From Data to Insights: The Strategy of a Data Analytics Team
From Data to Insights is a practical guide to building a strategy that addresses the common issues faced by Data Analytics teams. Not enough time, too many requests, unhappy stakeholders, and colleagues with low team morale are just some of the problems caused by poor strategy and design.

This guide will help managers avoid these pitfalls and improve team performance by focusing on long-term goals and strategic planning, ensuring your Data Analytics team can effectively support their business and its stakeholders.

Practical examples and explanations are provided to help understand how a Data Analytics team’s strategy can be implemented and why certain approaches will or won’t work.

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From Data to Insights: The Strategy of a Data Analytics Team
From Data to Insights is a practical guide to building a strategy that addresses the common issues faced by Data Analytics teams. Not enough time, too many requests, unhappy stakeholders, and colleagues with low team morale are just some of the problems caused by poor strategy and design.

This guide will help managers avoid these pitfalls and improve team performance by focusing on long-term goals and strategic planning, ensuring your Data Analytics team can effectively support their business and its stakeholders.

Practical examples and explanations are provided to help understand how a Data Analytics team’s strategy can be implemented and why certain approaches will or won’t work.

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From Data to Insights: The Strategy of a Data Analytics Team

From Data to Insights: The Strategy of a Data Analytics Team

by John Mackay
From Data to Insights: The Strategy of a Data Analytics Team
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From Data to Insights: The Strategy of a Data Analytics Team

From Data to Insights: The Strategy of a Data Analytics Team

by John Mackay

Overview

From Data to Insights is a practical guide to building a strategy that addresses the common issues faced by Data Analytics teams. Not enough time, too many requests, unhappy stakeholders, and colleagues with low team morale are just some of the problems caused by poor strategy and design.

This guide will help managers avoid these pitfalls and improve team performance by focusing on long-term goals and strategic planning, ensuring your Data Analytics team can effectively support their business and its stakeholders.

Practical examples and explanations are provided to help understand how a Data Analytics team’s strategy can be implemented and why certain approaches will or won’t work.

Product Details

ISBN-13: 9789819635443
Publisher: Springer Nature Singapore
Publication date: 03/04/2025
Pages: 118
Product dimensions: 6.10(w) x 9.25(h) x (d)

About the Author

John Mackay is a seasoned data and analytics manager with over two decades of experience building and leading high-performing teams that deliver actionable insights and drive business success. Beginning his career in finance at one of Europe’s largest banking groups, he has held every role in a data analytics team – from engineering and analysis to testing and management – perfecting his skills in designing innovative strategies, implementing comprehensive data infrastructures, and developing reporting suites that significantly improve business outcomes.

Currently serving as the Group Analytics Senior Manager at a global technology firm, John oversees multiple analytics teams and provides consultancy to Fortune 500 companies. His passion has been in not only creating and implementing strategies to a wide variety of teams, but also about ensuring they are effectively maintained over the long term, deeply understanding the impacts of each decision. John has established himself as a trusted leader and mentor in the ever-evolving world of data and analytics.

Table of Contents

Chapter 1. Introduction: Day 1 Strategy.- Chapter 2. Leadership.- Chapter 3. Building a Team.- Chapter 4. Data Sources.- Chapter 5. Data Processing.- Chapter 6. Other Data Considerations.- Chapter 7. Stakeholders.- Chapter 8. Reporting and Insight.- Chapter 9. Strategy.- Chapter 10. Conclusion.

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