Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

The Rise of the Citizen Data Scientist

1,615 views

Published on

Gartner predicts that the role of the Citizen Data Scientist will grow 5X faster than its highly trained counterparts (the Data Scientist). Learn more about the rise of this emerging class.

Published in: Technology
  • Be the first to comment

The Rise of the Citizen Data Scientist

  1. 1. THE RISE OF THE CITIZEN DATA SCIENTIST
  2. 2. Gartner predicts that the role of the Citizen Data Scientist will grow 5X faster than its highly trained counterparts (the Data Scientist).  
  3. 3. WHY? Because self-service big data discovery platforms enable Citizen Data Scientists to now explore previously undetected big data patterns to derive fast insights and solve core business challenges.
  4. 4. Research Proves the Rise of the Citizen Data Scientist USING TELEMETRY DATA, PLATFORA IDENTIFIED: •  The core power users of Platfora •  The personas of these power users •  How their usage patterns map over to roles like that of the Citizen Data Scientist
  5. 5. STEP 1: Analyzed 40,000 Sessions of Clickstream Data About User Behavior User Clickstream Click . . . . . . . . . . . . . . . . . . . . . . . . (ui.VizboardVizObject.Viz.Click, Ui.VizboardToolbar.SidePanels.Builder.Tab, Ui.VizboardToolbar.NotReadOnly.Save.Button, . . .) 2015-05-13 14:04:192015-05-13 11:20:152015-05-11 15:33:20 CUSTOMER 1 CUSTOMER 2 40,000 Sessions
  6. 6. STEP 2: Clustered Clickstreams into Groups Based on Similarity OUTCOMES DisimarilityDISIMILARITY 40,000 Sessions Cluster Sessions 1 2 3 4 5 6 7 8 9 10 010203040
  7. 7. STEP 3: Looked at Main Activities within each Cluster 40,000 Sessions Cluster Sessions Create Datasource Create Dataset Create Computed Field-Data Ingest Create Reference Modify Dataset Modify Reference View Dataset Create Lens Modify Lens View Lens Create New Page Create Vizboard Create Vizualization Create Computed Field- Vizboard Modify Vizboard Undo Vizboard Share Vizboard CLICKFREQUENCY 0.000 0.005 0.010 0.015 0.020 Activity by Cluster
  8. 8. Create Dataset Modify Dataset Build Lens with modification on dataset if needed Check system page Create Lens and visualization Create dataset, Lens and visualization in one workflow FREQUENCY Use Segments in visualization Use Vizboards, with more Vizboards object and manipulations on fields Use Vizboards with more data export Use Vizboards with viewing and exploring 0.00 0.25 0.50 0.75 1.00 STEP 4: Grouped the Main Activities within each Cluster by User 40,000 Sessions Activity by Cluster Cluster Sessions Activity by Users
  9. 9. STEP 5: Clustered Usage Patterns Across the User Base to Identify Core Personas FULL STACK USER #1 FULL STACK USER #2 FULL STACK USER #3 FULL STACK USER #4 VIZBOARD USER Identify Personas 40,000 Sessions Activity by Users Activity by Cluster Cluster Sessions FREQUENCY 0.00 0.25 0.50 0.75 1.00 Create Dataset Modify Dataset Build Lens with modification on dataset if needed Check system page Create Lens and visualization Create dataset, Lens and visualization in one workflow Use Segments in visualization Use Vizboards, with more Vizboards object and manipulations on fields Use Vizboards with more data export Use Vizboards with viewing and exploring
  10. 10. What We Learned DATA Data Pipelines & Transformation Modeling & Structure Visual BIData Science Publish Data Feeds DATADATA Publish Dashboards 4 OUT OF 5 USERS ARE FULL STACK USERS
  11. 11. Traditional User vs. Full Stack CUSTOMER WITH MORE TRADITIONAL ROLE ALIGNMENTS CUSTOMER WITH MORE FULL-STACK USERS Vizboard-only Users Full-Stack Users Full stack users return insight 2.4x faster  
  12. 12. Who is This New User? CITIZEN DATA SCIENTISTFULL STACK USER = •  Line-of-business user with a passion for data •  Not a trained data scientist or developer •  Focused on business problems – e.g. customer behavior, risk/fraud, IoT devices, cyber threats •  Driven to pull together the right data, now •  Iterative workflow– one question leads to the next
  13. 13. Key Takeways Find and Nurture Citizen Data Scientists Expand Study to Include Data Science Activities Transitional Role OR Career Path? THE DISCUSSION CONTINUES…
  14. 14. You should know.

×