How to Create a Financial Dashboard in Looker

Creating a financial dashboard in Looker is one of the best ways to get a real-time, consolidated view of your company's performance. Instead of chasing numbers across spreadsheets and accounting software, you can build a single source of truth to track revenue, expenses, and profitability. This guide will walk you through the essential steps, from planning your metrics to assembling the final visualizations.

First, Plan Your Financial Dashboard

Jumping straight into building without a clear plan is a recipe for a confusing dashboard. Before you even open Looker, take a few minutes to outline what you need. A well-planned dashboard provides clear answers, while a poorly planned one just creates more questions.

Identify Your Audience and Key Questions

Who is this dashboard for? The metrics a CFO needs are very different from what a sales manager or marketing lead is looking for. An executive dashboard might focus on high-level trends like net profit margin and cash flow, while a departmental one might track budget vs. actual spend.

Start by asking:

Who will use this dashboard most often? (e.g., C-suite, finance team, department heads)
What are the top 3-5 questions they need to answer? (e.g., "Are we on track to hit our quarterly revenue target?" or "Which department is overspending its budget?")
What actions will they take based on this information? (e.g., adjusting ad spend, re-evaluating pricing, hiring new staff)

The answers will help you focus on the metrics that truly matter and avoid creating a dashboard cluttered with vanity metrics.

Choose the Right Financial KPIs

Once you know your audience and their key questions, you can select the Key Performance Indicators (KPIs) to display. Your goal is to provide a complete picture of financial health without overwhelming the user.

Here are some of the most common and valuable financial KPIs to consider:

Revenue Metrics

Gross Revenue: The total sales revenue before deducting any costs.
Net Revenue: Gross revenue minus returns, allowances, and discounts. A more accurate reflection of actual income.
Monthly Recurring Revenue (MRR) / Annual Recurring Revenue (ARR): Essential for SaaS and subscription businesses to track predictable income over time.
Revenue Growth Rate: The percentage increase or decrease in revenue over a specific period, crucial for tracking business momentum.

Profitability Metrics

Gross Profit Margin: (Net Revenue - COGS) / Net Revenue. Shows how profitable your core product or service is.
Net Profit Margin: (Net Income / Revenue) * 100. The ultimate bottom-line metric, showing what percentage of revenue is left after all expenses are paid.
EBITDA: Earnings Before Interest, Taxes, Depreciation, and Amortization. A popular metric for evaluating a company's operating performance.

Cash Flow Metrics

Operating Cash Flow (OCF): The cash generated from normal business operations. A key indicator of a company's ability to cover its short-term liabilities.
Free Cash Flow (FCF): Operating Cash Flow minus capital expenditures. This is the cash a company has left over to invest, pay down debt, or return to shareholders.
Cash Burn Rate: How quickly a company is spending its cash reserves, particularly important for startups and high-growth companies.

Expense Metrics

Cost of Goods Sold (COGS): The direct costs of producing goods or services.
Operating Expenses (OpEx): Expenses not directly tied to production, like rent, salaries, and marketing costs. Often broken down by department (e.g., Sales & Marketing, R&D).
Budget vs. Actual Spend: Comparing planned expenses to actual spending to keep costs in check and ensure departments are sticking to their budgets.

Check Your Data Sources

Finally, where does all this financial data live? Your raw data is likely spread across multiple platforms. Common sources for a financial dashboard include:

Accounting Software: QuickBooks, Xero, NetSuite
Payment Processors: Stripe, Braintree, PayPal
CRMs: Salesforce, HubSpot (for tracking revenue pipelines)
Billing Platforms: Chargebee, Recurly
In-house Databases: A SQL database (PostgreSQL, MySQL, etc.) where your application or transaction data is stored.

Looker will need access to these sources, which are typically funneled into a central data warehouse like BigQuery, Snowflake, or Redshift for easier querying.

Step-by-Step Guide to Building a Financial Dashboard in Looker

With a solid plan in place, you’re ready to start building. Looker's power lies in its modeling layer, LookML, which lets you define business logic once and reuse it across all your reports. This ensures everyone is using the same definitions for key metrics like "revenue" or "profit margin."

Step 1: Connect Your Data

Before you can visualize anything, Looker needs to be connected to the database where your financial data resides. If you haven’t done this already, an administrator will need to go to Admin > Database > Connections and add the connection details for your data warehouse. Looker supports a wide variety of SQL databases, making this step relatively straightforward.

Step 2: Model Your Data with LookML

This is where Looker really shines. Instead of writing one-off SQL queries for every chart, you create a LookML model. This model acts as an abstraction layer over your database, allowing you to define dimensions (attributes like 'date', 'customer name', 'department') and measures (calculations like 'total revenue', 'average transaction value').

For a financial dashboard, a LookML developer would:

Create Views: A view file typically corresponds to a single table in your database (e.g., a transactions table).
Define Dimensions: Within a view, you define your dimensions. These are the fields you’ll use to group or filter your data.
Define Measures: Measures are your aggregations. You might create a total_revenue measure by summing the amount column from your transactions table.

For example, a simple measure for total revenue in a transactions view might look like this:

And a more complex measure for Gross Margin might be:

Defining these in LookML ensures that every time someone pulls "Gross Margin" anywhere in Looker, they get the exact same, correct calculation.

Step 3: Explore Your Data and Create "Looks"

Once your LookML model is set up, you can start building visualizations - called "Looks" in Looker. This is done in the Explore interface, a user-friendly query builder that non-technical users can use.

To create a Look for "Monthly Revenue":

Navigate to an Explore based on your financial data.
From the field picker on the left, select a time dimension (e.g., “Transaction Month”).
Select the measure you want to track (e.g., “Total Revenue”).
Click “Run.”
Under the “Visualization” tab, choose a chart type that best represents the data. A line chart is perfect for tracking revenue over time.
When you're happy with the chart, click the gear icon in the top right and select Save > As a Look. Give it a descriptive name like "Monthly Revenue Trend."

Repeat this process for each of your key KPIs - one Look for Gross Profit Margin, one for OpEx by Department, etc. These individual Looks will be the building blocks of your dashboard.

Step 4: Assemble Your Looks into a Dashboard

Now it’s time to bring all your Looks together into a single dashboard.

Navigate to the folder where you want to save your dashboard and click New > Dashboard.
Give your dashboard a name, like "Executive Financial Overview."
Once inside your new empty dashboard, click "Add Tile."
You can now choose to add visualizations from your saved Looks. Add the "Monthly Revenue Trend" Look you just created.
Continue adding your other saved Looks as tiles. You can easily drag, drop, and resize the tiles to create a logical layout. A common practice is to place the most important, high-level numbers (known as "single value" visualizations) across the top.

Step 5: Add Interactive Filters

A static dashboard is good, but an interactive one is great. Filters allow users to dig deeper into the data without needing to build a new report. The most common filter for a financial dashboard is a date range.

To add a filter:

In dashboard edit mode, click Filters > Add Filter.
Name your filter (e.g., "Date Range").
Set the “Control” to the desired type, such as “Date Range.”
Under the “Tiles to Update” tab, select each tile on your dashboard. For each tile, specify the field that the filter should apply to (e.g., link it to the "Transaction Month" field).
Click "Add" and save your dashboard changes.

Now, users can select a specific time frame, and all the charts and numbers on the dashboard will update automatically to reflect that period.

Best Practices for Effective Financial Dashboards

Tell a Story: Organize your dashboard logically. A good flow might be: High-level summary at the top (Total Revenue, Net Profit), followed by trends over time (revenue and expense line charts), and finally breakdowns by category (spend by department).
Use the Right Chart: Don't force a pie chart where a bar chart works better. Use line charts for trends, bar charts for comparisons, tables for detailed data, and single value cards for headline KPIs.
Provide Context: A number like "$500,000 in revenue" is more meaningful with context. Include comparisons to the previous period (e.g., +15% vs. last month) or progress towards a goal (e.g., 85% of quarterly target).
Keep it Clean: Resist the urge to add every possible metric. A cluttered dashboard is an ignored dashboard. If a metric doesn't help answer one of your key questions, leave it out.

Final Thoughts

Building a powerful financial dashboard in Looker is a process of thoughtful planning, careful data modeling in LookML, and intuitive visualization design. By focusing on the needs of your audience and adhering to best practices, you can transform raw financial data into a critical tool for strategic decision-making.

We created Graphed because we know that process can be complex and time-consuming, even for experienced analysts. Instead of navigating LookML and manually arranging tiles, Graphed allows you to connect your financial data sources and simply ask for what you need in plain English - like "Show me a dashboard comparing our MRR and total ad spend over the last six months." Our AI-powered analyst builds the real-time, interactive dashboard for you in seconds, saving you hours of setup and maintenance so you can get straight to the insights.