Masters Certificate in Analytics for Leaders

Whether you’re looking to implement a data analytics program from scratch, take your use of data to the next level, or simply increase your fluency in the domain, the Masters Certificate in Analytics Leadership is the program for you.

This 13-day program for non-data specialists, is delivered in seven modules over three months and has been designed to quickly round out your knowledge of all the technical, managerial and organizational dimensions required to successfully and sustainably generate insights from data and translate them into action. This cutting-edge data analytics content is structured in convenient standalone modules can be taken by managers from any sector or functional area.

What is Required to Implement Data Analytics?

While most organizations today collect data as a basis for decision making, seeing patterns in the exploding volumes being generated can quickly become overwhelming. Analyzing it properly to in order to make better business decisions requires some specialized skills and tools, especially for non-data specialists.

What Does Predictive Analytics Entail?

Leveraging data using the right analytics tools can “open a window into the future”. It works when organization leaders can recognize the patterns and then ask the right questions of the data. The result is meaningful insights that uncover hidden or unexpected opportunities.

Communication Skills Are Critical

Having useful data is essential. It then becomes necessary, using data visualization, to shape them into a format that effectively communicates results and recommendations to managers across the organization so they can take action.

Leadership Dimensions

For analytics to gain traction, organizational infrastructure, processes and support from management must also be developed and implemented. That involves being able to advocate for and manage change. Applying analytics-focused entrepreneurial and design thinking results in a culture that fully engages the workforce for maximum effectiveness.

How Technically Demanding is it?

The modules have been developed for non-data scientists and do not require any prior technical knowledge. Some topics make use of math but only for explanation or demonstration purposes. All participants require to benefit is an openness to learning.

Content

Introduction to Analytics

An exploration of the underlying principles, this module will familiarize you with the reasons why it’s possible to trust data to make better decisions compared to intuition or experience.

Data vs. Intuition + Data-Driven Decision Making

• Decision-making strategies based on data vs. intuition
• Use data skills to build effective intuitions and vice versa
• Use data-driven strategies for better decision making
• Drive up ROI with data driven approaches

Understanding Variation + Correlation vs. Causation

• Consistency of process through measuring variability
• Measures of variability that determine outcome fluctuations
• Distinguish correlation from causation for better insight
• Variables and relationships relevant to business problems

Analytics & Leadership

Learn, practice and perfect the softer leadership skills which have proven critical for successfully engaging with human factors when implementing analytics-based projects.

Leading with Analytics

• Pair your business expertise with data science’s capabilities
• Identify the best corporate analytical strategy for success
• Frame business problems for data and analytics answers
• Overcome communication barriers

Negotiating and Influencing Skills

• Influence people on the conversational or interpersonal level
• The art and science of negotiating
• Strategies for persuading consistently
• Attain win/win outcomes with conflict resolution

Business Insights with Data

“Moneyball” insights are real! Locate the Moneyball instances within your organization by asking the right data questions, and then successfully present insights using data visualization.

Finding “Moneyballs” with Analytics

• Explore Applied Moneyball Theory as a unique value multiplier
• Unlock thinking and skills for identifying high value moneyballs
• Create predictive measures and questions to ask of the data
• Convince decision makers to invest in Moneyball opportunities

Data Visualization with Tableau

• Ask the right questions to reveal patterns and trends
• Illustrate actionable insights with data visualizations
• Empower decision makers with management dashboards
• Apply design principles, visual theory and data storytelling

Managing Data

Learn the fundamentals of an analytics infrastructure: what’s required to store, access, manipulate and manage data from technical, regulatory, privacy and cybersecurity perspectives.

Data Governance & Privacy

• Modern macro and micro drivers for effective data governance
• Organizational alignment and cross-functional engagement
• Internal/external roles and responsibilities
• Effective data leadership within an organization’s value network

Overview of Databases and Big Data Tools

• Big data and data science for more informed business decisions
• Organizational growth through more effective data analytics
• How big data analytics can drive competitive advantage
• Cloud, mobility, security, social media and online business

Data Science in Action

Envision the practical predictive analytics applications most suited to your organization now, and explore the additional possibilities afforded by data science technologies.

Introduction to Predictive Analytics

• Explore the past to predict advantageous future outcomes
• Apply tools and methods to your business decisions
• Differing science and data needs across industries
• Understand and communicate knowledge gained

A Map of the Terrain and Technologies

• The difference between supervised and unsupervised learning
• Common and useful data science algorithms in practice today
• Technologies most useful in enabling workplace data science
• How AI algorithms enable powerful data-driven insights

Digital Transformation

This module provides participants with strategies and techniques to enable the digital transformation which analytics represents to gain and maintain traction in their organization.

Entrepreneurial Thinking for Tech Strategies

• Data & AI challenges prevalent in the enterprise today
• Compare disruptive start-up vs. enterprise tech strategies
• Methodologies to execute like a tech-enabled start-up
• Processes to maintain rigor, security and compliance

Design Thinking in the Age of Big Data

• Create organizational value through internal design thinking
• Maximize value with design solutions based on insights
• Frame internal challenges to deliver new benefits
• Apply design thinking through an analytics lens

Capstone Project Presentation

Participants will present in groups on a case which challenges them to think about artificial intelligence in the context of large enterprises and how to develop a scalable business to serve the AI needs of these firms.