Interview Stephanie McReynolds Director Product Marketing, AsterData

Here is an interview with Stephanie McReynolds who works as as Director of Product Marketing with AsterData. I asked her a couple of questions about the new product releases from AsterData in analytics and MapReduce.

Ajay – How does the new Eclipse Plugin help people who are already working with huge datasets but are new to AsterData’s platform?

Stephanie- Aster Data Developer Express, our new SQL-MapReduce development plug-in for Eclipse, makes MapReduce applications easy to develop. With Aster Data Developer Express, developers can develop, test and deploy a complete SQL-MapReduce application in under an hour. This is a significant increase in productivity over the traditional analytic application development process for Big Data applications, which requires significant time coding applications in low-level code and testing applications on sample data.

Ajay – What are the various analytical functions that are introduced by you recently- list say the top 10.

Stephanie- At Aster Data, we have an intense focus on making the development process easier for SQL-MapReduce applications. Aster Developer Express is a part of this initiative, as is the release of pre-defined analytic functions. We recently launched both a suite of analytic modules and a partnership program dedicated to delivering pre-defined analytic functions for the Aster Data nCluster platform. Pre-defined analytic functions delivered by Aster Data’s engineering team are delivered as modules within the Aster Data Analytic Foundation offering and include analytics in the areas of pattern matching, clustering, statistics, and text analysis– just to name a few areas. Partners like Fuzzy Logix and Cobi Systems are extending this library by delivering industry-focused analytics like Monte Carlo Simulations for Financial Services and geospatial analytics for Public Sector– to give you a few examples.

Ajay – So okay I want to do a K Means Cluster on say a million rows (and say 200 columns) using the Aster method. How do I go about it using the new plug-in as well as your product.

Stephanie- The power of the Aster Data environment for analytic application development is in SQL-MapReduce. SQL is a powerful analytic query standard because it is a declarative language. MapReduce is a powerful programming framework because it can support high performance parallel processing of Big Data and extreme expressiveness, by supporting a wide variety of programming languages, including Java, C/C#/C++, .Net, Python, etc. Aster Data has taken the performance and expressiveness of MapReduce and combined it with the familiar declarativeness of SQL. This unique combination ensures that anyone who knows standard SQL can access advanced analytic functions programmed for Big Data analysis using MapReduce techniques.

kMeans is a good example of an analytic function that we pre-package for developers as part of the Aster Data Analytic Foundation. What does that mean? It means that the MapReduce portion of the development cycle has been completed for you. Each pre-packaged Aster Data function can be called using standard SQL, and executes the defined analytic in a fully parallelized manner in the Aster Data database using MapReduce techniques. The result? High performance analytics with the expressiveness of low-level languages accessed through declarative SQL.

Ajay – I see an an increasing focus on Analytics. Is this part of your product strategy and how do you see yourself competing with pure analytics vendors.

Stephanie – Aster Data is an infrastructure provider. Our core product is a massively parallel processing database called nCluster that performs at or beyond the capabilities of any other analytic database in the market today. We developed our analytics strategy as a response to demand from our customers who were looking beyond the price/performance wars being fought today and wanted support for richer analytics from their database provider. Aster Data analytics are delivered in nCluster to enable analytic applications that are not possible in more traditional database architectures.

Ajay – Name some recent case studies in Analytics of implementation of MR-SQL with Analytical functions

Stephanie – There are three new classes of applications that Aster Data Express and Aster Analytic Foundation support: iterative analytics, prediction and optimization, and ad hoc analysis.

Aster Data customers are uncovering critical business patterns in Big Data by performing hypothesis-driven, iterative analytics. They are exploring interactively massive volumes of data—terabytes to petabytes—in a top-down deductive manner. ComScore, an Aster Data customer that performs website experience analysis is a good example of an Aster Data customer performing this type of analysis.

Other Aster Data customers are building applications for prediction and optimization that discover trends, patterns, and outliers in data sets. Examples of these types of applications are propensity to churn in telecommunications, proactive product and service recommendations in retail, and pricing and retention strategies in financial services. Full Tilt Poker, who is using Aster Data for fraud prevention is a good example of a customer in this space.

The final class of application that I would like to highlight is ad hoc analysis. Examples of ad hoc analysis that can be performed includes social network analysis, advanced click stream analysis, graph analysis, cluster analysis and a wide variety of mathematical, trigonometry, and statistical functions. LinkedIn, whose analysts and data scientists have access to all of their customer data in Aster Data are a good example of a customer using the system in this manner.

While Aster Data customers are using nCluster in a number of other ways, these three new classes of applications are areas in which we are seeing particularly innovative application development.


Stephanie McReynolds is Director of Product Marketing at Aster Data, where she is an evangelist for Aster Data’s massively parallel data-analytics server product. Stephanie has over a decade of experience in product management and marketing for business intelligence, data warehouse, and complex event processing products at companies such as Oracle, Peoplesoft, and Business Objects. She holds both a master’s and undergraduate degree from Stanford University.

MapReduce Analytics Apps- AsterData's Developer Express Plugin

AsterData continues to wow with it’s efforts on bridging MapReduce and Analytics, with it’s new Developer Express plug-in for Eclipse. As any Eclipse user knows, that greatly improves ability to write code or develop ( similar to creating Android apps if you have tried to). I did my winter internship at AsterData last December last year in San Carlos, and its an amazing place with giga-level bright people.

Here are some details ( Note I plan to play a bit more on the plugin on my currently downUbuntu on this and let you know)

Aster Data Developer Express provides an integrated set of tools for development of SQL and MapReduce analytics for Aster Data nCluster, a massively parallel database with an integrated analytics engine.

The Aster Data Developer Express plug-in for Eclipse enables developers to easily create new analytic application projects with the help of an intuitive set of wizards, immediately test their applications on their desktop, and push down their applications into the nCluster database with a single click.

Using Developer Express, analysts can significantly reduce the complexity and time needed to create advanced analytic applications so that they can more rapidly deliver deeper and richer analytic insights from their data.

and from the Press Release

Now, any developer or analyst that is familiar with the Java programming language can complete a rich analytic application in under an hour using the simple yet powerful Aster Data Developer Express environment in Eclipse. Aster Data Developer Express delivers both rapid development and local testing of advanced analytic applications for any project, regardless of size.

The free, downloadable Aster Data Developer Express IDE now brings the power of SQL-MapReduce to any organization that is looking to build richer analytic applications that can leverage massive data volumes. Much of the MapReduce coding, including programming concepts like parallelization and distributed data analysis, is addressed by the IDE without the developer or analyst needing to have expertise in these areas. This simplification makes it much easier for developers to be successful quickly and eliminates the need for them to have any deep knowledge of the MapReduce parallel processing framework. Google first published MapReduce in 2004 for parallel processing of big data sets. Aster Data has coupled SQL with MapReduce and brought SQL-MapReduce to market, making it significantly easier for any organization to leverage the power of MapReduce. The Aster Developer Express IDE simplifies application development even further with an intuitive point-and-click development environment that speeds development of rich analytic applications. Applications can be validated locally on the desktop or ultimately within Aster Data nCluster, a massive parallel processing (MPP) database with a fully integrated analytics engine that is powered by MapReduce—known as a data-analytics server.

Rich analytic applications that can be easily built with Aster Data’s downloadable IDE include:

Iterative Analytics: Uncovering critical business patterns in your data requires hypothesis-driven, iterative analysis.  This class of applications is defined by the exploratory navigation of massive volumes of data in a top-down, deductive manner.  Aster Data’s IDE makes this easy to develop and to validate the algorithms and functions required to deliver these advanced analytic applications.

Prediction and Optimization: For this class of applications, the process is inductive. Rather than starting with a hypothesis, developers and analysts can easily build analytic applications that discover the trends, patterns, and outliers in data sets.  Examples include propensity to churn in telecommunications, proactive product and service recommendations in retail, and pricing and retention strategies in financial services.

Ad Hoc Analysis: Examples of ad hoc analysis that can be performed includes social network analysis, advanced click stream analysis, graph analysis, cluster analysis, and a wide variety of mathematical, trigonometry, and statistical functions.

“Aster Data’s IDE and SQL-MapReduce significantly eases development of advanced analytic applications on big data. We have now built over 350 analytic functions in SQL-MapReduce on Aster Data nCluster that are available for customers to purchase,” said Partha Sen, CEO and Founder of Fuzzy Logix. “Aster Data’s implementation of MapReduce with SQL-MapReduce goes beyond the capabilities of general analytic development APIs and provides us with the excellent control and flexibility needed to implement even the most complex analytic algorithms.”

Richer analytics on big data volumes is the new competitive frontier. Organizations have always generated reports to guide their decision-making. Although reports are important, they are historical sets of information generally arranged around predefined metrics and generated on a periodic basis.

Advanced analytics begins where reporting leaves off. Reporting often answers historical questions such as “what happened?” However, analytics addresses “why it happened” and, increasingly, “what will happen next?” To that end, solutions like Aster Data Developer Express ease the development of powerful ad hoc, predictive analytics and enables analysts to quickly and deeply explore terabytes to petabytes of data.
“We are in the midst of a new age in analytics. Organizations today can harness the power of big data regardless of scale or complexity”, said Don Watters, Chief Data Architect for MySpace. “Solutions like the Aster Data Developer Express visual development environment make it even easier by enabling us to automate aspects of development that currently take days, allowing us to build rich analytic applications significantly faster. Making Developer Express openly available for download opens the power of MapReduce to a broader audience, making big data analytics much faster and easier than ever before.”

“Our delivery of SQL coupled with MapReduce has clearly made it easier for customers to build highly advanced analytic applications that leverage the power of MapReduce. The visual IDE, Aster Data Developer Express, introduced earlier this year, made application development even easier and the great response we have had to it has driven us to make this open and freely available to any organization looking to build rich analytic applications,” said Tasso Argyros, Founder and CTO, Aster Data. “We are excited about today’s announcement as it allows companies of all sizes who need richer analytics to easily build powerful analytic applications and experience the power of MapReduce without having to learn any new skills.”

You can have a look here at

Business Analytics Analyst Relations /Ethics/White Papers

Curt Monash, whom I respect and have tried to interview (unsuccessfully) points out suitable ethical dilemmas and gray areas in Analyst Relations in Business Intelligence here at

If you dont know what Analyst Relations are, well it’s like credit rating agencies for BI software. Read Curt and his landscaping of the field here ( I am quoting a summary) at

Vendors typically pay for

  1. They want to connect with sales prospects.
  2. They want general endorsement from the analyst.
  3. They specifically want endorsement from the analyst for their marketing claims.
  4. They want the analyst to do a better job of explaining something than they think they could do themselves.
  5. They want to give the analyst some money to enhance the relationship,

Merv Adrian (I interviewed Merv here at has responded well here at

None of the sites I checked clearly identify the work as having been sponsored in any way I found obvious in my (admittefly) quick scan. So this is an issue, but it’s not confined to Oracle.

My 2 cents (not being so well paid 😉 are-

I think Curt was calling out Oracle (which didnt respond) and not Merv ( whose subsequent blog post does much to clarify).

As a comparative new /younger blogger in this field,
I applaud both Curt to try and bell the cat ( or point out what everyone in AR winks at) and for Merv for standing by him.

In the long run, it would strengthen analyst relations as a channel if they separate financial payment of content from bias. An example is credit rating agencies who forgot to do so in BFSI and see what happened.

Customers invest millions of dollars in BI systems trusting marketing collateral/white papers/webinars/tests etc. Perhaps it’s time for an industry association for analysts so that individual analysts don’t knuckle down under vendor pressure.

It is easier for someone of Curt, Merv’s stature to declare editing policy and disclosures before they write a white paper.It is much harder for everyone else who is not so well established.

White papers can take as much as 25,000$ to produce- and I know people who in Business Analytics (as opposed to Business Intelligence) slog on cents per hour cranking books on R, SAS , webinars, trainings but there are almost no white papers in BA. Are there any analytics independent analysts who are not biased by R or SAS or SPSS or etc etc. I am not sure but this looks like a good line to  pursue 😉 – provided ethical checks and balances are established.

Personally I know of many so called analytics communities go all out to please their sponsors so bias in writing does exist (you cant praise SAS on a R Blogging Forum or R USers Meet and you cant write on WPS at SAS )

– at the same time someone once told me- It is tough to make a living as a writer, and that choice between easy money and credible writing needs to be respected.

Most sponsored white papers I read are pure advertisements, directed at CEOs rather than the techie community at large.

Almost every BI vendor claims to have the fastest database with 5X speed- and benchmarking in technical terms could be something they could do too.

Just like Gadget sites benchmark products, you can not benchmark BI or even BA products as it is written not to do so  in many licensing terms.

Probably that is the reason Billions are spent in BI and the positive claims are doubtful ( except by the sellers). Similarly in Analytics, many vendors would have difficulty justifying their claims or prices if they are subjected to a side by side comparison. Unfortunately the resulting confusion results in shoddy technology coming stronger due to more aggressive marketing.

Interview Merv Adrian IT Market Strategy

An interview with renowned technology analyst Merv Adrian is as follows. Mr Adrian has spent three decades in IT industry and has also served as SVP at Forrester Research, and now is founder of IT Market Strategy. Merv talks on his views on technology and how he sees the next big tech trends coming.


Ajay- Describe your career in science and technology. What do you think is the best thing that science careers offer to people.

Merv- I wouldn’t characterize myself as having worked in science – even computer science implies a direction quite different from my own. I began as a statistician, and after getting the opportunity to learn some computer skills, spent a number of years coding a variety of decision support and data integration programs. I joined the software industry as a technical journal editor, and held a variety of marketing, strategy and analyst relations positions before beoming an industry analyst.

Ajay-  With your background in finance, how do you think the next generation of financial reporting systems should be built for early warning signals of crisis. Due to think predictive analytics can play a bigger role than just traditional reporting and metric aggregation.

Merv- We’re already seeing greater specialization in financial applications that provide context: an understanding of the industry the firm is in, and its special requirements for industry standards, compliance, etc. This added specific depth and breadth, combined with increasing sophistication in pre-built models for predictive analytics and access to hitherto unavailable volumes of historical data, will extend the reach of applications used by financial professionals. Guided analysis and advanced visualization will make more sophisticated tools available and understandable, promoting more awareness of impending problems and recommending courses of action.

Ajay- What tips would you like to give to aspiring analysts or science journalists and bloggers. What are the top 5 things do’s /don’ts that you refer to while writing a report or analysis.


* Never stop learning, and never assume you know enough. Be humble enough to acknowledge that the person you talk to may have something to teach you – and ask about anything you hear that you don’t understand.

* Remember your audience. If you don’t know who you’re writing for, how can you decide what matters to them?

* Explain why what you’re saying matters, and to whom. Don’t assume your readers know.

* Be clear about what is new or changed. If it’s business as usual, there should be a good reason to write about it – maybe change was expected but is slow in coming.

* Acknowledge your sources and collaborators. Be generous with credit.

Ajay- Recently some BI Analyst firms saw the departure of star analysts to found their own firm. How do you think tech companies can manage the retention of talented people especially those who become a bigger brand than they were originally supposed to.

Merv- I’m assuming you want the response to refer to analyst firms. “Bigger than they were originally supposed to” is not an accurate way to describe the sitution.

Analyst firms don’t put a ceiling on their employees’ brand building; quite the contrary. They train them, give them a platform, and sustain them as they do so. Nonetheless, the firm’s brand, not the individual analyst’s brand, is what matters to them.

In general, the big ones don’t care about retaining people. They believe they can easily replace them, and history shows that they recover well from such departures.

Ajay- What incentives apart from the usual financial ones can help build a culture of intrapreneurship in which employees help build startups within the parent firm.

Merv- You can’t leave finances out of it. The business model that has been shown to work for intrapreneurs is partnership, where the partners share significantly in successful practices they build and deliver.

In consulting firms, if you build a practice, you benefit from its success. Analyst firms are increasingly making consulting part of the analyst job description, but the big ones have not made any moves to institute a partner-style model. So to your point, those who build their own brand successfully are likely to leave.

They become entrepreneurs, not intrapreneurs.

Ajay- What are your views on the next 12 months in terms of technology and BI industry dynamics. What is your wishlist- the top three things that you wish happen in the field of technology.


* We’re entering a period of great ferment in data management as a set of upstarts has had early success with specialized analytic database platforms. As spending rebounds, most will see their momentum continue. Several have new funding, strong management teams, and early successes to build on.

* The rest of BI will see similar expansion. BI is a perennial growth market and it’s not about to slow down – predictive analytics, advanced visualization, more spohisticated and widespread use of text analytics, and the movement to SaaS models will play a role.

* True analytic applications, as described above in a financial context, will also continue their momentum. You’ll see them in other places, from manufacturing to retail, as micro-verticalization and the proliferation of templated best business practice models roll out form the largest players.

Those are both predictions and a wish list – they move us closer to delivering on the promise of having computing power help us improve business results. There are many more changes coming in packaging, licensing, the emergence of dramatically more powerful hardware platforms – but that’s business as usual. The aging server population will need replacement, and the rebound will be substantial, hastening the generational shift. And a skills shortage will re-accelerate the growth of offshoring. The next decade will be transformational in many ways.

Ajay- How does Merv Adrian balance his work and home life? How important is work life balance in this profession and do you think younger analysts sometimes dont pay attention to it.

Merv- As a manager, I always did my best to remind analysts working for me to leave time for the things that define us a humans – family, friends and faith. What we leave behind will be there, not in our reports, no matter how good they are. We all find ourselves consumed by our work, and social media exacerbates the situation unless we build in ways to be human too.

Youth will always be in a hurry, but the natural maturation process usually works out fine. Where I see balance begin to reassert itself is usually in the family – when your kids arrive, you must stop and remember to be there for them. You mustn’t delegate that one – nobody has ever looked back at their life and said “I wish I had spent less time with my kids.”

Thanks for asking, Ajay. My final thought is that all this guidance is aspirational; I struggle for balance every day. Sometimes I do pretty well at it,and often I fall short. I try to keep my values firmly in mind and strive to live up to them, as we all do.

Analyst and consultant Merv Adrian founded IT Market Strategy after three decades in the IT industry. During his tenure as Senior Vice President at Forrester Research, he was responsible for all of Forrester’s technology research, and covered the software industry. Earlier, as Vice President at Giga Information Group, Merv focused on facilitating collaborative research and covered data management and middleware. Prior to becoming an analyst, Merv was Senior Director, Strategic Marketing at Sybase, where he also held director positions in data warehouse marketing and analyst relations

For more on Merv’s views you can go here

Merv’s B-Eye Network channel at
Twitter: merv

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