A Checklist for Big Data Success. Steve Ackley Sandeep Kumar Gupta

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1 A Checklist for Big Data Success Steve Ackley Sandeep Kumar Gupta

2 Big Data Investment Is on the Rise 76% of companies surveyed are investing or will invest in Big Data

3 The Big Data Potential in Banking Growth of financial services data Electronic payments Online and mobile banking Tick-level market data Market and credit risk information Social media Customer interactions Uses cases in banking Customer 360 Personalized marketing Churn prevention Trading analytics Risk management Fraud detection

4 Big Data Requires New Technologies Large-scale processing Spark Hive M ap Reduce Pig Centralize data from multiple sources Store all data in source form Scalabl e Unstructured Data Low Cost

5 Big Data is complex. It gets more complicated as you scale.

6 Big Data-as-a-Service

7 About Altiscale Founded Headquartered in Palo Alto, CA. Led by experienced, renowned Hadoop team from Yahoo! 40,000 nodes Raymie Stata, CEO. Former Yahoo! CTO, well-known advocate of Apache Software Foundation 500 PB 1,000 users David Chaiken, CTO. Former Yahoo! Chief Architect $ billions at stake Built and managed by veterans of Big Data, SaaS, and enterprise software From Google, Netflix, LinkedIn, VMware, Oracle, and Yahoo! Financed by top-tier technology investors Recognized innovator in Big Data-as-a-Service

8 We Enable Our Customers Success Checklist for Big Data Success Applications - We identify and implement applications which deliver business value within a short period of time. Analytics Middleware We integrate a wide array of analytics capabilities on top of Hadoop that form the building blocks for applications. Hadoop - Success with Altiscale starts with a rock-solid implementation of Hadoop as the foundation. It just works.

9 We Enable Our Customers Success Checklist for Big Data Success Applications - We identify and implement applications which deliver business value within a short period of time. Analytics Middleware We integrate a wide array of analytics capabilities on top of Hadoop that form the building blocks for applications. Hadoop - Success with Altiscale starts with a rock-solid implementation of Hadoop as the foundation. It just works.

10 The Cloud Is Becoming the Preferred Big Data Option OnPremises Cloud Plus OnPremises Cloud Only 32 % 29 % 23 %

11 The Altiscale Data Cloud

12 Why Fully Managed Cloud Service? Fast time to value days not months Easier, faster scalability with elastic scaling Operations support done Lower TCO so your jobs get for fast investment payba

13 Focus on Your Business, Not Your Infrastructure By offering a managed service in the cloud, Altiscale allows organizations to focus on time to insight, rather than worrying about infrastructure management.

14 We Enable Our Customers Success Checklist for Big Data Success Applications - We identify and implement applications which deliver business value within a short period of time. Analytics Middleware We integrate a wide array of analytics capabilities on top of Hadoop that form the building blocks for applications. Hadoop - Success with Altiscale starts with a rock-solid implementation of Hadoop as the foundation. It just works.

15 Innovaccer Our Strategic Partner Innovaccer and Altiscale have partnered to develop industry targeted big data solutions. Company Innovaccer is a big data analytics firm that provides data-driven solutions to business challenges. These solutions are powered by Innovaccer's technology platform, Datashop, which provides a fast, cost-effective manner to collect and mash-up data, and develop data solutions to help companies accelerate innovation. We launched with a joint Harvard & Wharton project. Launched our revolutionary platform. Powering data driven innovation at leading organizations around the world. History Developed technology in conjunction with various research institutions. Select Clients Won various awards for the best big data product.

16 Datashop Our Big Data Platform Datashop lets you integrate structured and unstructured data streams to innovate faster. Busines s Analysts Data Scientist s + Applicatio n Engineers Our Platform Disparate Streams of Data Powered by Hadoop and Spark Data Driven Decisions 16

17 End-to-End Big Data Solutions Datashop is the ios equivalent for Big Data. Business Applications API Endpoints Data Management Data Security Analytics Environment Big Data Lake Integration Engine Standardization, Cleaning and Linking Public Data Private Data 17 Partner Data

18 Seamless Integration to Databases Datashop has connectors to two hundred data systems. Integration Engine Private Data Public Data Partner Data 18

19 Easy and Intuitive Data Management Run and share analytical insights with the click of a button. With Datashop s intuitive interface you can access all your distributed data assets without writing complex scripts. With an inbuilt analytics environment you can run and share analytical insights with the click of a button. 19

20 Customer Success Stories The true test of an organization is not how they succeed but how their customers succeed with their help.

21 Case Study: Systemic Risk Analytics Objectives Measure and monitor the systemic risk of a multitrillion dollar economy to help prevent economic meltdowns Develop and apply algorithms based on network analysis theory to produce risk measures and scores on both a macro and micro level Network Effects in a Banking System Results Integrated multiple datasets including highly sensitive inter-lending bank information along with streaming stock data, credit ratings data, and a host of other sources within an intuitive graphical user interface Produced new, open source algorithms that power the systemic risk monitoring area at the Reserve Bank of India (RBI) The RBI now has increased operational visibility on a near real-time basis into the fragility, criticality, and overall systemic risk of the domestic banking economy The solution and underlying analytics are now being piloted at the US Federal Reserve through a collaboration with the Massachusetts Institute of Technology (MIT)

22 Case Study: Portfolio Servicing A $2.5B hedge fund is developing their entire portfolio servicing solution using Datashop

23 Case Study: Communication analytics A leading investment management firm deploys Datashop to extract insights from internal communications ( , Bloomberg chat, Symphony) to improve organizational and communication effectiveness.

24 Case Study: Competitive Insights One of the most successful venture capital firms uses Datashop Echo to gain competitive insights from social media and job boards.

25 The 30-Day Challenge Deliver business value in 30 days Enable business to visualize insights Start immediately on Altiscale Data Cloud and Innovaccer Datashop Supported by expert data analysts, data scientists and Industry experts

26 Thank You!

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