Section4 Certificate Description:
“Credentialed Section4 Data & Analytics strategists understand the language, frameworks, and power of analytics across an organization. They are able to visualize the end-to-end process of running analytics including how to identify opportunities suited for analytics and the data to fuel an investigation. Data & Analytics strategists will be able to mobilize a team to execute an analysis, anticipate barriers to success, and turn data into a story that generates stakeholder buy-in.”
Earning Criteria
Completed the Section4 Data & Analytics Sprint project: Design an analytics model that unlocks insights on a business problem or opportunity and create a plan for implementation.
Completed all course material in the Section4 Data & Analytics Sprint, including lessons, case studies, and live classes.
Completed an analytics model for a company and articulated the need to investigate the business problem or opportunity through strategic recommendations.
Demonstrated Skills
o Analytics
o Critical Thinking
o Data
o Data Analysis
o Data & Analytics Strategy
o Data Leadership
o Storytelling with Data
o Strategic Thinking
COURSE OUTLINE
The Power & Process of Analytics
o Types of Analytics – Descriptive, Predictive & Prescriptive
o Steps Involved – Collect Raw Data, Run a Model, Quality Assurance & Deployment
o Traditional Analytics vs. Machine Learning
Determining what problems are suited for Analytics
o (U-DATA-I) “Put Data between U & I”
Untested, Defined, Acute, Testable, Actionable & Impactful
Determine UAI first before assessing the other criteria
o Analytics is an iterative process
o Resist the urge to run into the analytics and first spend time fully understanding the problem & involve others (stakeholders) in framing the problem.
Exploring and Evaluating Data
o Quantity does not mean Quality. Evaluate the quality of the data in terms of:
Size, Reliability, Uniqueness & Accessibility
Designing Models
o Once you have collected the data and framed the problem, the first step is creating a hypothesis to test. Understanding the business model is critical in this first step. [Insert Venn Diagram of a Business Model (Value Creation, Value Delivery, Value Capture)]
o In order to have high confidence in your model, strive to give it context by incorporating various types of data (eg. Binary, Numeric, Ordinal, Categorical), assigning weights to various independent variables and monitor over time.
Interpreting Results
o Is your hypothesis supported or refuted by the analysis?
o Determine your confidence in the results
o Explore correlation and causation (A/B testing)
Competing in Analytics as a Business (DELTA)
o Data driven companies relentlessly gather and leverage high-quality data (eg, the Boston Red Sox example, Airbnb, Amazon & Zillow)
o Enterprise-wide approach of setting an analytics strategy and roadmap, manage a unified data analysis platform & improve data literacy throughout the organization (eg Capital One and its “information based strategies)
o Leadership – company leaders appreciate the importance of data and analytics and tout it to the whole organization. (UPS example)
o Targets - Identify clear business priorities and a feasible roadmap. Targets are lofty but attainable goals.
o Analysts - Recruit and retain talented Analysts by providing challenging problems, support continuous learning, encourage analytical decision-making and offering competitive compensation.