Developing a successful Big Data strategy. Using Big Data to improve business outcomes

Transcription

1 Developing a successful Big Data strategy Using Big Data to improve business outcomes

2 Splunk Company Overview Copyright 2013 Splunk Inc. Company (NASDAQ: SPLK) Business Model / Products Customers (6000+) 2004 founded On-premise 60+ of the Fortune first software HQ San Francisco In the cloud SaaS Largest license: 300 Terabytes/day

3 Operational Intelligence from Big Data

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

5 Industry Leading Platform for Machine Data Any Machine Data Operational Intelligence Servers Online Services Security Web Services Networks GPS Location Packaged Applications Search and Investigation Proactive Monitoring Operational Visibility Real-time Business Insights Storage Desktops Messaging Custom Applications Online Shopping Cart Telecoms RFID Databases Energy Meters Web Clickstreams Call Detail Records Smartphones and Devices

6 Splunk Enterprise Real-time machine data Hunk Splunk analytics for Hadoop

7 Telcos using Splunk for big data Security incident investigation, troubleshooting and monitoring Improved customer experience, incidence response & problem resolution IT operations management and data center insight Business insights in IT, Engineering, Security, Business and Marketing Operational intelligence across machine data and log file information Reports and visualization of all IT data for compliance & security Real-time dashboards giving operational visibility & insight

8 Developing a successful big data strategy Andrew Dunn Chief Technology Officer Nick Hills Chief Systems Architect

9 About us Global platform for recording and analyzing communications Used by banks and enterprises for compliance, risk and performance improvement Scales seamlessly across data centers worldwide First global platform for mobile, landline and data capture First to achieve PCI-DSS Level 1 compliance on a global, carrier-grade, public cloud platform

10 How we use Big Data

11 Our Big Data drivers Be elastic and able to adapt Using real-time, big, machine data to understand normal usage patterns and anomalies Improve customer service Mobile device behavior, usage and health Value added information

12 The data we can collect Machine data Handset data Battery, signal, network type Log files & all data sources App server logs, AWS, proxy logs. Billing, CDR, telephony switch data Door entry logs Public data Social media feeds Weather data Market prices

13 What we do with it Operational intelligence Monitoring Proactive troubleshooting Trend analysis All of our data + public feeds (Twitter) Usage patterns of people & devices Correlating events and behaviour Sentiment analysis

14 Big Data is about velocity and value as much as volume The need to be real-time Be proactive rather than reactive There is great, untapped value in the data

15 How we help our customers Big Data challenges

16 Our customers problems Untapped value in voice Expensive to extract Fragmenting channels Locked in department silos Mobile, landline, VOIP, SMS, , IM, social Value = f{speed of response}

17 Solution: one global platform Phone Appllications (C2) Voice UK Carrier Connect (Vodafone) UK MVNO Text US Carrier Connect (AT&T) Payments (PCI) Numeric On Site PBX - Fixed Hosted PBX Image AP Carrier Connect Instant Messenger Secure, Location Based, Rules Governed Storage United States of America, South America, European Union, Asia Pacific, * local, on-site Video Event: X Social Skype FaceTime Trading Services News Feeds Data Storage Growth of acquired data as a result of launching new product sets. Realtime or batched, cross cutting search and analytics across media type, country, domain and solution = Actionable alerts & intelligence Time Real-time actionable intelligence

18 Recommendations Consider the value you can get from machine data Record and monitor all your machine data and customer interactions Even if its not apparent they have an immediate value Augment your own big data with public, social data Download and try Splunk for free on your data

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