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IT Briefcase Exclusive Interview: Open Source BI Today with Nobby Akiha, SVP Marketing, Actuate Corporation

May 10, 2013 No Comments

In the below interview, Nobby Akiha from Actuate Corporation emphasizes the value of a true Open Source BI solution, and outlines ways in which visual data mining, social media and predictive analytics can improve complex business variables and increase overall ROI for businesses today.

  • Q. In your opinion, how are cloud computing, mobile, social media, and big data transforming the way people view business intelligence today?

A. Business Intelligence (BI), as a practice and a field, has not changed in principle. It’s still about using data to make better decisions and improve business operations in areas such as gaining better understanding of your customers to drive higher revenue. The area in which it has changed is in the process and the effectiveness of doing so. Before the advent of “Big Data,” the data we examined most often originated “inside” the business stored in databases; today it’s equally as often originating “outside” the business, on websites, social media and running commentary like we find in blogs. Big Data also throws into the mix additional repositories of information that reside inside corporations, which have rarely been considered sources of relevant business intelligence; sources such as print streams, machine logs, customer service records, etc. Hence we see the often cited “3 Vs of Big Data”: Volume, Variety and Velocity that is truly changing both BI and the world of business in general.

We used to say, “It’s the customer that counts,” and, “The customer is always right,” but those phrases were just marketing taglines for many companies. Today, if a business doesn’t operate with those beliefs at its core, it will soon be out of business. And that change is driven by the ubiquitous access to information about consumer and business products that individuals have at their fingertips, literally anytime they are awake, via the web and on mobile devices.

We’ve known for decades that there’s no more powerful recommendation than that of a friend. Suddenly, in the last five years, we have universes of “friends” that we don’t even know. People we’ve never met have the ability to tweet or post – for good or bad – about anyone’s product or service, and influence buying decisions of people and businesses they’ve never even heard of. Social media has created experts of average consumers; we’re all “reviewers” today. Business Intelligence can effectively use all of the available information to out-quick and out-smart the competition.

As far as cloud as an influence, that’s a delivery mechanism and a cost-of-business concern for most businesses. To consumers, cloud computing is transparent – they don’t see it., for instance, is just an on-line store to most shoppers, who see it in the same way they see the big department stores in physical shopping malls. These shoppers are not aware of the massive amounts of data being uploaded and downloaded to millions of devices, hubs, warehouses, vendors, and shippers, nor are they aware of Amazon’s business offerings, such as AWS. So the way Amazon’s cloud-based business is accomplished, with split-second efficiency due to cloud storage and virtually instantaneous access, is truly game-changing. Nonetheless, for businesses “cloud” is a logistical business decision that needs to be examined by each company individually – via their IT group – as a way to save in-house digital storage costs considered against accessibility and speed/security of data access.

So we see that the convergence of Big Data (including Social Media sources), instant access anytime anywhere via mobile devices, and cloud infrastructure, has already changed the game of BI – by providing virtually instant insight into customers of all types – for the better, at least from the industry’s point of view. How consumers whose habits are being made public feel about this new world of intelligent insight into their preferences and quirks is perhaps the subject of another conversation.

  • Q. What do you see as the ultimate value of leveraging data to gain better insight into the end user experience?

A. The ultimate value – the end game if you will – of Business Intelligence (BI) is the ability to predict outcomes such as how, why, where, and when which consumer will buy which “next” product, so that sales of products and services can grow exponentially. This is, of course, the purview of Predictive Analytics software – an emerging focus that is running right alongside Big Data. Being able to predict a customer’s next purchase, investment, upgrade, etc., will be the driver that creates competitive advantage for companies of all sorts, whether they’re in the B2C or B2B space.

For many months now we’ve seen the emphasis on “insights” as the goal of setting up Big Data systems. And of course insights are what come of any kind of data analysis, whether it’s performed on small data or Big Data. In fact there are now four categories of analysis being discussed in the field of BI: descriptive, diagnostic, predictive and prescriptive. Just now, the trending topic is predictive.

Almost all Big Data software vendors claim that their products can do “predictive” analytics. And these vendors exist in all three phases of Big Data management – “Organizing,” “Visualizing/Analyzing,” and “Operationalizing” Big Data. Predictive analytics spans the last two phases. And the complexity of performing predictive analytics tends to depend on which of these phases the vendor’s primary product addresses. For instance, Hadoop vendors (in the “organizing” category) say that predictive analytics can be done with Hadoop. The reality is that Hadoop requires working through the organization’s IT department to first make the investment and put in place the IT architecture for a Hadoop repository and programming with MapReduce. Vendors who play in the “visualizing/analyzing” category offer predictive capability at some level in their BI platforms, or they claim to. Very few vendors other than Actuate offer an end-user targeted predictive analytics solution that can be used immediately and effectively by the data-savvy business user without going to the IT department.

So, because the ultimate value of leveraging data to gain better insight into the end user experience is the ability to increase sales of products and services; and because such insight is critical to achieving that ultimate value, the key to this equation is making available efficient and intuitive predictive analytics solutions directly to the people who manage the business.

  • Q. How do you see the consumerization of IT affecting the evolution of open source BI?

A. The need for individual self-service and control – consumerization of IT – is not only affecting BI, it’s driving it. And open source as a trend has always offered increased self-service. Any BI that is not “consumerized” already today will not succeed.  Open source just keeps growing. Already in 2011, more developers coded for Android than for Apple iOS. And when you throw Big Data – not a trend but the new reality – into the mix, almost all Big Data applications being built today are either built on or are themselves open source, no matter what stage(s) of Big Data management the application is designed to address (see answer #2 above for the stages of Big Data management).

  • Q. What are the biggest data management challenges your clients are bringing to the table, and how is Actuate working to overcome these challenges?

A. We recently commissioned an independent research study among the Global 9000 – that is the 9000 global companies with revenues exceeding 1 billion USD. The results showed us that one of the biggest data management challenges, even before tackling Big Data for the corporation, is the immediate need to collect all of a business’ existing sources of information and make them simultaneously accessible. Without this ability to access both structured and unstructured data – including for instance, printed bank or hospital customer statements that exist in print archives – no truly accurate behavioral or descriptive analysis can be done, let alone predicting what health procedure a patient needs next, or predicting the next best investment option for a financial customer. Actuate addresses this challenge through ActuateOne for Customer Communications Management (CCM), developed by our Xenos™ Group. ActuateOne for CCM is used to access, design, integrate, process, store and deliver high volume customer communications including statements, policies, and bills for top-tier organizations in financial services, insurance and telecommunications.

Once these items are transformed into digital format, their data becomes accessible for analysis and can be rolled into BIRT Analytics™. As Actuate’s recently introduced predictive analytics solution, BIRT Analytics can process billions of rows of data faster than any other product on the market, for speed-of-thought visual discovery of patterns and anomalies that leads to insights in customer/patient behavior, which in turn allows creation of additional marketing offers to drive increased organizational effectiveness and bottom line profitability. (For more about BIRT Analytics, see answer to question #6.)

  • Q. Can you please tell us about how BIRT, an open source BI solution, has become the backbone of many enterprise-level BI deployments?

A. Actuate has always excelled at helping businesses for whom information is a key part of the value they provide their customers. And we succeeded doing that for years before the brilliant idea that became BIRT came to light. In 2004 our CEO, Pete Cittadini, after considering the trend toward open source programming, realized that open source development tools would be integral to the creation of solutions that manage data for insight.

It’s probably easiest to let the numbers speak for us here.  Due to that realization, Actuate co-founded BIRT (BI Reporting Tools) open source software as a top-level project within the Eclipse Foundation in 2004. Actuate engineers coded BIRT and delivered its first release in 2005. Today, more than 2.5 million developers are using BIRT to develop open source BI applications – developers working inside small-to-huge corporations; developers working in IT departments of other companies who build on BIRT as part of their internal solutions; and developers working out of their garages in Silicon Valley or Sweden, for instance, starting high-profile, highly funded BI projects and companies. Since 2005, more than 12 million downloads have been recorded from the Eclipse website, and BIRT is used by more than one third of their open source development community; making it the leader among Eclipse open source projects like the SOA platform, Orion and Gemini.

The reason BIRT has been so rapidly adopted and become a standard open source toolset in the world of BI is that first, when it was developed, there was a ready-made community of open source developers at the right technical level who were part of the Eclipse community and looking for a BI toolset. Second, BIRT was deliberately built to be the easiest answer to both simple and complex data presentation requirements.

  • Q. How does BIRT Analytics work to provide visual data mining, social media and predictive analytic capabilities to analyze, manage and improve complex business variables with minimal reliance on IT?

A. BIRT Analytics™ is part of ActuateOne® – the BIRT-based suite of commercial products for development and deployment of custom business analytics applications. BIRT Analytics is an end-user product that allows business analysts to uncover trends, visually mine for unknown correlations, or perform time-series extrapolation for forecasts on both traditional and big data assets such as social media, Internet data, and traditional corporate sources.
BIRT Analytics has been adopted in financial services, telecommunications, government, eCommerce, healthcare, utilities and gaming. The end-user software offers:

An in-memory columnar data storage server, with lightning fast indexing and retrieval, to allow data-savvy end users to analyze all their data, independently, without IT intervention

Automatic data loading and lightning fast calculations even with billions of rows of data loaded into the system

Connect-Transform & Load (CTL) features for acquiring and integrating Big Data sources, and integrating massive amounts of data from multiple sources

Access to structured data from traditional data warehouses, RDBMSs, SAP and transactional systems

Access to popular petabyte-size Big Data repositories, including Hadoop, Cassandra and MongoDB

Ability to access social and Internet sources including Twitter, Facebook, LinkedIn and

Intuitive visual data mining and predictive analytics techniques including Pareto and bubble charts; Venn diagrams; profiling, mapping, clustering, and forecasting data; association rules; predictive functions; and decision tree definition to extend the already extensive arsenal of ActuateOne and BIRT visualizations.

  • Q. What major trends do you foresee emerging within open source BI and data analytics over the next five years, and what solutions will Actuate provide to support this evolution?

A. Over the coming years – five years may be too far out to predict in such a fast-changing market – we see a couple of major trends emerging. First, we see continued and accelerated consolidation of vendors in the Big Data space. Today we see many players in the game and, as we mentioned earlier, most of the newer solutions are based on open source. But many of the solutions replicate each other, particularly in the Hadoop arena. These specialty vendors will need to differentiate themselves, and we see movement toward that already.

One way to think of this is there are effectively three stages of Big Data management [as we noted in our answer to question #2] – “Organizing” your data sources (Hadoop and other repositories play here); “Visualizing and Analyzing” that data (Actuate plays here and has recently strengthened our offering with the addition of BIRT Analytics per Question 6, above); and Operationalizing that data, which is the final step of taking the analysis and predictions and making changes throughout the business to increase bottom line profitability. Applications in this space have yet to emerge because this is so deeply dependent on how any particular company runs its business and its culture. But this final step also includes “externalizing” which means Customer Communication Management (CCM) and our ActuateOne for CCM solution addresses this phase perfectly [see response to question #4].

Second, we see the world of business moving closer to the “Market of One” which is a term encompassing the idea that understanding customers and patients on an individual level – enabled by the technologies we have been discussing here – will mean that companies no longer have to settle for marketing their products to “target markets” such as “teenagers” or “retired men.” They will be able to market to the individual – the teenage girl from L.A. who frequents Facebook on her Samsung Galaxy s4, buys science fiction iBooks and plays World of Warcraft while wearing Doc Martens, flannel shirts and ripped jeans – or the single, retired man with 15 grandchildren whom he sees at bi-yearly reunions at his ranch in Southern California, and whose hobby is fly fishing on trips to Alaska while wearing L.L. Bean waders and driving a green Jeep Wrangler Unlimited.

This means that the time-worn phrase, “knowledge is power,” takes on a whole new meaning. The companies who master this type of targeted predictive and prescriptive analytics, and do it in a non-intrusive way, with targeted rewards for customers who agree to be transparent, will become the leaders in our newly data-driven world.

We plan to continue being right out front in providing solutions that help our customers become those leaders.

Mr. N. Nobby Akiha is Senior Vice President of Marketing at Actuate Corporation, with a career spanning 25 years in technology marketing and product management. Prior to joining Actuate in 2000 as vice president of marketing, he held the roles of vice president of marketing and business development at Inference Corporation; senior consultant at Regis McKenna, Inc.; director of marketing communications for CASE vendor Interactive Development Environments (IDE); and group product manager at Oracle. Mr. Akiha started his career consulting to consumer packaged goods companies Management Decision Systems and Burke Marketing Research. He holds a Master of Science in Management degree from the Sloan School of Management at M.I.T., and a Bachelor of Science in Commerce from the University of British Columbia.


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