Poslovna Inteligencija - Croatia
:: Umanis - France
:: GNOSYS Technology - Australia

New!
:: Catch Kognitio on YouTube at the KognitioWX2 channel
www.youtube.com/kognitiowx2

Announcing the Kognitio YouTube channel

We're excited about our new YouTube channel where you can learn more about Kognitio and our WX2 analytical database in the form of short videos around a certain theme. Have a look at the channel and already you can see an introduction to WX2 as well as our viewpoint on the eternal "which is better, row-based or columnar database?" question. Moreover, you'll see customer viewpoints as well as more details on how WX2 delivers the performance it does, thanks to its in-memory nature, its shared nothing architecture and the fact that it is a MPP (massively parallel processing) database.

Subscribe to the channel now and be the first to see new content when it appears.

The channel is here: http://www.youtube.com/kognitiowx2

Here is the introductory video to WX2:
http://www.youtube.com/watch?v=nHHx3LsBDVA

Here is the video that discusses the row vs columnar debate:
http://www.youtube.com/watch?v=apeURjTzodU

And here is the video that discusses how WX2 offers the performance it does:
http://www.youtube.com/watch?v=J-rwzmI1vLo

Looking for the diamonds in the data

When dealing in data analytics, organizations don’t care about individual numbers such as birth dates or social security numbers. They do care about customer habits; they want to know things like how old they are, their annual household income, what their buying habits are, and things like that.

It’s not because they want to do anything bad with that data; quite the contrary. The more companies know about people, the better they can market to them…the better they can anticipate their needs and wishes, and not spam them with stuff for which they have absolutely no use.

The responsible use of personal data benefits everyone. For instance, when customers shop online sites like Amazon.com, they’re already seeing this kind of behavior in use. After they click on an item, chances are the next window says something like, “People like you also liked,” and there’s a list of other products that are tailored to their demographic. This is not an invasion of their privacy; they’ve agreed to provide certain information to the vendor, and allowed them to use it to market more effectively to them.

And every time they go to the grocery store and swipe their loyalty card, they’re allowing the grocer to know exactly which products they’re buying, how often, and what their shopping patterns are. In return, they get discounts every week off their grocery bill.

Responsible marketers and vendors need to do a better job of conveying the benefits of sharing information. This is increasingly important as the U.S. government considers a “do not track” bill, which would allow consumers to easily say “no thanks” to online marketers who want to follow their click-trails.

Such a law makes perfect sense, but there is an inherent need to better communicate to consumers the advantages associated with making use of the information they share with retailers and vendors, making it abundantly clear that…no…they don’t care about them as individuals. But they do care about them as people.

Announcing a new line of WX2 Appliances, built on HP

We’ve already received significant positive feedback from folks throughout the industry about last week’s announcement that we offer a complete line of data warehouse appliances. InformationWeek, Network World and more have written articles. And at the TDWI World Conference in Orlando last week, a substantial number of folks came up to our booth wanting more information.

There’s a wonderful irony here, of course, and it’s not lost on anyone at Kognitio. We were building data warehouse appliances before they were ever known as “appliances.” And we’ve been building to-order appliances for companies around the world; it’s part of our commitment to give our customers the industry’s widest range of delivery options (software, appliances, DaaS).

What’s really piqued the interest of so many is our use of HP servers in combination with our WX2 in-memory analytic database. At the very time that so many of our traditional competitors have been swallowed up by larger hardware firms and are focusing their attention on increasingly proprietary configurations, we’re doing just the opposite. HP servers are industry-standard, but enable us to offer our customers an appliance that costs significantly less to buy, and operate. Plus, HP’s track record of reliability is second to none in our business, and that counts for a lot.

Especially so, as you consider that more companies than ever are realizing that the costs involved with advanced data analytics, or “Big Data,” are dropping significantly. They’re seeking ways that they can implement it at their firms, without having to deal with the traditional gating factors: too expensive, too slow to implement, too long to obtain actionable results.

The Kognitio/HP approach blows pasts all of those challenges. At the high end, our tests show that our appliances outperform our competitors, delivering results of up to five times more quickly, and at one-third the cost. Plus, they’re designed to scale more efficiently. Our approach is simple: if you only need an appliance capable of analyzing ten terabytes of data, why should you be forced to buy one that handles ten times that workload, under the guise of “preparing for the future?” We believe you should by what you need now and worry about the other stuff later, since our HP-hardware appliances scale seamlessly with no loss of performance.

We remain committed to allowing our customers to deploy WX2 in the way that’s most convenient for them. But it’s kind of fun to see all the buzz we’re generating about our new line of appliances. Especially when you consider how long we’ve been doing it.

Kognitio wins BeyeNETWORK's "Vision Award for Business Impact" second year in a row!

We're thrilled that our efforts in helping our clients achieve maximum business value from their data has been recognized by the folks at the BeyeNETWORK for the second time in a row.

This year, we entered the competition together with our client Segmetrix and highlighted how, using our DaaS-based model, Segmetrix has been able to build its Match2Lists.com application on top of WX2 quickly, and how it can now offer end-users the ability to upload various data lists via a web front-end and then match, cleanse, de-dupe and cleanse then. All at an exceedingly low cost and within very short timescales.

If you would like to read the full press release, click here. For more information on how WX2 via DaaS has proven to be the optimum solution for the Segmetrix Match2Lists.com application, click here.

Making your BI program world-class

We recently ran across an article from Timo Elliott, answering the question of “What Does a World-Class BI Program Look Like?” He writes that successful programs incorporate five separate elements:

• Focus on changing the business
• Focus on people
• Provide some simple data access for everyone
• Tell stories
• Stick with it

The end result, he writes, is that a world-class BI program “successfully changes the information culture of the organization.” We agree, but we’d go a little bit further.

• Successful BI implementations are game-changers. They don’t merely take what you’re already doing and make it a little better; they move you into a completely new realm of possibilities. In traditional programs, BI can be used to better understand customer thinking, help predict their future behavior and anticipate their needs. More recently, as the size of data sets have exploded (the so-called “Big Data” initiative), billions of customer transactions are being analyzed in a fraction of the time it used to require, providing near real-time understanding of market trends. Specialties such as sentiment analysis and the mining of social data are newcomers, but would not have been possible without the technology improvements of the last several years.

• WIIFM? Marketers everywhere will recognize this acronym; it means “What’s in it for me?” Simply put, a successful BI program must contain a WIIFM for everyone who interacts with it, from the C-suite all the way down to the customer service reps on the front lines. Good BI implementations no longer require oodles of time, money or personnel commitment: the emergence of BI SaaS programs, like our Data Warehousing as a Service, means that programs can be quickly implemented and begin producing tangible results at a fraction of the cost it used to take. The WIIFM for those who need the data is obvious; the WIIFM for your CFO is equally so.

• Fulfill the vision. The beauty of BI SaaS, as well as market-driven improvements such as analytical appliances on commodity hardware, is that companies can move quickly to test out the potential benefits of BI initiatives. Things like ROI and TCO have never been more important than they are in today’s economy; BI’s evolution has made it possible to imagine what your company could do with a greater level of insight and to actually implement it, rather than leaving the vision on the wish list indefinitely.

Above all else, we’d expand Timo’s thinking: well-strategized BI programs, properly implemented, change not only the “information culture of the organization.” They change the organization itself, as well as every person who comes into contact with it.

New product announcements are fine, but how are they helping businesses?

The idea for this blog posting comes not from what people are talking about; it is from what they aren’t discussing. Like any business day, today there are a number of news releases available about this or that new service or product. Each promises to deliver significant benefits at lower cost in less time…in short, what we’ve all come to expect from news releases of this type.

The thing that strikes us most, however, is the dearth of stories about customers who are actively using a product to make a difference in the way they do business. And yet prospects who are actively seeking to find a solution to their challenges are going to be looking for that kind of information.

So whenever we can, we make a habit of leading with stories about our customers, and how our WX2 analytical database has made the difference that allows them to be more competitive in the marketplace. For example, a company such as Segmetrix. Its founders had a great idea: what if we could, they thought, make it possible for marketers to take multiple mailing lists and clean them up, standardizing the lists in a mere fraction of the time it was taking data analysts to do it manually? And what if they delivered it as a cloud-based service, helping those marketers keep their costs to a minimum and allowing them to focus on the results they needed, and not the underlying technology?

Segmetrix knew what it wanted to do, but couldn’t find the company that would help it meet its vision…until it found Kognitio. Today, Segmetrix’s Match2Lists.com is a leader in its market, and the guys who run it will gladly tell you that Kognitio was an integral part of its success.

That’s the kind of information that people are seeking: while news releases about the latest and greatest are fine, people really want to know how products can make their lives easier, more successful and more profitable.

Incidentally, watch this space for further news on Match2Lists.com.

Is your glass half-full or half-empty?

A Corporate Executive Board survey finds that corporate IT budgets are going to grow by an average of more than three percent next year. It’s the first increase in three years.

Of course, if you’re a “the glass is half-empty” kind of person, it’s going to be very easy to disregard this news: you might add that they won’t be spending like they did in the past. In fact, they may never spend like they used to!

Quite true, but this is good news from our perspective. Here’s why: the survey found that much of the increase will be “spent on services that can provide analytics and other tools that help target customers,” according to the Wall Street Journal. But as they spend more on the services, they’ll be spending less on the hardware that’s needed to make the services work. Instead, they’ll be working with companies that can deliver those services through cloud computing.

Which means that services like Kognitio’s Data Warehousing as a Service (DaaS) offering are well positioned to deliver the kind of results that companies are seeking. They need to analyze greater amounts of data than ever (the so-called “Big Data” initiative), in less time than ever, and make the results available to more of their workers in a timely manner.

And, as the survey found, they simply don’t have unlimited amounts of money to spend to make it all happen, as may have been the case several years ago.

The lesson here is clear: businesses are seeking more efficient ways of doing business. And if you’re not one of them, your competitors are looking to gain on you…or surpass you. If, in fact, they haven’t already done so. It may be time to take a long, hard look at what you do as a company, and the way you do it…and to ask yourself if there are more effective and efficient ways of doing it. Data Warehousing as a Service is an incredibly effective way of enabling your firm to do the deep dive analytics required in today’s marketplace, but it’s only one of the options you should consider.

The result, of course, will be a company that fires on all cylinders, nimbly responding to changes in the market to help keep you at or near the front of the pack. And that’s worth than just half of a glass.

A rising tide lifts all ships

We’re sure you’ve seen the news about IBM buying Netezza. Not only is the news a good thing for the business intelligence industry, but for Kognitio as well.

If you agree with the old adage that “a rising tide lifts all ships,” then Netezza’s good fortune means good news for other BI vendors as well. As an industry leader, IBM is in position to strongly influence trends: the technologies that people can and should use to make their companies more effective. Its purchase of Netezza indicates that IBM believes business intelligence will continue to grow in strategic importance at more firms, and that there’s a significant market to be served.

We believe they’re right. Moreover, we believe that companies like Kognitio and Netezza have made it possible for more mid-tier companies than ever before to realize and take advantages of the benefits that BI has traditionally offered far larger firms.

At Kognitio, of course, we’ve pioneered concepts such as commodity hardware-based data warehousing appliances and BI delivered on a SaaS basis. Both concepts are accepted as the norm today; in fact, more than half of our total business is trending toward implementations based on a SaaS delivery model.

So, what do we expect as the result of IBM’s purchase? Well, nothing but good things. IBM has validated the market for companies that may have been sitting on the fence about adopting BI technology, or deploying it at an organization through an appliance. Moreover, we believe the pace of innovation will actually accelerate, as companies like Kognitio deliver new ideas to the market…so that we can stay ahead of the behemoths. (We’re already working on a new concept that we plan to deliver soon.)

Overall, we’re pleased with this week’s news. We believe the greater awareness that the purchase of Netezza has generated means greater understanding of what we and other BI vendors are telling the market. Which is good news for everyone.

Bringing data analytics to the world of football

There are a number of solid reasons to utilize data analytics. It can be used to better understand and predict your customers’ future behavior based on prior purchases; it can be used to prevent fraud by seeking trends and patterns that may indicate abnormal activity; it can do a deep dive on huge amounts of data to help your company develop a better pricing strategy.

Or it can be used to pick the best players for your fantasy football team.

Computerworld ran this article, about a product manager who’s a fantasy football fanatic. She applies the same type of analytical thinking to creating her team that she does in her work. That is, she takes the available data, runs it through an analytic application, and figures out which players to choose: which are most likely to gain her points based on touchdowns or field goals, and which quarterback is probably going to have the best game on any given Sunday.

In doing so, she’s doing far more than the other team “owners” in her league. They basically rely on their gut feelings to choose their rosters. In that respect, they’re not that far removed from a number of business executives; a 2008 survey from Accenture revealed that 40 percent of business executives made important business decisions without using analytics.

Obviously, we think that’s not a wise move on the part of those executives. The more you can make solid decisions with the right data in front of you, the better your chances are of making the right decision.

The product manager says the other member in her league are aware that she’s using analytic software to help her draft her roster; “not that they like it very much, because it gives me an edge,” she says. It helps her make better decisions, which helps…regardless of whether you’re a fantasy team owner, or the owner of a very real business.

And the analytic approach works. The woman says in the last five years she’s been crunching the numbers before choosing her fantasy football rosters, she’s won her league three times. Let’s see: that’s a 60 percent winning percentage; finishing first in a league where finishing second counts for nothing.

That gets her the results she wants for another year. In the business world, the effective use of data analytics can deliver far more.