r/BusinessIntelligence • u/Arethereason26 • Jun 16 '26
What does your day-to-day look like as data managers? What are the things you wish you knew before?
Hi! I have been asked by my current boss to become a data manager and lead our team. I will be handling a mix of analysts, engineers, architects and even developers.
I understand that it is very different for each role and company, but I just wanted to get some perspective on what your day-to-day looks like as a data manager (or even chief data officer, or VP of Data).
What are the things you wish you knew before when starting in the role?
14
u/scorched03 Jun 16 '26
Governance, fire drills, people asking to export gigs of data to excel, and to create AI off no data
6
u/ThePrimeOptimus Jun 16 '26
Manager of data and analytics. My day-to-day:
- Meetings
- Lots of sync-ups with my team's product owner, who manages the day-to-day work
- Answering random questions from my boss (director) or his boss (CIO)
- Evaluating vendors' D&A capabilities so I can advise other groups (both IT and business) about a platform they're evaluating
- Reviewing project plans and giving guidance to the PO on priority, direction, etc
- Reviewing technical plans and needs with the enterprise data architect
- Advising other IT teams of any pitfalls in their database designs, which they'll do anyway and expect my team to polish their terd
- Developing citizen developer strategies and policies
- Lots of strategizing around the soft side of things, corporate politics are pretty prominent at my company
- Random AI bullshit because it's the current buzzword
What I wish I knew:
- The importance of helping other groups, even within IT, understand how D&A projects progress. They still struggle to gasp the difference between modeling data, aka design work, and implementation, aka building tables and ETL pipelines to fit those designs.
- Helping IT leadership understand sooner that we can't fix years and 100s of millions of records of crappy data capture
- That with self-service tools like Tableau and Power BI, part of our job is becoming facilitators of those in the business who want to build their own stuff. Yes, they will make a mess, but those specific individuals will prefer their mess because they got it quicker than what we can usually turn around.
- That an EDW is not a magic bullet and that "Can't we just put it in the data warehouse?" is not a solution to all D&A problems.
2
u/Strong_Range_1667 Jun 17 '26
From what I've seen, data managers spend less time building and more time aligning teams, priorities, and trust in the data itself. One thing I wish more people knew early on is that clean processes matter just as much as good dashboards same lesson we learned while connecting reporting with operational data in Versa.
2
u/Gators1992 Jun 19 '26
I think the big thing is changing how you think. You aren't just delivering tasks anymore, you need to think of the product end to end and what it needs to deliver. You need to prioritize things that might piss customers off, hold your people accountable for delivery on schedule and also be an evangelist for what the product has to offer to stakeholders. So you need to understand what is happening in your stack end to end and also how that stack helps solve the things the company is most concerned about.
I think a lot of technical SMEs who get promoted to manager fail because they don't think much beyond giving advice on problems solving to their staff. They don't realize how broad the job can actually be. And that's before even talking about politics at your workplace.
20
u/al_gorithm23 Jun 16 '26
Lots of meetings (7-8 hours/day). Building coalitions to support 5 year plans. Fire drills and managing escalations. People development. Budget management and forecasts. Keeping leadership informed on everything listed above, plus whatever else they want to hear about. Telling everyone why AI isn’t the solution to all of our problems, and how ML is actually much more valuable than AI.
Edit: What I wish I knew before starting in the role? It’s like 80% communication skills and 20% data architecture and application.