How to Use Looker

Getting started with Looker can feel like staring at a complex cockpit, but it's simpler than you might think once you understand the basic controls. It's a powerful tool for exploring data, but its true strength lies in how it enables anyone on a team to ask questions and get reliable answers. This guide will walk you through the fundamentals of navigating Looker, exploring your data, visualizing your findings, and building your first simple dashboard.

Understanding the Looker Landscape: Key Concepts

Before jumping in, it's helpful to understand a few core concepts that make Looker different from tools like Excel or Google Sheets. Looker is a web-based business intelligence platform that sits directly on top of your company's database. Its power comes from a special modeling layer called LookML.

What is LookML? (And Why You Should Care)

You won't be writing LookML as a business user, but it's the engine that makes Looker work. LookML is a modeling language that your data team uses to define all your business metrics and logic. It acts as a "single source of truth." When you see a field called Total Revenue, you can trust it's calculated the exact same way for everyone in the company.

This pre-defined logic prevents common reporting errors, like one person including tax and shipping in revenue while another doesn't. You can explore data with confidence, knowing the definitions are consistent and governed.

Explores: Your Starting Point for Analysis

An "Explore" is the interactive environment where you build queries to ask questions of your data. Think of it as a logical starting point for an investigation. Your data team will set up different Explores based on your business, such as:

• Orders Explore (for analyzing sales, products, and customer purchase data)
• Users Explore (for understanding user behavior and demographics)
• Website Traffic Explore (for analyzing sessions, sources, and pageviews)

You'll choose an Explore that contains the data relevant to the question you want to answer.

Dimensions vs. Measures: The Building Blocks of a Query

Every field within an Explore is categorized as either a dimension or a measure. Understanding this distinction is the most important part of using Looker effectively.

• Dimensions: These are the attributes, categories, or non-numerical fields in your data. They are what you use to group or segment your results. Dimensions typically appear in <em>blue</em>.
• Measures: These are the quantitative, numerical values that you can aggregate (sum, average, count, etc.). They are what you are measuring. Measures typically appear in <em>orange</em> or <em>brown</em>.

In short: Dimensions slice, Measures count.

Your First Steps: Navigating the Looker Interface

When you log in to Looker, the interface is fairly clean. The main area you'll use is the left-hand navigation panel. Here's what you need to know:

• Folders: This is where dashboards and reports (called "Looks" in Looker) are saved. You'll typically have a "My Folder" for your personal projects and "Shared Folders" for team reports.
• Browse Menu: This is where you'll find the launching pad for your analysis. Clicking Browse will show you all available Dashboards and, more importantly, the Explores your team has built for you. This is usually where you will start.
• History: Looker helpfully saves a history of the queries you've run recently. This can be a lifesaver if you accidentally close a tab or want to revisit an analysis from earlier.

Querying and Exploring Data: Your First Analysis

Now, let's get our hands dirty and build a real query. Let’s imagine we want to answer the question: "What were our total sales by product category over the last three months?"

Step 1: Choose Your Explore

First, navigate to Browse > Explores. You’ll see a list of available data sets. Since our question is about sales and products, an Explore named "Orders" or "Sales" would be the right choice. Let’s click on that.

Step 2: Select Your Dimensions and Measures

The Explore interface opens up. In the "All Fields" pane on the left, you'll see a searchable list of all dimensions (in blue) and measures (in orange), often grouped by topic. Based on our question, we'll need:

• A dimension to group by: Find the "Product Category" field and click it.
• A measure to calculate: Find the "Total Sales Amount" field and click it.

As you click each field, Looker adds it to the Data panel on the right.

Step 3: Filter Your Data

Right now, our query would pull sales data for all time, which isn’t what we want. We need to add a filter to limit the results to the last three months. To do this:

1. Find the "Order Date" dimension in the left pane. Instead of clicking it, hover over it and click the Filter icon that appears.
2. This adds the field to the "Filters" section at the top of the screen.
3. Click into the filter settings. Looker provides excellent, human-friendly options. We'll set the parameters to: Order Date "is in the past" 3 "complete months".

You can add filters to any dimension or measure to hone your query.

Step 4: Run the Query and View the Results

With our fields and filters configured, click the Run button in the top right corner. Looker translates your selections into a finely-tuned SQL query, runs it against the database in real-time, and displays the results in a data table below.

From Data to Insight: Visualizing Your Results

A data table is useful, but a chart is often much easier to interpret. Looker makes it simple to move from raw data to a presentation-ready visualization.

Step 1: Choose a Visualization Style

Above the data table, you’ll see a Visualization tab. Click it. Looker will try to guess the best visualization type for your data - in this case, probably a bar chart or a pie chart. You can easily override this by clicking on one of the chart icons displayed, such as Bar, Column, Line, or Pie.

Step 2: Customize Your Chart

For more control, click the Edit button (the gear icon) within the visualization pane. This opens a panel with dozens of customization options. You can:

• Change the color palette.
• Add value labels to your bars or segments.
• Adjust the labels for the X and Y axes.
• Stack series in a bar chart to show parts of a whole.

These settings give you the power to fine-tune your chart so it tells a clear story.

Step 3: Save Your Work as a "Look"

If this is a chart you'll want to refer back to again, you should save it. A saved query and its visualization setting are called a Look.

Click the gear icon in the top right of the screen (next to the Run button) and choose Save... > As a new Look.... Give your Look a clear title like "Sales by Category - Last 3 Months" and choose your personal folder. Now you can access this report anytime without rebuilding it.

Bringing It All Together: Creating Your First Dashboard

A dashboard is a collection of saved Looks and visualizations that give you a high-level view of performance. It's where you can monitor your most important metrics in one place.

Step 1: Create a New Dashboard

Start by navigating to your folder. Click the New button at the top and select Dashboard. Give it a descriptive name, like "My Key Performance Dashboard."

Step 2: Add Tiles to Your Dashboard

You'll see a blank canvas. To add your Look, click Add > Looks, search for the "Sales by Category - Last 3 Months" Look you saved earlier, and add it to the page.

This report is now a "tile" on your dashboard. You can resize it and drag it around to organize your layout. You can continue adding other Looks you've saved or even create new query tiles from scratch directly within the dashboard editor.

Step 3: Link Tiles with Dashboard Filters

The real power of a Looker dashboard comes from its interactive filters. You can add a filter to the dashboard that controls the data in all (or some) of its tiles simultaneously.

Go to Filters > Add Filter at the top of your dashboard. Let's add one for "Date." Once you've created the filter, you need to tell each tile which of its fields to "listen" to. Click the menu on your sales tile, select Edit Tile, go to the Filters tab, and link the dashboard date filter to the tile's "Order Date" field.

Now, anyone viewing your dashboard can change the date filter at the top (from "Last 3 Months" to "Last 30 Days," for example), and all linked tiles will update automatically.

Final Thoughts

Getting comfortable with Looker is about understanding its core concepts - Explores, Dimensions, and Measures - and then practicing the workflow of building queries, visualizing them, and curating them on a dashboard. This structure allows business users to safely explore massive datasets and find reliable answers without needing to know SQL.

While Looker is a phenomenal tool for organizations with dedicated data teams to manage its setup, sometimes you just need answers faster. We created Graphed to make getting those answers as simple as having a conversation. You can connect your marketing and sales data sources in seconds, and then just ask for the reports or dashboards you need in plain English. No learning curve, no waiting for a data team - just real-time insights when you need them.