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Data Science: Create Teams That Ask the Right Questions and Deliver Real Value
Learn how to build a data science team within your organization rather than hiring from the outside. Teach your team to ask the right questions to gain actionable insights into your business.
Most organizations still focus on objectives and deliverables. Instead, a data science team is exploratory. They use the scientific method to ask interesting questions and run small experiments. Your team needs to see if the data illuminate their questions. Then, they have to use critical thinking techniques to justify their insights and reasoning. They should pivot their efforts to keep their insights aligned with business value. Finally, your team needs to deliver these insights as a compelling story.
Insight!: How to Build Data Science Teams that Deliver Real Business Value shows that the most important thing you can do now is help your team think about data. Management coach Doug Rose walks you through the process of creating and managing effective data science teams. You will learn how to find the right people inside your organization and equip them with the right mindset. The book has three overarching concepts:
You should mine your own company for talent. You can't change your organization by hiring a few data science superheroes.
You should form small, agile-like data teams that focus on delivering valuable insights early and often.
You can make real changes to your organization by telling compelling data stories. These stories are the best way to communicate your insights about your customers, challenges, and industry.
What Your Will Learn:
Create data science teams from existing talent in your organization to cost-efficiently extract maximum business value from your organization's data
Understand key data science terms and concepts
Follow practical guidance to create and integrate an effective data science team with key roles and the responsibilities for each team member
Utilize the data science life cycle (DSLC) to model essential processes and practices for delivering value
Use sprints and storytelling to help your team stay on track and adapt to new knowledge
Who This Book Is For
Data science project managers and team leaders. The secondary readership is data scientists, DBAs, analysts, senior management, HR managers, and performance specialists.
Most organizations still focus on objectives and deliverables. Instead, a data science team is exploratory. They use the scientific method to ask interesting questions and run small experiments. Your team needs to see if the data illuminate their questions. Then, they have to use critical thinking techniques to justify their insights and reasoning. They should pivot their efforts to keep their insights aligned with business value. Finally, your team needs to deliver these insights as a compelling story.
Insight!: How to Build Data Science Teams that Deliver Real Business Value shows that the most important thing you can do now is help your team think about data. Management coach Doug Rose walks you through the process of creating and managing effective data science teams. You will learn how to find the right people inside your organization and equip them with the right mindset. The book has three overarching concepts:
You should mine your own company for talent. You can't change your organization by hiring a few data science superheroes.
You should form small, agile-like data teams that focus on delivering valuable insights early and often.
You can make real changes to your organization by telling compelling data stories. These stories are the best way to communicate your insights about your customers, challenges, and industry.
What Your Will Learn:
Create data science teams from existing talent in your organization to cost-efficiently extract maximum business value from your organization's data
Understand key data science terms and concepts
Follow practical guidance to create and integrate an effective data science team with key roles and the responsibilities for each team member
Utilize the data science life cycle (DSLC) to model essential processes and practices for delivering value
Use sprints and storytelling to help your team stay on track and adapt to new knowledge
Who This Book Is For
Data science project managers and team leaders. The secondary readership is data scientists, DBAs, analysts, senior management, HR managers, and performance specialists.
- GenresTechnology
270 pages, Paperback
Published November 18, 2016
14 people are currently reading
63 people want to read
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Displaying 1 - 3 of 3 reviews
March 14, 2021
A good non-technical book on how you should approach data science by asking questions and apply the scientific method to answer those questions.
If you are looking for technical guidance on executing data work, this is NOT the book for you.
If you are looking for guidance on how to take a high-level strategic view to data for business use and how to convey your findings to make lasting change in your organization by reaching people where they are, this is THE book for you. It is very good at that.
The writing was concise, non-fluffed, and enjoyable. I liked it very much.
If you are looking for technical guidance on executing data work, this is NOT the book for you.
If you are looking for guidance on how to take a high-level strategic view to data for business use and how to convey your findings to make lasting change in your organization by reaching people where they are, this is THE book for you. It is very good at that.
The writing was concise, non-fluffed, and enjoyable. I liked it very much.
February 7, 2021
the book should be for project manager but i doubt whether it is even good for them considering a lot of points given in the book are not as suitable for at least what i see in our own working environment.
December 28, 2021
As one who is in the middle of this process of building a data science (analytics) team, this was super helpful. This is much less about the tools of data science and much more about how to ask the right questions and the way you should structure the team to be successful. Simple, basic concepts that are so easy to gloss over and forget amidst all the hype around technology and tools. This is crucial to recognize, it is not the tools and technology that will make or break the ability to get the valuable insights from the data. Rather it is the focus to asking the right questions and being able to communicate the insights in the most effective way.
Displaying 1 - 3 of 3 reviews