Safe Harbor Statement

1. Introducing Hunk™Splunk Analytics for HadoopBrett SheppardDirector, Big Data Product Marketingdata@splunk.com

2. Safe Harbor Statement During the course of this presentation, we may make forward looking statements regarding future events or the expected performance of the company. We caution you that such statements reflect our current expectations and estimates based on factors currently known to us and that actual events or results could differ materially. For important factors that may cause actual results to differ from those contained in our forward-looking statements, please review our filings with the SEC.  The forward-looking statements made in this presentation are being made as of the time and date of its live presentation. If reviewed after its live presentation, this presentation may not contain current or accurate information.  We do not assume any obligation to update any forward looking statements we may make.  In addition, any information about our roadmap outlines our general product direction and is subject to change at any time without notice. It is for informational purposes only and shall not be incorporated into any contract or other commitment. Splunk undertakes no obligation either to develop the features or functionality described or to include any such feature or functionality in a future release.

3. The Accelerating Pace of Data Machinedatais the fastest growing, most complex, most valuable area of big data GPS, RFID, Hypervisor, Web Servers, Email, Messaging, Clickstreams, Mobile, Telephony, IVR, Databases, Sensors, Telematics, Storage, Servers, Security Devices, Desktops Volume | Velocity | Variety | Variability

4. Make machine data accessible, usable and valuable to everyone.

5. Splunk Company Overview Company (NASDAQ: SPLK) Business Model / Products Customers 6000+ of the Fortune 100 2004 60+ founded On-premise first software release 2006 In the cloud Largest license: 100 Terabytes/day SaaS HQ San Francisco

6. Delivers Value Across IT and the Business App Dev and App Mgmt. IT Operations Security and Compliance Digital Intelligence Business Analytics Industrial Data and Internet of Things Developer Platform (REST API, SDKs) Small Data. Big Data. Huge Data. 6

7. Getting Value from Data in Hadoop is Challenging Wide Range of Open Source Projects for Hadoop Analytics Mahout Pig H i v e Sqoop YARN DataFu Azkaban Hadoop (MapReduce & HDFS) Easy storage but hard analytics: difficult to explore, analyze, visualize Complex technology: many open source projects Hard-to-staff skills: must write MapReduce jobs or fixed schemas

8. What Does Gartner Say? My most advanced Hadoop clients are also getting disillusioned … The only consistent success, reported by my clients, is with Splunk. “ VISIBILITY “ Many Hadoop customers Peak of inflated expectations Svetlana Sicular, Gartner Research Director, January 22, 2013 trough of disillusionment TIME 8 Plateau of productivity Slope of enlightenment Technology Trigger

9. We Began to Address This Challenge Real-time Collection and Analysis Dashboards, Reports, Access Controls Splunk Hadoop Connect • Bi-directional data transfer Splunk App for Hadoop Ops > > > > > > • Troubleshootand monitor

10. Introducing Hunk™ Splunk Analytics for Hadoop New product from Splunk delivers interactive data exploration, analysis and visualizations for Hadoop

11. Integrated Analytics Platform for Hadoop Data Full-featured, Integrated Product • Analyze • Explore • Dashboards • Share • Visualize Insights for Everyone Works with What You Have Today Hadoop (MapReduce & HDFS)

12. Validation from Partners "The fact that Splunk is bringing ease-of-use to sophisticated Hadoop problems is welcome from every angle. The power of Hunk comes across in how easy it is to just plug it in, throw it in there, and suddenly you have all of your answers. I wish every product worked this nicely.” “I'm super excited about Hunk. Hunk is solving one of the top issues that our customers have – access to the skills and know-how to leverage the data inside of Hadoop. Splunk has a very beautiful UI that is very easy to learn. So it bridges that gap and makes it very easy to access the data inside of Hadoop." "Hunk will help Hortonworks customers explore, analyze and visualize data in Apache Hadoop, driving more intelligent decisions across the entire organization."

13. Explore, Analyze and Visualize Data On-the-fly Virtual Index Schema-on-the-fly Flexibility and Fast Time to Value • Enables seamless use of the Splunk technology stack on data wherever it rests • Handles MapReduce • Structure applied at search time • No brittle schema • Automatically find patterns and trends • Interactive search • Preview results while MapReduce jobs run • Drag-and-drop analytics

14. Derive Actionable Insights from Raw Data 1 2 Point Hunk at Hadoop Cluster Immediately start exploring, analyzing and visualizing raw data in Hadoop Explore Analyze Visualize Dashboards Share HadoopStorage

15. Challenges With Alternative Approaches “Do it yourself” Hadoop / Pig Hive or SQL on Hadoop Extract to in-memory store OPTION 1 OPTION 2 OPTION 3 Problems Problems Problems Need to know MapReduce Wait for slow jobs to finish No interactive exploration Pre-defined fixed schema Need knowledge of data Miss data that “doesn’t fit” Data too big to move Limited drill down to raw data Another data mart

16. Powerful Analytics Anyone Can Use – Now on Hadoop Preview results and interactively search across one or more Hadoop clusters Interactive Search Provides more meaningful representation of underlying raw machine data Data Model Enables non-technical users to build complex reports without learning the search language Pivot 16

17. Empowering Business and IT Stakeholders Data Model Interactive Search Development Environment Pivot Business Analyst Developer Enterprise Architect • Build scalable big data apps on top of data in Hadoop • Use the development languages and tools you know and like • Adapt your architecture for big data • Hadoop shared-service departments offer self-service analytics • Free data scientists for custom analytics, not be data butlers • Save time by just pointing at Hadoop • Avoid fixed-schemas and low-level tooling • Answer questions iteratively without waiting for MapReduce jobs to finish

18. Fast Deploymentand Configuration Just point at Hadoop Connect to one or multiple Hadoop clusters • Certified integration with all major Hadoop distributions • Choose 1st-gen MapReduce or YARN • Create Virtual Indexes across one or more clusters • From download to searching data in < 60 minutes YARN certified

19. Connect Hunk to HDFS and MapReduce Hadoop Cluster 1 Connect to Apache HDFS and MapReduce or your choice of Hadoop distribution

20. Hunk Scales With Your Hadoop Deployments Connect Hunk to multiple Hadoop clusters Hadoop Cluster 1 Hadoop Cluster 2 Hadoop Cluster 3

21. Search and Explore from One Place Rapidly interact with data Pause or stop MapReduce jobs Search interface • Powerful Search Processing Language (SPL™) • Ad-hoc exploratory analytics across massive datasets • Preview results • No fixed schemas • No requirement to “understand” data upfront Preview results Drill down to raw data

22. Powerful, Easy-to-use Analytics Pivot • Drag-and-drop interface enables anyone to analyze raw, unstructured data • Build complex queries and reports without learning search language • Click to visualize any chart type; reports dynamically update when fields change Time window All chart types available in the chart toolbox Select fields from data model Save report to share

23. Define Relationships in Big Data Data Model • Describes how underlying machine data is represented and accessed • Defines meaningful relationships in the data • Enables single authoritative view of underlying raw data Hierarchical object view of underlying data Add constraints to filter out events

24. Visualize and Share Data with Role-based Security Build and personalize • Rapidly build advanced graphs and charts on-the-fly • Combine charts, viewsand external data in dashboards and reports • View and edit on any desktop or mobile device • Drill down to raw data • Protect data with role-based access controls

25. Build Big Data Apps on Top of Hadoop Pick your favorite tools Extend and Integrate Hunk Build Big Data Apps • Use a standards-based web framework and REST API • Customize dashboards and UIs with Simple XML, JavaScript or Django • Choose among SDKs for Java, JavaScript, Python, Ruby, C# and PHP SDKs Data Models Simple XML Web Framework Search Extensibility JavaScript Ruby C# PHP Java JavaScript Python Django REST API Hadoop (MapReduce & HDFS)

26. Drive Value Across the Enterprise Unlock the value of big data in Hadoop to address business challenges Multi-Channel Retail Management Financial Risk Management Synthesize Data from all Customer Touch Points – 360° View

27. Multi-Channel Retailer Otto Group Sales operations can see the big picture and drill down to individual SKUs Corporate strategists can access market conditions for 400 stores in 20 countries Analysts can more quickly explore data and create visualizations for in-store inventory

28. Petabytes of seemingly “random numbers” in Hadoop More, higher-complexity risk calculations Analysis showed the level of core Tier 1 capital ratio that the bank needs to hold against its balance sheet given their current risk profile RISK MANAGEMENT AT MAJOR GLOBAL BANK

29. MORE COMPLETE CUSTOMER VIEWFOR FASHION RETAILER Analyze this massive, diverse data sets in Hadoop Obtain a near 360 degree view of customers Raw data in Hadoop: Apache web logs, ecommerce site activity, Akamai image hosting logs, Squid proxy logs

30. Demo

31. Hunk™: Splunk Analytics for Hadoop FAST TO DEPLOY AND DRIVE VALUE FULL-FEATUREDANALYTICS Simply point Hunk at your Hadoop cluster and start exploring data immediately Explore, analyze and visualize data in Hadoop from one integrated platform INTERACTIVE SEARCH RICH DEVELOPER ENVIRONMENT Interact with data, change perspectives and preview results as MapReduce jobs run Build big data apps on data in Hadoop using standard web languages and frameworks

32. Thank Youwww.splunk.com/hunk