welcome [tc18.tableau.com] · careerstep.com . who is career step? company objectives • allow...
TRANSCRIPT
Welcome
Extending Tableau with the Power of Machine Learning: From Data Analyst to Citizen Data Scientist
Tony JohnsonDirector of Business Intelligence
Career Step
#TC18
Steven EreksonSr. Consultant, DW Architect
Align BI
Nick MagnusonVP, Product & Engineering
Big Squid
Agenda Key Takeaways
Who is Career Step?
Building a Data Driven Culture
Expanding Our Footprint
Scaling Our Organization
Extending Value with Predictive
What’s Next
Questions
Key Takeaways
Key Takeaways
1. Accelerate Time to Value with Your Data
2. Build a Data Driven Culture
3. Elevate Yourself to a Citizen Data Scientist
4. Extend Machine Learning to Grow Your Business
Who is Career Step?
Who is Career Step?
Career Step is an online provider of career-focused education and professional training. The company has trained over 100,000 students for
new careers as well as more than 100,000 healthcare professionals through its various continuing education courses. Career Step is committed to helping students and practicing healthcare professionals alike gain the
skills they need to be successful in the workplace—improving lives, advancing careers and driving business results through education.
careerstep.com
Who is Career Step?
Company Objectives • Allow flexible self-paced learning online• Provide superior student support• Create professional education content • Provide relevant career focused training• Low cost
Our BeliefEducation is one of the best ways
to change your life
1. Accelerating Value
Why the Foundation is Important
Expanding Our Footprint
2. Building a Data DrivenCulture
Building a Data Driven Culture
Analytics Expansion
Expanding the Tableau FootprintPinpoint actionable lead and sales related data Get Past the Noise - Visualize Predicted Outputs
Kraken Integration Enabling our Analysts to use advanced analyticsLead Qualification and Scoring
3. Scaling Our Organization
Scaling Our Data Analysts
Scaling Our Data Analysts
Scaling Our Data Analysts
Maximize Your Investments
Tableau + Kraken
4. Extending Value
Why the Foundation is Important
Predictive Analytics
• Use Case | Lead Qualification• How can we better qualify our pipeline of leads
for enrollment and understand our marketing approach to impact the volume of enrolled opportunities
•Machine Learning Results & Application• Identified drivers most influential and
unique to each open opportunity
• Defined relationships between driversand their individual ability to predict lead conversion probability
Predicting which leads are likely to close and identifying the drivers of those leadswill allow us to prescribe marketing efforts and prioritized sales strategy
Operationalizing The Model
Operationalizing The Model
Operationalizing The Model
What’s Next?
What’s Next?Operationalize Driver Influence Discovery• Build supportive views to monitor and
track driver analysis
What’s Next?Operationalize Driver Influence Discovery• Build supportive views to monitor and
track driver analysis
Prescriptive Analytics • How do we Impact our Predicted Results?• Machine Learning Collaboration • Scenario Planning
What’s Next?Operationalize Driver Influence Discovery• Build supportive views to monitor and
track driver analysis
Prescriptive Analytics • How do we Impact our Predicted Results?• Machine Learning Collaboration • Scenario Planning
Analyze Results
Kraken Scenarios Marketing
MixMarketing Mix Predictions • Understanding the ideal makeup of our
marketing campaigns to drive better conversion
Key Takeaways
Key Takeaways
1. Accelerate Time to Value with Your Data
2. Build a Data Driven Culture
3. Elevate Yourself to a Citizen Data Scientist
4. Extend Machine Learning to Grow Your Business
Questions?
Please complete the session survey from the Session Details screen in your TC18 app