Your SlideShare is downloading. ×
Piloting Big Data: Where To Start? - StampedeCon 2014
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

Piloting Big Data: Where To Start? - StampedeCon 2014

229

Published on

At StampedeCon 2014, John Akred (Silicon Valley Data Science) presented "Piloting Big Data: Where To Start." …

At StampedeCon 2014, John Akred (Silicon Valley Data Science) presented "Piloting Big Data: Where To Start."

You know you have data. You know there are problems it can solve. But how do you bridge the gaps in between? We’ll describe a road-tested strategy for methodically moving from business problem, through an understanding of data requirements and technical capabilities, through to creating a targeted roadmap for your pilot project.

Published in: Technology, Education
0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
229
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
0
Comments
0
Likes
1
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. © 2014 Silicon Valley Data Science LLC All Rights Reserved. www.svds.com @SVDataScience Piloting Big Data Where to Start? 29 May 2014 – StampedeCon – St. Louis John Akred (@BigDataAnalysis), www.svds.com @SVDataScience
  • 2. © 2014 Silicon Valley Data Science LLC All Rights Reserved. www.svds.com @SVDataScience 2 Solving  difficult  problems  with   technology,  data,  and  science   Cross-­‐func<onal  teams   Agile  delivery  methods   Business-­‐driven  technology   strategy  and  advisory  
  • 3. © 2014 Silicon Valley Data Science LLC All Rights Reserved. www.svds.com @SVDataScience 3 1 Why big data? 2 What is a pilot? 3 Choosing a use case 4 Defining success Doing a Big Data Pilot Fielding a team Delivering
  • 4. © 2014 Silicon Valley Data Science LLC All Rights Reserved. www.svds.com @SVDataScience http://svds.com/post/ successful-data-teams-are-agile-and-cross-functional 4
  • 5. © 2014 Silicon Valley Data Science LLC All Rights Reserved. www.svds.com @SVDataScience Why Big Data? 5 1. New Capabilities 2. Economic Scalability
  • 6. © 2014 Silicon Valley Data Science LLC All Rights Reserved. www.svds.com @SVDataScience 6 DATA PLATFORMS FOR NEW CAPABILITES
  • 7. © 2014 Silicon Valley Data Science LLC All Rights Reserved. www.svds.com @SVDataScience 7 THE DATA VALUE CHAIN Acquire Ingest Process Persist Integrate Analyze Expose
  • 8. © 2014 Silicon Valley Data Science LLC All Rights Reserved. www.svds.com @SVDataScience 8 DATA PLATFORMS FOR ECONOMIC SCALABILITY at NetApp
  • 9. © 2014 Silicon Valley Data Science LLC All Rights Reserved. www.svds.com @SVDataScience 9 UP OR OUT? The SaaS Edition Users Revenue scale-out cost good times bummer Different products and features put different demands on the data infrastructure •  Profitable •  Unprofitable Increasing cost per user from scale-up architectures causes a barrier to economic expansion of the product user base.
  • 10. © 2014 Silicon Valley Data Science LLC All Rights Reserved. www.svds.com @SVDataScience 10 UP OR OUT? in the enterprise Different use cases put different demands on the data infrastructure •  UC1 •  UC2 •  UC3 •  UC4 •  UCn Increasing cost per unit of capability from scale-up architectures causes rationing of resources. Only the most valuable use cases are pursued. Data Resource Usage Value scale-out cost UC 1 UC2 UC3 UC4 UCn
  • 11. © 2014 Silicon Valley Data Science LLC All Rights Reserved. www.svds.com @SVDataScience 11 StampedeCon 1 Why big data? 2 What is a pilot? 3 Choosing a use case 4 Defining success
  • 12. © 2014 Silicon Valley Data Science LLC All Rights Reserved. www.svds.com @SVDataScience 12 From idea to production Agile: Iterate to value, answering the most valuable questions as quickly as possible Plan Prototype Pilot Production þ þ þ þ þ
  • 13. © 2014 Silicon Valley Data Science LLC All Rights Reserved. www.svds.com @SVDataScience What is a Pilot? Plan and Initialize • Define architectural approach • Identify resources • Provision training • Choose use case • Define success • Populate initial backlog and sprint plans Prototype and Prove • Identify poorly understood functionality • Isolate and experiment • Determine solution approaches • Evaluate solution(s) • Correctness • Scale • Economics Pilot • Define end-to- end “steel thread” • Partition off pilot population • Build and integrate system components • Modify associated processes • Train pilot user team Production • Expand to entire user/ customer/ partner/ etc population • Industrialize monitoring capabilities • Re-engineer processes • Train user community 13
  • 14. © 2014 Silicon Valley Data Science LLC All Rights Reserved. www.svds.com @SVDataScience 14 1 Why big data? 2 What is a pilot? 3 Choosing a use case 4 Defining success StampedeCon
  • 15. © 2014 Silicon Valley Data Science LLC All Rights Reserved. www.svds.com @SVDataScience 15 STRATEGIC IMPERATIVES BUSINESS OBJECTIVES MAP OBJECTIVES TO TECHNICAL WORKLOADS RATIONALIZE WORKLOADS Strategic Workloads
  • 16. © 2014 Silicon Valley Data Science LLC All Rights Reserved. www.svds.com @SVDataScience 16 BUILDING A DATA PLATFORM External Systems Data Acquisition Internal Data Sources Data Management Security, Operations, Data Quality, Meta Data Management and Data Lineage Analytics Data Ingestion Data Repository External Data Sources Persistence Offline Processing Real Time Processing Batch Processing Data Services
  • 17. © 2014 Silicon Valley Data Science LLC All Rights Reserved. www.svds.com @SVDataScience 17 1 Why big data? 2 What is a pilot? 3 Choosing a use case 4 Defining success StampedeCon
  • 18. © 2014 Silicon Valley Data Science LLC All Rights Reserved. www.svds.com @SVDataScience •  Incremental revenue •  Time to market •  Economic functional implementation •  Cost avoidance •  Brand benefit •  Goodwill ✔ 18 Defining Success
  • 19. © 2014 Silicon Valley Data Science LLC All Rights Reserved. www.svds.com @SVDataScience thank you! 19 Yes, we’re hiring www.svds.com/join-us

×