Why Employees Should Learn to Code: Data Analysis & Data Science
Bloomberg is a data, tech and media company started 35 years ago to help make data discoverable. Suzanne Mulder, the facilitator, has been with Bloomberg for 17 years and is a data trainer. A new manager came in with a background in engineering in training.
1) Central L&D team
2) Major business units have a training team in them. Automation rapidly increased. Analysts with background in finance now need more technical skills. How does this fit?
What is big data? It’s impractical to manage with traditional software tools. What qualifies is constantly changing! Our learning story:
1) Curated resources
2) MOOC with study group
3) On-Demand Learning with transparency
4) On-Demand Learning with mentorship, projects and original content
5) Classroom training with focused time to learn
People want to learn and it’s time!
Hourofcode.org - organized time to all learn to code
MOOCS don’t provide transparency
Vendor with videos that are engaging were better
Time boxed learning on people’s time, but people needed more guidance.
Need to be clear on what people should do with their skills! BQvant - Python and Jupyter notebooks linked to the terminal-created a product for customers and the analysts had to complete projects to learn this tool.
Adding a layer of leadership to support the program
Becoming a lot more common that students coming out of college know at least one programming language. How are leaders supposed to train/manage if they don’t know how to code?
30 leaders going through a pilot with vendor. Two day workshop-data for leaders. 10 week data analytics and data science course in Princeton New Jersey and across the globe. Two full days per week plus homework.
Accelerated rate of change
Pilot to decide whether or not we want to roll this out to entire company
Tuition reimbursement changed to skills-based programs with certificates
People need dedicated time to focus
Q: word-of-mouth? As product gets more visibility people learn that they need to know Python.
Evolving job roles in data:
Data wrangler-acquires, collects, questions, cleans data.
Data analyst-examines data to find answers to specific business questions.
Data engineer-develops, constructs, tests and maintains architecture/data bases.
Data scientist-creates predictive models to answer open ended questions.
The secret mission statement: to save people’s jobs!
Q: predictors of success-to do what? What’s in it for me? We need to get beyond technical and talk about the actual skills people need.
Q: pushback from higher up management?We have a culture where we can try things and we just do it. Then we ask for forgiveness.