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

Thank you!Tony Johnson

Career Steptony.johnson@careerstep.com

#TC18

Nick MagnusonBig Squid

nmagnuson@bigsquid.com

Steven EreksonAlign BI

stevene@alignbi.com