Your First 90 Days As A BI Analyst

Starting a new BI analyst role is exciting, but it can also feel like being dropped into the deep end. You’re handed logins to a dozen tools, a pile of outdated dashboards, and a vague directive to “help us make better decisions.” Where do you even begin? 

The truth is, your first 90 days shouldn’t be about building flashy dashboards or complex models. It’s about laying the groundwork for long-term impact. Focus on three key areas: understanding the business (not just the data), addressing and rectifying issues that are broken, and delivering quick wins that demonstrate your reliability and trustworthiness.

Early progress doesn’t always look like big product launches or perfect reports. Sometimes it looks like getting the right stakeholders in a room to agree on a metric definition. Or reducing how often someone has to ask, “Which version of this number is correct?” That’s real momentum, and it matters just as much as what shows up in your dashboards.

This blog post walks you through what to focus on, when to do it, and how to track the signals that you’re headed in the right direction. If you’re looking for a clear path through the messy middle of onboarding, you’re in the right place. You’ll see where quick wins can come from cleanup, how to identify what matters, and how tools like Sigma can help you move faster without sacrificing thoughtfulness. Let’s get into it and set you up to make your mark from day one.

Before day 1: Set yourself up to learn fast

Starting a new role always comes with a bit of tension, especially when you’re stepping into a BI analyst seat for the first time. You might already be comfortable with data, maybe even a Sigma pro. But moving from report builder to insights partner presents a distinct challenge. The real work starts before you ever open a dashboard.

• Spend time understanding why the role exists. Every BI analyst role sits inside a story. Sometimes it’s a replacement. Sometimes it’s a new headcount to “make better use of data.” Ask what’s been working and what hasn’t. That context tells you where to look first.
• Get the lay of the land. Request documentation upfront, even if it’s incomplete or messy. Who owns what systems? Are there metrics definitions? Past reports? Any department with a data process, like marketing, finance, or operations, likely has artifacts worth reviewing. These will help you ask more effective questions in your initial meetings.
• Identify your early champions. One of the fastest ways to build momentum is to find the people who’ve been waiting for someone like you. Maybe it’s a product manager drowning in spreadsheets. Or a finance director who’s been doing double duty as the “Excel person.” Reach out and ask what they wish existed. Those pain points are gold. They’ll give you direction and likely become your strongest advocates when it’s time to share wins.
• Brush up on business fluency. It’s easy to obsess over syntax and tooling, but understanding how your company makes money and measures success will make you far more effective. Read recent board updates, skim product announcements, or sit in on customer calls if you can. These insights will shape how you prioritize work later. You’ll also build trust faster when you speak the same language as the teams you're supporting.
• Clarify expectations early. Ask your manager how they define success at 30, 60, and 90 days. Are they expecting quick wins? Stakeholder relationships? A dashboard revamp? The sooner you understand the shape of the runway, the more confidently you can move down it.

Make a list of what you to go through to ensure you feel prepared for your new role and responsibilities.

What success looks like in your first 90 days

Before diving into the timeline, it helps to reframe what success means in the early weeks. You’re not being measured on how many dashboards you ship or how technical you sound in meetings. You’re being measured on something harder to spot: how well you listen, how quickly you learn, and how clearly you can spot what matters. You’re stepping into a role with context that others have built up over months or years. It’s okay not to know everything on day one. Your value comes from asking thoughtful questions, noticing where things break down, and making sense of what’s already in place. That clarity is just as important as what you build later. 

The pressure to prove yourself early is real. But don’t confuse speed with success. Showing up, asking why things work the way they do, and documenting what’s missing? That’s progress. 

Days 1 to 30: Get oriented, not overwhelmed

In the first month, resist the urge to dive straight into dashboard building. You’ll add more value by slowing down and learning how the business runs. This month is all about listening, observing, and asking smart questions. Gather a complete picture of the data, the systems that support it, and the people who rely on it. 

Begin by scheduling one-on-one meetings with stakeholders from various departments. Don’t just talk to the usual folks in finance and operations; connect with the people who depend on reports to make daily decisions. Ask about what’s working, what’s missing, and where they feel stuck. These conversations often reveal hidden gaps or habits that have never been documented formally.

At the same time, conduct a comprehensive audit of the dashboards, reports, and data models you’ve inherited, identifying which ones are regularly used and which are not. Look out for reports that show different answers for the same metric, and note any inconsistencies in naming or logic. You're not there to criticize. You’re mapping out what exists and figuring out what makes sense to keep. 

If you hear phrases like “Only Sarah knows how that works” or “We just copy this from an old sheet,” write it down. That’s tribal knowledge, and it’s fragile. Start documenting those details, even if it’s a rough outline in a shared doc or wiki. You’ll make everyone’s life easier just by getting things out of people’s heads and into a format others can use.

Make sure you have access to all tools and systems connected to your analytics work. That includes your data warehouse, dashboards, version control tools, and any documentation repositories. Ask early if something is missing so it doesn’t slow you down later.

The goal here isn’t to impress anyone with how fast you can build. It’s to understand what’s worth building at all.

Days 31 to 60: Trim the fat, boost the signal

Once you've mapped the current state of things, the next step is triage. The second month is your opportunity to refine what doesn’t work and make informed decisions about what stays, what goes, and what needs to be rebuilt. These small wins matter. They show people you’re paying attention and that their problems aren’t being ignored.

Start by reviewing every dashboard and report for accuracy and clarity. If two dashboards present different information about the same metric, investigate further. If a report hasn’t been opened in six months, ask who it was built for and whether it’s still needed. 

Don’t assume popularity means quality, but it’s usually a good place to start. Usage audits can reveal a great deal. Which dashboards are being viewed? Which ones are bookmarked or exported? This gives you a better sense of what helps people make decisions versus what merely takes up space. Use that insight to flag reports that are stale or redundant and suggest removing or consolidating them.

Then, examine how metrics are defined across the board. You’ll probably find more than one version of “customer churn” or “net revenue.” Pull those definitions into a shared document, discuss them with the stakeholders who rely on them, and work toward a consensus. Even small alignment here goes a long way toward reducing confusion down the road.

Now’s also the time to start improving performance. If you encounter dashboards that take a long time to load or reports that require multiple manual steps to refresh, mark those for improvement. This is where your technical skills can shine by rewriting a query or rebuilding a clunky report in a more modern format, makes an immediate impact. 

Sigma makes this easier. You can rebuild with clean logic, a shared metric layer, and a layout that works for non-technical users, without the need to export or duplicate data. Fixing legacy debt in a modern tool allows you to demonstrate what good looks like. The goal here is to make your work easier to maintain and easier for others to use.

Days 61 to 90: Build trust through new value

By now, you’ve taken inventory, cleaned up the mess, and clarified what your team needs. This is when people start expecting results. Not perfection, but progress they can see and share. Month three is your chance to show what’s possible when analytics is thoughtful, fast, and collaborative. With a clearer understanding of the lay of the land, you can begin to provide 

Start by building something new that answers a fundamental business question and addresses what the business is struggling to see clearly. Maybe it’s a report on customer retention trends or a comparison of product margins. Maybe marketing wants to understand why a campaign stalled. Maybe operations need better visibility into fulfillment delays. Choose a question that matters to the team and build a report that answers it simply, accurately, and in one place. Focus on one deliverable that addresses a gap you identified in your early conversations. Keep it tight and actionable. When people see their feedback turn into insights, it builds momentum and credibility.

Next, look for reporting that’s still being done manually, such as monthly decks, weekly updates, and spreadsheet snapshots. These are time sinks waiting to be automated. Set up refreshable dashboards that eliminate repetitive tasks. When done correctly, this saves time and helps teams respond more quickly to changes.

This is also the time to connect the dots between departments. Analytics often lives in silos, but business questions don’t. Collaborate with different teams to build dashboards that reflect shared goals across finance and sales, for example, or marketing and support. With data apps, you can take that a step further, creating interactive, purpose-built tools that let business users explore data on their own, take action in the moment, and even write back directly to your warehouse. Instead of fielding endless one-off requests or sending out static reports, you’re giving teams a place to collaborate, update inputs, and answer their own questions. That shift from reactive reporting to shared insight and action is where your work starts to change how people operate.

If your team is ready, outline a simple roadmap of where you want to go next. That could include improving data quality, closing reporting gaps, or building more cross-functional tools. You don’t need a five-year plan. Just show you’re thinking ahead and planning with purpose.

Metrics that matter in your first 90 days

You’ve spent the first three months making sense of the data, fixing what’s broken, and delivering new value. But how do you know if it’s working? The answer isn’t in a single KPI, it’s in a collection of signals that show your impact. Some are clear and measurable, while others are more subtle, showing up in conversations or team behavior. Both are equally important.

Measurable progress to track

There’s no shortage of dashboards to build, reports to run, or questions to answer. However, to determine whether your first 90 days moved the needle, focus less on volume and more on traction. Below are a few ways to measure whether your work is making a real difference.

Time-to-value: How fast are answers turning into decisions?

One of the clearest indicators that your work is creating value is how quickly teams can go from asking a question to getting an answer they trust. If you’ve shortened that cycle, perhaps by replacing manual steps with refreshable dashboards or by reducing the complexity of existing queries, you’ve improved the pace of decision-making. 

That kind of progress often gets noticed by people outside the data team, even if they don’t explicitly acknowledge it. You might hear it in passing: 'This is exactly what I needed,' or 'We finally have a clear picture.' Those are subtle wins, but they mean you’re helping decisions happen faster and with more confidence.

Stakeholder satisfaction: Are your dashboards being used without you?

Usage metrics can also paint a picture of what’s working. Pay attention to which dashboards are opened most often, which ones get bookmarked, and which reports are shared in recurring meetings. If your dashboards are being used without needing your involvement every time, that’s a strong sign of impact. In Sigma, you can often see which workbooks are gaining traction simply by watching how different teams interact with them over time.

Cleaning house: What legacy clutter did you clean up?

Cleaning up legacy assets is another area worth tracking. If you’ve identified outdated reports, retired dashboards that no one uses, or merged multiple views into one standardized version, keep a log of those changes. While these tasks may not seem impressive on the surface, they reduce maintenance costs, enhance data quality, and enable others to navigate the analytics stack more efficiently. Over time, that adds up to better outcomes and fewer repeated mistakes.

Adoption: Who’s using your tools without help?

You should also monitor how your self-service tools are being adopted. If you’ve created dashboards or Sigma Data Apps that allow non-technical users to explore metrics on their own, keep track of how often those tools are accessed. More independent exploration usually means people trust the data and feel comfortable using it without needing to consult you every time they require a number.

And finally, tie your work back to outcomes. Did your analysis help marketing find a better lead source? Did a finance dashboard reveal a way to cut waste? Even anecdotal wins count, especially early on. The more you can connect your work to actual decisions or changes, the more valuable you become to the team.

Qualitative signals of success

Not every win will be reflected in usage statistics or system logs. Some of your most meaningful progress will come through informal feedback and the changing ways people interact with you. For example, if stakeholders begin referencing your dashboards during meetings or using your reports to back up decisions, that’s a strong signal that your work is becoming a trusted source. You might notice that fewer people are double-checking your numbers or requesting the same report in multiple formats. These small shifts in behavior are signs that your work is reducing friction and increasing clarity.

Another way to assess your impact is by examining when you’re brought into conversations. If you’re included earlier in planning or asked for input before key decisions are made, it shows that your voice is gaining influence. Being proactive during your first 90 days helps set this expectation. Over time, teams will begin to rely on your input as part of their regular decision-making process rather than as a last-minute data request.

You might also see improvements in cross-functional alignment. If you’ve worked on standardizing metric definitions or creating a single source of truth for recurring KPIs, you may hear fewer debates about which number is correct or which version of the truth to use. When teams start speaking the same language around metrics, even if just in pockets, that consistency often begins with the analyst who took the time to make things clear.

Lastly, pay attention to how often your name comes up when people discuss the analytics process. Are people referring others to you when they have a question? Are your dashboards being passed along as “the one to use”? These aren’t formal metrics, but they are signs that you’ve become someone the team trusts to add clarity, not confusion.

Your data’s future success awaits

The first 90 days in a BI analyst role aren’t about fixing everything at once. They’re about building a foundation by getting a clear read on what’s in front of you, making things easier to use, and showing you can be counted on. The teams around you are watching less for perfect dashboards and more for signs that you understand the business, ask the right questions, and follow through.

Learning the tools is part of the job. But learning the people: what they need, where they’re blocked, and how they think about data makes the difference. The impact you create isn’t just in the dashboards you build, but in how you help others use them with confidence. Cleanup matters just as much as creation. Removing friction, standardizing what gets reported, and improving access to existing data can create more momentum than a flashy new chart. It shows that you’re thinking about what helps the team work smarter.

With the right habits in place, you can go from the new hire to someone the team relies on. What you fix now, what you simplify, and what you document all lay the groundwork for better decisions later. And if you’re looking to do this kind of work with a team that’s building the future of analytics, check out our open roles.

What you build in your first 90 days sets the tone, but what you do next will shape how your company works with data moving forward.

‍