conf2015_BusinessPracticePreso_092215_post
- 1. Copyright © 2015 Splunk Inc. Florian Huck Marketing Analyst, Splunk Data Practice 101: An Intro to Business Data Anne-Marie Chun Splunk Data Practice
- 2. Disclaimer 2 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 the 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. About Us 3 Anne-Marie ‘Punky’ Chun Management Consulting MBA @ Wharton Splunk! Florian ‘Hucky’ Huck 1.0: Counter Strike Source 2.0: Business education 3.0: SF…and Splunk!
- 4. Agenda 4 Intro to Business Data Data Practice 101 – From Requirements to Consumption Powerful Commands for Business Data You Can Take Home Today Main Takeaways Additional Resources
- 5. Copyright © 2015 Splunk Inc. Intro to Business Data
- 7. Business Data != IT Data 7 IT Data Business Data Universally similar, rare singularities Varies for each team and company Machine generated Human + Machine generated Few data owners Many data owners Mostly logs Leverages fixed CRM / historical data Technical, understands logs, data structures… Business-minded, not highly technical
- 8. Understand Your Audience 8 Is this data correct? Short Attention Span Not Technical Might Not Know Work Needed Needs Insights at Fingertips How is this relevant? What actions should I take? Make it simple What data can we use? Make it pretty! Project scope…mmh what?! Doesn’t Need Technical Details
- 9. Be a Superhero to Your Business Folks 9
- 10. Copyright © 2015 Splunk Inc. Data Practice 101
- 11. Data Practice 101: Process 11 Gather Requirements Collect & Cleanse Data Build & Develop Deliver & Consume
- 12. Data Practice 101: Gather Requirements 12 Identify the right stakeholders Keep everyone honest Ask the right questions Understand the business problem to solve
- 13. Data Practice 101: Gather Requirements 13 AVOID: Rushing without properly understanding goal
- 14. Data Practice 101: Collect & Cleanse 14 Collect everything, identify relevant data Investigate to ensure data quality Work with data owners Collect, understand & enhance/enrich the data you need Identify extra sources to enrich the data
- 15. Data Practice 101: Collect & Cleanse 15 AVOID: Assuming the data is correct…and exists!
- 16. Data Practice 101: Build & Develop 16 Optimize your search structure Don’t forget unique identifiers! Use definitions Manipulate the data to find answers to the questions
- 17. Data Practice 101: Build & Develop 17 AVOID: Going heads down without seeking guidance
- 18. Data Practice 101: Deliver & Consume 18 Tailor delivery to the audience Anticipate questions that will come up Keep it simple, straight to the point Deliver answers (and identify next questions)
- 19. Data Practice 101: Deliver & Consume 19 AVOID: Information overload
- 20. Copyright © 2015 Splunk Inc. Powerful Splunk Commands
- 21. Easily Visualize Your Data 21 | table * | fields
- 22. Enhance Your Data 22 | eval if, case, mv* | stats count, avg, values | dedup | rex
- 23. Enrich Your Data 23 | lookup | join
- 24. Main Takeaways 24 Ask the right the business question Investigate the data – Splunk is FLEXIBLE – Collect everything & figure out later – Splunk is AGILE – Ingest any data…no need of specific format Use the power of SPL to do the magic – SPL is POWERFUL – Refine/enhance the data as you wish!
- 25. .conf2015 – Next Steps 25 Search Party! .conf2015 sessions – Go or watch – “Unraveling Analytics and Data Science: An Expert Panel ” – Tom LaGatta, Hal Rottenberg – “Building Powerful Analytics with Ease” – Pierre Brunel – “Enhancing Dashboards with Javascript!”– Satoshi Kawasaki
- 26. Copyright © 2015 Splunk Inc. Resources
- 27. Additional Resources 27 Splunk Quick Reference Guide Eval Functions Statistical and Charting Functions SplunkLive! Presentation: Data Models 101 Splunk Education: Searching and Reporting
- 28. Additional Resources (cont.) 28 Blog Post: Still Using 3rd-party Web Analytics Providers? Build Your Own Using Splunk! Blog Post: Capturing Omniture (or Google Analytics, or Webtrends) Data into Splunk External Whitepaper: Data Governance: A Business Value-Driven Approach