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Building the Data Academy

Pluralsight LIVE

Attendees will gain a step-by-step blueprint for building a data analytics academy, making the case to management, to identifying candidates and topics, to measuring its effectiveness.

In September 2019, McKinsey called for the rise of the in-house “analytics academy” to up-skill employees’ data literacy and prepare organizations for the changes from artificial intelligence and automation.

In this session, I will share tips for designing effective data analytics training programs acquired from working with leading technology and development organizations.

Attendees will gain a step-by-step blueprint for building a data analytics academy, making the case to management, to identifying candidates and topics, to measuring its effectiveness.

In this session, I will share tips for designing effective data analytics training programs acquired from working with leading technology and development organizations.

Attendees will gain a step-by-step blueprint for building a data analytics academy, making the case to management, to identifying candidates and topics, to measuring its effectiveness.

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Data Analytics Data Literacy Employee Training Upskilling

What's inside

Syllabus

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Read about what's good

what should give you pause

and possible dealbreakers

Addresses growing demand from organizations for employees who are data analytics literate

In-house training helps organizations prepare for AI and automation changes

Provides tips for designing effective training programs

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Reviews summary

Strategic guide to in-house data training

This analysis is based on inferences derived solely from the course description, as no actual review data was provided. Therefore, the summary represents potential strengths and areas of focus rather than direct learner feedback. According to the course's design, it aims to provide a positive:step-by-step blueprint for establishing an in-house data analytics academy. It focuses on strategic aspects, including positive:making a case to management and identifying appropriate neutral:candidates and topics. Learners should expect positive:practical guidance on neutral:measuring effectiveness of training programs, drawing from the instructor's experience with leading organizations. The course addresses a positive:timely need for neutral:data literacy and up-skilling employees in the context of AI and automation, aligning with current industry calls for such initiatives.

Addresses a critical and timely organizational need.

"The course really highlights the critical need for data literacy and how to address it internally, citing relevant industry reports."

"It's aligned with current industry trends and the push for up-skilling employees in data, making it very relevant today."

"Understanding the McKinsey perspective made the arguments for our academy much stronger to present to leadership."

Offers actionable tips for real-world application.

"The tips for identifying the right candidates and topics were incredibly helpful for starting our internal program."

"I really appreciated the section on how to measure the effectiveness and ROI of a data academy."

"It provides practical strategies that I can immediately apply in my organization to kickstart our data up-skilling."

Provides a clear, actionable framework for academy building.

"This course laid out a clear step-by-step blueprint for building an analytics academy in our organization."

"I found the guidance on making a strong business case to management extremely valuable and actionable."

"It's a fantastic guide for anyone looking to structure effective in-house data training initiatives."

Best for those with prior L&D or strategic experience.

"Some sections felt a bit abstract; you definitely need to have an understanding of corporate dynamics to fully grasp them."

"As someone new to organizational learning and development, I found myself needing to do extra research on change management."

"This course is ideal for senior managers or L&D professionals, perhaps less so for junior staff seeking tactical training."

Primarily strategic, may lack deep technical curriculum details.

"While great for strategy, I wished it delved more into the actual curriculum design or specific data tools to include."

"It's more about the 'why' and 'how to set up' the academy, rather than the 'what to teach' in great detail."

"I was hoping for more concrete examples of data training content, not just the framework for building the academy structure itself."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Building the Data Academy with these activities:

Read 'Data Science for Business'

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Gain valuable insights into how data science can be applied to solve business problems.

View Data Science for Business: What You Need to... on Amazon

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Read the book and take notes on key concepts
Identify real-world examples of how data science is used in different industries

Review Intermediate SQL

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Warm up your SQL skills by reviewing the basics of Intermediate SQL.

Browse courses on SQL

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Revisit SELECT statements, joins, and subqueries.
Practice writing queries to aggregate and manipulate data using GROUP BY, HAVING, and window functions.
Review how to use indexes and optimize query performance.

Organize and review course materials

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Reinforce your understanding of the course material by organizing and reviewing your notes, assignments, and quizzes.

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Gather all of your course materials
Organize your materials into a logical structure
Review your materials regularly

Six other activities

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Show all nine activities

Complete coding exercises from Pluralsight

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Practice and apply the concepts learned in the course by completing coding exercises provided on Pluralsight.

Browse courses on Coding Exercises

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Identify the coding exercise that aligns with the lesson topic.
Attempt to solve the exercise on your own.
Review the provided solution and compare your approach.

Complete Leetcode-style coding problems related to data structures and algorithms

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Solidify your understanding of data structures and algorithms by solving coding problems.

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Start with easier problems and gradually increase the difficulty.
Focus on understanding the problem statement and coming up with an efficient solution.
Implement your solution in a coding language of your choice and test it thoroughly.
Review your solution and identify areas for improvement.

Identify and connect with experienced professionals in the field

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Expand your network and gain guidance from those already working in the data analytics industry.

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Attend industry events and conferences
Reach out to your alumni network and professional organizations
Request informational interviews with individuals who work in roles you are interested in

Attend Coursera's 'Introduction to Data Analysis with R'

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Gain a comprehensive understanding of data analysis techniques by completing this Coursera course.

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Enroll in the course and complete the video lectures
Follow along with the hands-on exercises and assignments
Participate in the discussion forums to interact with peers and ask questions

Build a data visualization dashboard using Tableau or Power BI

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Develop your data visualization skills by creating a dashboard that communicates insights from a dataset.

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Choose a dataset that you are interested in
Identify the key insights that you want to communicate with your dashboard
Select appropriate charts and graphs to represent the data
Build and iterate on your dashboard until you are satisfied with the results

Participate in a Kaggle competition related to data analytics

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Challenge yourself and apply your skills by participating in a data analytics competition.

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Identify a Kaggle competition that aligns with your interests
Form a team or work individually on the competition
Develop and implement a data analytics solution
Submit your solution and track your progress on the leaderboard

Career center

Learners who complete Building the Data Academy will develop knowledge and skills that may be useful to these careers:

Data Science Instructor

Data Science Instructors teach data science concepts and techniques. They work with students to develop data science skills and knowledge. This course may be useful for Data Science Instructors as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.

See salaries and explore the career path for Data Science Instructor

Data Scientist

Data Scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course may be useful for Data Scientists as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.

See salaries and explore the career path for Data Scientist

Data Analyst

Data Analysts collect, clean, and analyze data to identify trends and patterns. They use their findings to make recommendations and inform decision-making. This course may be useful for Data Analysts as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.

See salaries and explore the career path for Data Analyst

Business Intelligence Analyst

Business Intelligence Analysts use data to identify trends and opportunities. They work with business stakeholders to develop and implement data-driven strategies. This course may be useful for Business Intelligence Analysts as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.

See salaries and explore the career path for Business Intelligence Analyst

Data Architect

Data Architects design and build data management systems. They work with business stakeholders to identify data needs and develop data management strategies. This course may be useful for Data Architects as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.

See salaries and explore the career path for Data Architect

Data Engineer

Data Engineers build and maintain data pipelines. They work with data scientists and data analysts to ensure that data is available and accessible for analysis. This course may be useful for Data Engineers as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.

See salaries and explore the career path for Data Engineer

Machine Learning Engineer

Machine Learning Engineers build and deploy machine learning models. They work with data scientists to identify and solve machine learning problems. This course may be useful for Machine Learning Engineers as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.

See salaries and explore the career path for Machine Learning Engineer

Data Analytics Manager

Data Analytics Managers plan and execute data analytics initiatives within an organization. They work with business stakeholders to identify data needs, develop data analytics strategies, and implement data analytics solutions. This course may be useful for Data Analytics Managers as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.

See salaries and explore the career path for Data Analytics Manager

Data Privacy Analyst

Data Privacy Analysts assess and mitigate data privacy risks. They work with business stakeholders and IT staff to ensure that data is collected, used, and stored in compliance with privacy regulations. This course may be useful for Data Privacy Analysts as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.

See salaries and explore the career path for Data Privacy Analyst

Data Security Analyst

Data Security Analysts protect data from unauthorized access, use, disclosure, disruption, modification, or destruction. They work with business stakeholders and IT staff to implement data security measures. This course may be useful for Data Security Analysts as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.

See salaries and explore the career path for Data Security Analyst

Project Manager

Project Managers plan and execute projects. They work with stakeholders to define project scope, develop project plans, and track project progress. This course may be useful for Project Managers as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.

See salaries and explore the career path for Project Manager

Program Manager

Program Managers oversee multiple projects. They work with stakeholders to define program goals, develop program plans, and track program progress. This course may be useful for Program Managers as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.

See salaries and explore the career path for Program Manager

Consultant

Consultants provide advice and guidance to organizations. They work with clients to identify problems, develop solutions, and implement changes. This course may be useful for Consultants as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.

See salaries and explore the career path for Consultant

Data Evangelist

Data Evangelists promote the use of data within an organization. They work with stakeholders to identify data opportunities, develop data strategies, and implement data-driven solutions. This course may be useful for Data Evangelists as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.

See salaries and explore the career path for Data Evangelist

Data Governance Specialist

Data Governance Specialists develop and implement data governance policies and procedures. They work with business stakeholders and IT staff to ensure that data is used ethically and responsibly. This course may be useful for Data Governance Specialists as it provides a step-by-step blueprint for building a data analytics academy, including making the case to management, identifying candidates and topics, and measuring its effectiveness.

See salaries and explore the career path for Data Governance Specialist

Reading list

We've selected 16 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Building the Data Academy.

Deep Learning

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Comprehensive guide to deep learning, one of the most popular and powerful machine learning techniques. It covers the basics of deep learning, as well as some of the most advanced techniques used in the field.

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Building the Data Academy

What's inside

Syllabus

Traffic lights

Save this course

Reviews summary

Strategic guide to in-house data training

Activities

Career center

Reading list

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