We map the questions the business actually needs answered, then sequence the data, modeling, and reporting work to answer them in priority order instead of all at once.
We build the certified metric layer so revenue means the same thing in Finance, Sales, and the board deck. One definition, queried by everyone.
We design and build the reporting in Tableau or Power BI on top of clean, governed data, so the dashboards load fast and the numbers hold up in a meeting.
We put ownership, definitions, and access behind every metric that matters, so the number stays right after we leave and analysts stop re-deriving it by hand.
Finance, Sales, and Operations each query the data their own way and walk into the meeting with three revenue figures. Nobody can say which one is right.
The reports exist but they take a minute to load and disagree with the source system, so people export to a spreadsheet and work around them.
Your most expensive people spend the week cleaning exports and rebuilding the same pull, because there is no modeled layer underneath the reporting.
We turn raw business data into reporting people can act on. That means modeling the data, defining each metric once, building the dashboards in Tableau or Power BI, and putting governance behind the numbers so they stay right. The goal is one trusted source of truth, not another dashboard nobody believes.
A BI developer builds what you ask for. We diagnose what is actually broken first, the data model, the metric definitions, the governance, then fix the root cause. A dashboard built on an ungoverned data layer inherits the same disagreements it was supposed to solve.
Tableau and Power BI for the BI layer, Snowflake and Databricks for the warehouse, dbt for transformation. We are vendor-neutral. We work in the stack you already run and say so when a tool is not the problem.
It depends on the state of your data, the number of metrics to certify, and how much reporting you need built. We scope every engagement against a fixed set of deliverables and milestones before any work starts, so you see the number before you commit. Start with an audit and we will give you a scoped plan.
A scoped first certified metric set and a trusted dashboard typically lands in 6 to 8 weeks. Larger foundations take longer, but we sequence the work so you get a usable result early rather than waiting for a full rebuild.
Yes. We rarely recommend starting over. We audit what you have, find the gaps, and fix them in place. A full rebuild is the exception, not the default, and we will tell you plainly when it is warranted.
Senior-led data analytics consulting: metric certification, semantic modeling, and BI builds in Tableau and Power BI. One trusted number for every team.
Metric certification, semantic modeling, and BI builds. One trusted source of truth for every team.
There is no flat rate, and anyone who quotes one before seeing your data is guessing. These are the factors that move the effort.
Clean, modeled data is quick to report on. Fragmented sources and undefined metrics add discovery and cleanup.
Each metric that needs an agreed definition, an owner, and access rules is work. The count sets the governance effort.
How many dashboards, in which tool, and how many audiences they serve shapes the build.
Standing up ownership, documentation, and training so the numbers stay right is more than a one-time build.
You have dashboards but people export to spreadsheets anyway.
The numbers disagree by definition: start with Semantic Layer Engineering.
You are standing up or scaling Snowflake: see Snowflake Consulting.
The large firms sell analytics inside a bigger program, staffed with juniors. Here is where a senior-led boutique is different.
Not every engagement is a full build. Pick the entry that matches where you are, and we scope from there.
A fixed-scope diagnostic of your data, metrics, and reporting. You get a prioritized fix list and a scoped plan before any build begins.
A defined engagement with fixed deliverables and milestones: the metric layer, the model, and the dashboards. You see the number before you commit.
We run it after we build it. Ongoing monitoring, change requests, and support so the numbers stay right without a new hire.
We hand it off. Documentation, training, and pairing so your analysts own the reporting and stop re-deriving metrics by hand.
Most companies do not have a reporting problem, they have a definition problem. The dashboards exist. The numbers disagree. We fix the data model and the metric layer underneath your analytics so every team pulls the same trusted number, and the dashboards finally hold up in a meeting.
Data analytics consulting turns raw business data into reporting teams can trust and act on. Thinklytics models your data, defines each metric once, builds the dashboards in Tableau or Power BI, and puts governance behind the numbers, so every team works from one source of truth instead of three conflicting spreadsheets.
We build the BI environment on clean, governed data, in Tableau or Power BI, so the reporting is fast and the numbers hold.
One certified definition of every metric, so the number is the same everywhere and AI can reason on it.
The modeled, governed data layer underneath the reporting, so every metric you pull actually means something.
Start with an audit. We review your data, your metrics, and your reporting, then give you a prioritized fix list before any work begins.