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Interview: Sharmila Mulligan, ClearStory Data on Collaborative StoryBoards for Big Data


We discuss the founding story of ClearStory Data, progress since its launch, Collaborative StoryBoards, common pain points in business analytics and data harmonization.



Sharmila MulliganSharmila Shahani-Mulligan is CEO & Founder of ClearStory Data. Sharmila also serves on the Board of Hadapt, a big data company and on the Board of Lattice-Engines and is advisor to numerous software start-ups. Previously Sharmila served as Executive Vice President for Aster Data, where she led product strategy, all marketing functions, business development and inside sales.

Prior to Aster Data, Sharmila Mulligan was Chief Marketing Officer of the largest business unit (BTO) within HP Software responsible for marketing a $3+ billion software products portfolio spanning all major aspects of IT management. Before joining HP, Sharmila served as Executive Vice President of Marketing at Opsware Inc., a publicly traded company and leader in the Data Center Automation market. Mulligan has worked as Vice President at Totality and Netscape communication. She has also held managerial positions at General Magic, Microsoft and HP’s PC business (PSG).

She received her masters in management from the Kellogg Graduate School and her BA in business & economics and BS in computer science from Northwestern University.

Here is my interview with her:

Anmol Rajpurohit: Q1. How and when did you start thinking about launching ClearStory Data?

Sharmila Mulligan: I spent early days at Cloudera and then Aster Data, both Big Data platforms. What ClearStory_Datawas apparent is that customers were trying to move data from many diverse internal and external sources into new Big Data platforms to aggregate data in one place for holistic analysis. They would then try using a pre-existing BI tool to run analysis on masses of data. It simply didn’t work. Old BI tool architectures were never designed to work on large, diverse data volumes nor allow for fast business user exploration of insights.

So two things have changed over the last 7 years that warrants new analysis solutions: 1) data variety and volume has exploded, and 2) business users are in need of self-service exploration of insights to make business decisions faster.


AR: Q2. How has ClearStory Data evolved since its launch?

SM: We’ve always been focused on fast, automated Sparkblending and harmonization of diverse data and faster user exploration of insights. That has not changed and we continue to innovate in these areas. What’s evolved, however, is inside our data processing engine, we use Apache Spark for fast processing and ‘data harmonization’ and we’ve deepened our investments in Apache Spark resulting in massive performance leaps when processing diverse data formats.

AR: Q3. You recently launched "Interactive, Collaborative StoryBoards" for ClearStory Data at Strata + Hadoop World 2014, New York. What are the key features of these story boards? How are these story boards different from traditional dashboards?

SM: ClearStory interactive and collaborative StoryBoards deliver highly interactive, collaborative insights to business users with the ability for users to explore and collaborate in real-time on insights at a deep level. The distinction between traditional dashboards versus Storyboards is that Storyboards update continuously as data updates, users can collaborate in real-time, and each Storyboard allows for very deep data exploration.

StoryBoards
This is not doable with dashboards that are pre-determined and often pre-wired to present a certain insight, outcome or KPI. Storyboards take data storytelling to a highly interactive, live view of insights.

AR: Q4. What are the most common pain points that you hear from your clients? What are the major bottlenecks in extracting value from Big Data?

SM:
The challenge they have is with speeding analysis and getting meaningful insights when multiple data sources or very large volumes of data are involved. Companies are looking for a faster way to wrangle all these data sources into meaningful, intuitive insights that business users can consume.
Multiple_Data_Sources We solve this with our data harmonization capability that speeds access to relevant data sources, harmonizes and blends them without needing long data wrangling cycles, and delivering these insights via interactive StoryBoards. The business users can themselves interact with and explore to quickly answer key questions.

AR: Q5. What do you mean by Data Harmonization? What are the big challenges in integrating data from multiple sources and running Analytics on it?

SM: Data Harmonization is our underlying technology built on Apache Spark that has built-in intelligence to read data sources, infer what’s in the data and then automatically blend them to reach answers and insights faster – all without needing specialized IT skills. Anyone can now point the ClearStory system to sources of data, internal and external, intelligently select what sources they want to blend using the information provided by the system , click ‘harmonize’ and the system determines how to blend the sources and dimensions in each source and immediately displays a visual insight.

platform-harmonization
 
What used to take days or weeks, can now be done in hours. The visual insights themselves can be easily explored; and if they lead to new questions that require new data to be added to the analysis; new sources can be included and harmonized on the fly without needing the traditional data modeling steps – that have been slow, complex and tedious for users.

The second part of the interview.

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