7 Habits Of Effective Data Managers

Recommendations for further reading on all 7 habits included!

Running a successful data team is hard.

Data teams are expected to juggle a combination of ad-hoc requests, big bet projects, migrations, etc. All while keeping up with the latest changes in technology.

In the past few years I have gotten to work with dozens of teams and see how various directors and managers deal with these and other challenges.

Each of these managers has their unique approaches and philosophies. However, I will say that there were several common traits that I have seen across many of these individuals. From how they prioritize work to getting buy-in from their leadership.

So for those who are looking to switch into a managerial role or perhaps just curious, here are 7 habits of effective data managers and directors.

1) The Ability To Prioritize and Say No

Data teams can get pulled into a lot of directions. People will ask you for ad-hoc data pulls and one-off dashboards that don’t align with the business. Thus, it's important to have a data leader who can say no because they have a clear north star. The best data leaders I have worked with have stayed focused on their overall goal vs. switching to please every team that asks.

One example of this was when I talked to Abby Kai Liu who discussed her team's focus on having one dashboard for their specific stakeholders (instead of thousands that no one looks at). From her perspective, there is only so much her data team can support and more importantly, only so much a business team can respond to. After all, data teams don’t operate in a vacuum; if all you do is create dashboards for the sake of dashboards, you won’t drive as much value as you think.

Here is some other content you can dig into to learn more about prioritizing and saying no:

1. Prioritize Ruthlessly by

   Ryan Peterman

2. The Product Development Life-Cycle For Dashboards - With Abby Kai Liu

2) Collaboration

"Talent wins games, but teamwork and intelligence win championships." – Michael Jordan

Data teams generally don't work in isolation. In turn, effective data managers and directors need to work with marketing, operations, sales, and other teams. They need to understand their problems, what drives them, and how the data team they manage can play a strategic role in the rest of the business. 

One of the ways that Ethan Aaron approached improving collaboration when he was head of BI was by creating camaraderie with other teams–whether that meant walking around with a drink cart on a Friday and just being personable or going to each of the leaders of other teams to understand their day-to-day problems. Overall, this is how you start the process of figuring out what projects you must deliver.

Here is some other content you can dig into to learn more about how to set-up your teams effectively:

1. 5 Best Practices for Data Science Team Collaboration

2. How To Set Up Your Data Analytics Team For Success – Centralized vs Decentralized vs Federated Data Teams

3) Clear Process for Deploying Results

It's one thing to run analysis or build pipelines. It is a totally different thing to translate those dashboards and metrics into something that the company can use. The best data leaders I have worked with have a clear process that helps guide them to take on new projects and then actually deliver them.

For example, when I talked with Tom Rampley - Sr. Director of Data & Analytics of Velocity Global - he referenced having a similar process to that of a product team. He referenced his process involving defining your persona, understanding their general business needs, and getting buy-in from your stakeholders (there was more but you’ll have to watch the video around the timestamp here). Because after starting the project, you’ll need to deliver it and figure out if it was successful or not!

Here is some other content you can dig into to learn more about how to deploy your projects successfully:

1. How Data Analytics Teams Can Deliver What The Business Needs

2. Looking Past Data Infrastructure - How To Deliver Value With Data

4) Team Empowerment

Whether it's been managers I have worked for or clients I have had, a common trait I have seen is the ability to empower people around them. They often create a safe space where their team members can grow and challenge themselves. 

Meaning that when the team member succeeds, it gets the praise required, and when a project doesn't go the way that it should, there is space to fail. This requires a lot of trust in both directions. The manager needs to trust their team and the team needs to trust that they won’t be chastised for trying new ideas or taking on more scope.

In the end, this leads to growth and experimentation that benefits the business.

Here is some other content you can dig into to learn more about how to empower your data team:

1. Incident Review and Postmortem Best Practices by

   Gergely Orosz

2. Empowering engineering effectiveness

5) Trust Builders

At the end of the day, if the business doesn't trust your data or results, your work doesn't really matter. That's probably why I have seen many data managers and directors spend time acting as evangelists for their team's work; get the business to buy in and understand that the data and results are reliable (because they have built systems to do so). There so many issues with data quality and expectations that data leaders need to constantly be ensuring that the work that their team produces is high quality (going back to limiting how many dashboards you create).

Here is some other content you can dig into to learn more about how to build trust:

1. How And Why We Need To Implement Data Quality Now!

2. Building Trust With Clients - With

   Irina Stanescu
   (non-listed Youtube Live!)

6) Deep Domain/Business

This one was brought up by Omar Halabieh, and I 100% agree. Data leaders aren’t just good at delivering technical work but also at understanding the business, in terms of understanding the domain, whether it’s healthcare or supply chain management, or how their project budgets are handled in accounting. All of this helps them make better cases for the work they take on. I’ll keep saying this, but data teams don’t operate in a vacuum; they need to build for the business which means they need to understand the business.

I know most of my readers are individual contributors, some of whom have taken on leadership roles, whether it be directly becoming a manager or indirectly by becoming a tech lead. I am sure some of these skills and traits resonated with you. 

Here is some other content you can dig into to learn more about how to build domain knowledge:

1. Data Is The How, Business Is The Why

7) Investing in the growth & development of their team members

When I posted on this topic on Linkedin, Drew Mooney provided this great point as well. That good managers and directors are also concerned about their teams growth and development. Which I would agree with. The best managers I have worked for always wanted to know what excited me, and what I was trying to learn. Obviously not every project you can take on aligns with your goals. But they often tried to line up conversations or introductions with other teams that might lead to the projects I’d like to work on.

Here is some other content you can dig into to learn more about how to invest in your own growth:

1. Becoming a Data Engineering Force Multiplier

2. Best Online Courses for Data Engineers

3. Check out my Youtube Channel or become subscribe to my newsletter(and if you want to read the past articles you can become a paid subscriber with this 40% off coupon)

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It could easily be said that many of these skills honestly transfer beyond just data leaders. However, I believe that much of the pressure on data teams to deliver drives these traits. So if you’re looking to make the switch to a leadership role and you’re wondering what to work on, I hope this was helped you.

Thanks for reading!

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Data Events Coming Up…

Dave Langer - Python in Excel, Data Science without "Data Scientists" by

Joe Reis

and Matthew Housley (past event)

The future of data transformation by Prophecy.io

Denver Data Low Key Happy Hour

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State Of Data Engineering And Infrastructure 2023!

If you missed it, last year we had well over 400 people fill out a survey to help provide insights into the data world. If you’re interested in participating, then please check out the survey here!

We would love to have 1000 people fill out the survey this year so we can share with our readers. You can also check out the articles from last year here.

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Join My Data Engineering And Data Science Discord

If you’re looking to talk more about data engineering, data science, breaking into your first job, and finding other like minded data specialists. Then you should join the Seattle Data Guy discord! We recently passed 4000 members!

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Articles Worth Reading

There are 20,000 new articles posted on Medium daily and that’s just Medium! I have spent a lot of time sifting through some of these articles as well as TechCrunch and companies tech blog and wanted to share some of my favorites!

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Planning Your Data Roadmap For 2024 – Elevating Your Data Strategy

It’s that time of year again.

When data leaders, VPs and Directors need to start planning out their data roadmap.

Of course, this brings up an important question, how should you start planning out your data roadmap?

Especially if you’re data team has found itself stuck in the data service trap. Simply providing data and dashboards when asked and never really becoming a strategic partner.

Now for some companies this is all that is needed. A service arm that provides some reports and numbers when asked. But if you’re team is either planning their current strategic data roadmap or wants to become a strategic partner, then now is the time to plan.

Over the past few weeks, I have been discussing the topic with several data leaders both on my Youtube Lives and in private, much of which has reinforced the methods I have picked up over the past decade.

Thus, I wanted to provide some tips to help those either in leadership positions or who want to break into these positions plan out their data roadmap for 2024.

Read More Here

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End Of Day 112

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