Fundamentals of Data Product Management and Data Strategy
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Welcome to the “Fundamentals of Data Product Management and Strategy,” an essential course tailored for those who aspire to tap into the immense power of data for strategic advantage. If you’re considering a career in data product management or if you’re in search of a holistic understanding of how data can steer your business objectives, this course is your perfect companion.
In the world that is increasingly centred around data, its value cannot be overstated. Data products, in particular, have become vital tools for organisations, harnessing raw data and transforming it into meaningful insights that guide decision-making and strategic planning. The advent of Machine Learning and Artificial Intelligence products has only further accentuated this trend, promising unprecedented opportunities for those ready to seize them.
However, there’s a notable void in the learning marketplace – while many courses focus on data-driven product management, few truly address data product management. Our course intends to bridge this gap, providing an in-depth exploration of the crucial elements of data product management without overwhelming you with excessive technical details.
We offer an immersive learning experience into the world of data strategy, a pivotal aspect often overlooked in conventional courses. Understanding how to strategise and operationalise data can significantly boost your organisation’s business success, making it an indispensable part of your learning journey.
But our course doesn’t stop at that. It delves deeper, exploring the complete lifecycle of data products – from identification and design to development, testing, and deployment. We also equip you with the vital skills you’ll need as a data product manager, including mastering roadmaps, managing expectations, collaboration tactics with internal and external teams, and leveraging agile methodologies.
In the “Fundamentals of Data Product Management and Strategy,” we aim to demystify the complexities of data product management and present it as a strategic differentiator in today’s data-centric world. Join us on this enlightening journey today and step confidently into the future of data.
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Data Fundamentals Section Intro -
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Understanding Data Types and Formats
Overview on the different types , formats and sources of data
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Understanding KPIs
What is a KPI and how do we create a holistic KPI framework?
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Experimentation and testing
What do we mean by experimentation and hypothesis testing? What is AB test and what a multivariate test?
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Data Informed versus Data Driven Approaches
Do we blindly trust only data or do we add some intuition from experience as well in the mix? What is the difference of the 2 approaches
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Section Conclusion
Recap what we have learnt
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Data Fundamentals QuizTest your knowledge! This Quiz is a great opportunity to revisit what you have learnt and ensure you are ready to continue the journey!
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Section Intro
Section Introduction and outline
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Data as a Product
What is the data as a product approach, how it was developed and how it is adding value
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Data Platform Products
What is a data platform product and why is it important?
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Data Products
The star of the course! Data products , their value, types and characteristics
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Analytical Data Products
The most common and strategic type of data products; what is an analytical data product , why is it important and what are its key features
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Operational Data Products
Another type of data products; the operational ones. Dive deeper on what they do and what value they add.
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ML / AI Products
The reason many of you are here! What are AI and ML products and what are their key features?
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Section Conclusion
Recap on what we have learnt.
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Data Product Types Quiz
Test what you have learnt and solidify your knowledge before continuing your journey.
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Section Intro
Section intro and outline
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Aligning data strategy with business objectives
The key on crafting an effective data strategy is to first understand the broader strategy and objectives of the organisation. Here we will dive deeper on what, why and how we do this.
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Data assets and sources
Understand what we mean about data assets and what are the sources they come from.
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Data pipelines
What is a data producer and what a data consumer? What is the origin of a data pipeline and what is its destination? Dive deeper into one of the most crucial parts of data products and infrastructure.
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Events and Normalisation
The blueprint of data strategy is how to organise and record your data. Here we will learn all about normalisation and events management.
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Database types and features
You have probably heard about relational databases. Although they are indeed the most common, they are just one of the many types of databases out there. Learn about columnar , key value pairs and more databases, their pros and cons and how you would select the right one for your organisation.
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Data processing
Would you opt for an ETL or an ELT processing sequence? What is a flat file and what are its pros against APIs? What is a CRM and what an ERP? Learn more about your processing options.
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Data Warehouses and Lakes
What is a data warehouse and what is a data lake? What are the pros of each and how do you choose the right approach for your organisation? Can you combine them?
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Data Modelling
How do you model your data to fit the purpose of your data products? What approaches are out there and how you make sure you chose the right one?
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Data Mesh and Data Platform
What is a centralised data platform and what is a data mesh? Learn more about these "trendy" concepts here
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Data Visualisation
How will users interact with your data products? What is the objective of data visualisation, what are the best practices and most important pitfalls to avoid?
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Cloud versus On Premise options
Would you opt for a cloud data platform solution or do you want to keep things within your premises? Learn more about these important decisions and what criteria you should choose.
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More Data Strategy & Infrastructure Decisions
There are more important decisions to consider. Do you build a data platform or would you buy one? And if so, would you go for commercial or out of the box solutions? What are the cost but also skill requirements? And who will do this, your in house team or an outsourced one?
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Building a data culture
How do you build an effective data culture across the organisation to foster your data strategy objectives?
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Section Conclusion
Recap on what we have learnt
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Data Strategy Quiz
Test your knowledge before continuing the journey!
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Section Introduction
Section Introduction
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Understanding Data Governance
What is data governance and why is it important?
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Data Governance Principles
Learn more about the data governance principles, the pillars based on which your strategy is built.
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Data Quality and Integrity
One of the most important aspects of data governance is data quality and integrity. Lets learn why
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Data Governance Frameworks
What are some popular data governance frameworks, which are their objectives, components and pros & cons?
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Trust in Data
How do you built trust in data and why is this important?
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Data Governance Tools
What kind of tools are out there within the data governance space, what are their objectives and why should you care?
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Section Conclusion
Recap on what we have learnt
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Data Governance Quiz
Test your knowledge before progressing further.
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Section Introduction
Section Introduction
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Discovery & Ideation
The start of every product! How do you identify the right opportunities and how do you start the discovery process
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Prioritisation
After identifying many opportunities you need to prioritise which ones to tackle. Here we ll talk about this process and go through some key frameworks and examples of prioritisation.
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MVPs and Prototypes
What is a minimum viable product and how does it differ from a prototype? Why are both important?
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SLAs & Data Contracts
Service level agreements and data contracts are bespoke parts of the lifecycle , here we will dive deeper on why
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Development, Testing and Deployment
Dive deeper into the intricacies of developing , testing and deploying data products
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Monitoring , evaluating, optimising and retiring
Understand why we need to monitor and evaluate our products so we can optimise them and ensure they still cover the needs of stakeholders.
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Challenges of the data product lifecycle
Data products don't come with their fair amount of challenges! Here we will dive deeper in these so you are better prepared.
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Section Conclusion
Recap on what we have learnt
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Data Products Lifecycle Quiz
Test your knowledge!
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Section Introduction
Section introduction and outline
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Technical Skills
Understand the key technical skills you need to master, from SQL to machine learning algorithms
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Business acumen and Domain knowledge
A data PM cannot survive in this landscape without a true understanding of the business and industry he operates in! Learn more about how these competencies will help you.
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Problem solving and analytical skills
A data PM's life is all about identifying and solving problems. See how these skills can make your life easier.
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Leadership skills
A product manager needs to lead his team under a common purpose and goal. See how leadership skills can help you in that journey.
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Agile methodologies
Nowadays all product development teams are working under agile methodologies, be it Scrum, Kanban or ML Ops. Learn more about these and be better prepared .
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Stakeholder identification and mapping
Understanding who your stakeholders are and what are their needs is one of the most crucial parts of the job. Learn some tips on how to do this effectively.
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Mastering prioritisation
If only you had enough time and resources to pursue all opportunities. Prioritisation is essential to make sure you are allocating your resources in the most value adding and feasible objectives.
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Creating data product roadmaps
Here is where you shine! Roadmaps are effective communication tools for both your stakeholders and your internal development team. Learn how to craft them effectively.
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Communication skills
Communication is perhaps the most important skill in a data PM's arsenal. Learn why and how you can improve it.
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Managing expectations
You can never make everyone happy. But you can keep them from getting upset. Here we will dive deeper in some of the techniques for effective expectations management
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Collaborating with the data team
Data PM's do not live in silos. Your data team is your best ally. Learn how you can work with them most efficiently.
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Collaborating with cross-functional teams
Collaborating with external and cross functional is not a nice to have; it is a guarantee for success for your products. Learn why.
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Section Conclusion
Recap on what we have learnt.
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Key Skills for data product managers quiz
Test your knowledge on the key product manager skills module.
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Section Intro
Section introduction and outline
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Finding the right role
Understand the differences of the various data product roles and how to find the right one for your skills and needs
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Preparing for an interview.
Learn how to ace your interview!
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Your first 90 days in your new role
You don't get a second chance for a first impression! Make your first 90 days matter!
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Lifelong learning
Your learning journey does not end here. Make sure you keep yourself posted on changes and new concepts
