Looker doubles as a Business Intelligence software and a Big Data Analytics platform that lets you analyze, explore, and share real-time business insights quite easily. Looker carries this out through its efficient Looker Reporting and Dashboarding processes. Looker houses support for multiple data sources and deployment methods without compromising on security, and transparency. With Looker, you can connect with 50+ supported SQL dialects that help avoid database lock-in, connect to multiple databases, based on and maintain Multi-Cloud data environments.
In this article, you will look at the Looker Reporting process in detail. This involves exploring the 3 main components involved in the process of Looker Reporting: saving, editing, and deleting a Look, which is an alias for a Looker Report. This article also covers the benefits and the working of Looker before diving into the Looker Reporting process.
Introduction to Looker
Looker primarily focuses on providing your teams with the tools they need to optimize their workflow. Looker ushers a Self-Service Analytical approach that helps drive results with embedded visualizations and personalized applications. With Looker, you can hit the ground running with an application customized for your need. Here are a few business use cases:
- Digital Marketing Analytics: You can customize powerful reports around Facebook Ads, Google Ads, and a couple of others to understand ad spend across channels better. Looker houses a unified cross-channel dashboard that can help you make informed bid changes on the spot, on the basis of active ad performance updates.
- Web Analytics: You can support your teams with access to shareable data from Google Analytics and sharpen visibility into Sales and Marketing performance through a Single Source of Truth. With Looker, you can also drill deeper into your website with features like dynamic cohorts, cross-property analysis, and alert schedules to name a few.
- Sales Analytics: Sales Analytics focuses on maximizing Retention and Upsell while minimizing Churn. With a centralized point of contact, you can combine data from multiple systems to gain valuable insights into your target audience. You can also manage every level of your Sales hierarchy with customizable and governed workflows.
Business Intelligence security is a priority when it comes to Looker which is evident from its fine-grained access controls that support three levels of data governance:
- Group Level: Group Level limits what content users have access to in Looker.
- Model Level: Model Level limits what models users have access to. It also controls the database connections.
- Role Level: Role Level sets specific data and feature functionality that an individual has access to in Looker.
Understanding the Benefits of Looker
Looker brings your data together to give you a more expansive view of your company metrics, based on the belief that precise data brings the confidence to invest where it counts. This lets companies create better outcomes. On that note, here are a few benefits of Looker that make it an indispensable tool in the field of Business Intelligence:
- Optimized for the Cloud: Looker’s architecture leverages modern Cloud Databases’ performance and scalability. It doesn’t rely on data extracts and ensures that you don’t experience any unnecessary overhead or new points of failure in the data pipeline. This also avoids the security risk of replicating data on your user’s devices and in another vendor’s database. Its Multi-Cloud capability allows you to choose where to deploy Looker as well.
- Reliable: The Looker platform is designed to deliver the balance between self-service and governance. The layered architecture ensures that users of all technical levels can explore and interact with centralized and trusted data and analytics content.
- API Enabled Data Experiences: Looker utilizes customized integrations through its best-in-class SDKs, APIs, and developer tools. The platform can be used by the customers to build and deploy their own personalized end-to-end applications. It also offers customers the option of working with Looker’s pre-built applications like Web Analytics, and Sales Analytics for rapid time to value.
- In-Product Support: The platform prioritizes customer relationships and feedback over everything else. Looker ensures customers are provided personal attention by assigning exceptional personnel who care about solving customer’s specific issues.
- No Desktop Software Required: Looker provides an immersive browser experience that eliminates the need for desktop client software installation and maintenance. It allows for link-based sharing of content that makes collaboration frictionless.
Understanding the Working of Looker
Looker stands apart by going beyond Business Intelligence to help organizations deliver impactful solutions through data-driven experiences and insights that fit the way people work. Looker simplifies the creation of Dashboards and Reports while avoiding stale data and siloed approaches to enterprise logic with Enterprise-Class Business Intelligence. To tap into the value of your data and build a full spectrum of data experiences you need to have an idea about how Looker functions. Here is a brief outlook of the working of Looker:
- Connecting Data: Looker utilizes a Database or a Data Warehouse to store the data along with a plethora of connectors out of the box. A database connection is required for Looker to work. This is because Looker operates in a live mode using SQL queries instead of ingesting flat files like Excel sheets or CSVs.
- Modeling Data: Once the connections have been established and tested, the next step is to select the tables from the database you wish to work with, and define relationships. You can do this using LookML, the backend of Looker. This provides a Data Modeling layer where you can define the relationships, drill-down features, and add new variables.
- Data Collaboration: Looker enables parallel execution of operations, which speeds up how fast you can develop the base for Looker. LookML can be used by numerous teams and the work done in one project can be referenced by others easily.
- Data Visualization: After the completion of a version of the LookML model, you can start working on creating the visualizations. There are two ways to develop these: Looks and Dashboards. Looks are singular visualizations used to analyze data on an ad-hoc basis and share insights with the stakeholders. Looks are loosely used to refer to Reports in Looker. Dashboards allow multiple visualizations and KPIs (Key Performance Indicators) to be presented together.
Understanding the Looker Reporting Process
You can use Looker Reporting to drill down into your customer data and extract profitable, actionable insights that can be utilized to guide business decisions and steer business growth. In this section, you will get an idea about how to set up a report in Looker in 3 simple steps as follows:
Looker Reporting: Saving Looks
To save a Look in Looker carry out the following steps:
- Step 1: In the upper right section of the Explore page, click on the gear menu.
- Step 2: From the gear menu, choose Save as a Look.
- Step 3: When prompted, enter a new title in the Title field. If you are saving over an existing Look, the title can be left blank.
- Step 4: In the Description section, you can enter a description of the Look or Looker Report. You can leave this blank if you are saving over an existing Look.
- Step 5: In the Folder section, ensure that the current folder is the desired destination.
- Step 6: If you wish to change the destination, navigate to the folder where you wish to save your Look. You can follow the given steps to carry this out:
- In the Folder section, click on any parent folders to navigate to it.
- On the left side, you can click the name of a top-level folder to navigate to it.
- On the right side, click the name of a subfolder you wish to use or navigate to one of its folders.
- If there are multiple subfolders to choose from, you can type the subfolder name into Filter by Title to filter the list to that subfolder.
The Folder field shows the name and location of the chosen folder, while the right side displays the contents of the chosen folder. If you choose a folder in which you aren’t allowed to save the Look, an alert will be displayed in the pop-up box footer.
- Step 7: If you wish to save over an existing Look, you can use the Filter by Title field to find and select the desired Look.
- Step 8: You can save your Look by clicking on Save. If you wish to view the newly created Look, you can click Save and View Look. This marks the end of this component of the Looker Reporting process.
Looker Reporting: Editing Looks
Once you’ve created a Look, you can edit its name, underlying query, and decide if it should run automatically when loaded. You can edit a Look with the following steps:
- Step 1: Click Edit in the saved Look to start the process.
- Step 2: Go to the Edit Look page, and make any changes you want using Looker’s filters, fields, visualizations, and many more.
- Step 3: After you have made the desired changes, click on the Run button to update the Look.
- Step 4: The Save button is enabled once the Look has finished running. Click on the Save button to save your changes. This concludes this step of the Looker Reporting process.
Looker Reporting: Deleting Looks
There are two ways you can go about when deleting Looks:
- You can delete multiple Looks at once from a folder. You need to have the Manage Access, Edit access level for a folder. You first need to check the box to the left of the items you wish to delete in the folder. Click the Move to Trash button that appears above the list of Looks. Click OK in the confirmation window to end this process.
- You can delete a single Look directly from the gear menu found at the upper right of the screen. This concludes the deletion part of the Looker Reporting process.
Conclusion
This article covered Looker Reporting in great detail touching upon the benefits and working of Looker before diving into the process of setting up a Looker Report. The Looker Reporting process includes three key steps: saving, editing, and deleting Looks or Looker Reports.
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Amit is a Content Marketing Manager at Hevo Data. He is passionate about writing for SaaS products and modern data platforms. His portfolio of more than 200 articles shows his extraordinary talent for crafting engaging content that clearly conveys the advantages and complexity of cutting-edge data technologies. Amit’s extensive knowledge of the SaaS market and modern data solutions enables him to write insightful and informative pieces that engage and educate audiences, making him a thought leader in the sector.