Global Agile Summit Preview: Implementing Agile Practices for Data and Analytics Teams with Henrik Reich

In this BONUS Global Agile Summit preview episode, we dive into the world of Agile methodologies specifically tailored for data and analytics teams. Henrik Reich, Principal Architect at twoday Data & AI Denmark, shares his expertise on how data teams can adapt Agile principles to their unique needs, the challenges they face, and practical tips for successful implementation.

The Evolution of Data Teams

"Data and analytics work is moving more and more to be like software development."

The landscape of data work is rapidly changing. Henrik explains how data teams are increasingly adopting software development practices, yet there remains a significant knowledge gap in effectively using certain tools. This transition creates both opportunities and challenges for organizations looking to implement Agile methodologies in their data teams. Henrik emphasizes that as data projects become more complex, the need for structured yet flexible approaches becomes critical.

Dynamic Teams in the Data and Analytics World

"When we do sprint planning, we have to assess who is available. Not always the same people are available."

Henrik introduces the concept of "dynamic teams," particularly relevant in consulting environments. Unlike traditional Agile teams with consistent membership, data teams often work with fluctuating resources. This requires a unique approach to sprint planning and task assignment. Henrik describes how this dynamic structure affects team coordination, knowledge sharing, and project continuity, offering practical strategies for maintaining momentum despite changing team composition.

Customizing Agile for Data and Analytics Teams

"In data and analytics, tools have ignored agile practices for a long time."

Henrik emphasizes that Agile isn't a one-size-fits-all solution, especially for data teams. He outlines the unique challenges these teams face:

• Team members have varying expectations based on their backgrounds

• Experienced data professionals sometimes skip quality practices

• Traditional data tools weren't designed with Agile methodologies in mind

When adapting Agile for data teams, Henrik recommends focusing on three key areas:

• People and their expertise

• Technology selection

• Architecture decisions

The overarching goal remains consistent: "How can we deliver as quickly as possible, and keep the good mood of the team?"

Implementing CI/CD in Data Projects

"Our first approach is to make CI/CD available in the teams."

Continuous Integration and Continuous Deployment (CI/CD) practices are essential but often challenging to implement in data teams. Henrik shares how his organization creates "Accelerators" - tools and practices that enable teams to adopt CI/CD effectively. These accelerators address both technological requirements and new ways of working. Through practical examples, he demonstrates how teams can overcome common obstacles, such as version control challenges specific to data projects.

In this segment, we refer to the book How to Succeed with Agile Business Intelligence by Raphael Branger.

Practical Tips for Agile Adoption

"Start small. Don't ditch scrum, take it as an inspiration."

For data teams looking to adopt Agile practices, Henrik offers pragmatic advice:

• Begin with small, manageable changes

• Use established frameworks like Scrum as inspiration rather than rigid rules

• Practice new methodologies together as a team to build collective understanding

• Adapt processes based on team feedback and project requirements

This approach allows data teams to embrace Agile principles while accounting for their unique characteristics and constraints.

The Product Owner Challenge

"CxOs are the biggest users of these systems."

A common challenge in data teams is the emergence of "accidental product owners" - individuals who find themselves in product ownership roles without clear preparation. Henrik explains why this happens and offers solutions:

• Clearly identify who owns the project from the outset

• Consider implementing a "Proxy PO" role between executives and Agile data teams

• Recognize the importance of having the right stakeholder engagement for requirements gathering and feedback

Henrik also highlights the diversity within data teams, noting there are typically "people who code for living, and people who live for coding." This diversity presents both challenges and opportunities for Agile implementation.

Fostering Creativity in Structured Environments

"Use sprint goals to motivate a team, and help everyone contribute."

Data work often requires creative problem-solving - something that can seem at odds with structured Agile frameworks. Henrik discusses how to balance these seemingly conflicting needs by:

• Recognizing individual strengths within the team

• Organizing work to leverage these diverse abilities

• Using sprint goals to provide direction while allowing flexibility in approach

This balanced approach helps maintain the benefits of Agile structure while creating space for the creative work essential to solving complex data problems.

About Henrik Reich

Henrik is a Principal Architect and developer in the R&D Department at twoday Data & AI Denmark. With deep expertise in OLTP and OLAP, he is a strong advocate of Agile development, automation, and continuous learning. He enjoys biking, music, technical blogging, and speaking at events on data and AI topics.

You can link with Henrik Reich on LinkedIn and follow Henrik Reich’s blog.