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.