After purchasing Looker earlier in February 2021, Google changed the name of its “Google Data Studio” platform to “Looker Studio” last December. Google tools Looker and Looker Data Studio have a lot in common. Both of these BI tools are powerful and offer data analytics, integration, and visualization to help businesses overcome their difficulties.
“Looker” and “Data Studio” are both popular business intelligence and data visualization tools, but they have different features, capabilities, and use cases.
Here’s an overview of each:
What is a looker?
Looker is a platform for data exploration and analysis that enables businesses to examine, visualize, and interpret their data. Without extensive coding knowledge, users may generate interactive reports, dashboards, and data visualizations.
Looker’s main goal is to make it possible for everyone in an organization to make decisions based on data by offering straightforward tools for data access and analysis.
Here are some characteristics of Looker:
- Data Modeling:Looker’s data modeling capabilities allow you to transform raw data from multiple sources into a coherent model that business users can easily query.
- Custom Metrics:You can define custom metrics and dimensions based on your data model.
- SQL-Based:Looker’s interface heavily relies on SQL queries, making it suitable for users familiar with SQL.
- Collaboration:Looker supports collaboration through sharing and commenting on reports and dashboards.
- Embedding:You can embed Looker content into other applications.
What is Data Studio?
Google Data Studio is a free data visualization and reporting tool developed by Google. It allows users to create interactive and customizable reports and dashboards by connecting to various data sources and presenting the data visually appealingly.
Data Studio is designed to be user-friendly, enabling individuals and organizations to turn raw data into meaningful insights without needing advanced technical skills.
Here are some characteristics of Data Studio:
- Visual Design: Data Studio offers a user-friendly drag-and-drop interface for creating visualizations without the need for coding or complex data transformations.
- Google Integrations:It seamlessly integrates with various Google services like Google Analytics, Google Sheets, BigQuery, etc.
- Collaboration:Similar to Looker, Data Studio allows collaboration by sharing and editing reports in real time.
- Data Source Variety:While Looker supports various data sources, Data Studio is particularly well-suited for Google-related data sources.
- Customization:Data Studio provides customization options for branding and styling your reports.
- Embedding:You can embed Data Studio reports on websites or within other application
Feature Comparison: Looker vs Data Studio
|1.||Data Modeling and Transformation/integration:||LookML:
Proprietary language for defining data models and transformations.
Advanced data modeling:
Complex data modeling and transformation capabilities
|Seamless Google integration:
Easily connects to Google services like Google Analytics, Google Sheets, etc
Connects to other data sources through connectors like BigQuery and MySQL
|2.||Querying and Analysis:
Requires SQL proficiency for querying and analysis.
Custom metrics and dimensions:
Ability to create custom calculations based on the data model.
Drag-and-drop interface for building queries and reports, suitable for non-technical users.
Limited custom calculations:
Provides basic calculated fields but not as robust as Looker’s data modeling
|Offers a range of chart types and visualization options.
Integration with third-party visualization libraries.
|Offers a wide range of pre-built visualizations and options.
Provides options for customizing the appearance of charts and reports.
Users can collaborate on reports and dashboards.
Ability to add comments to reports for discussions
Multiple users can edit reports simultaneously.
Commenting and annotations:
Users can add comments to specific parts of the report.
|5.||Embedding and Sharing:
Reports and dashboards can be embedded in other applications or websites.
Reports can be shared with specific users or group
Reports can be embedded on websites or shared via links.
Google Drive integration:
Reports can be stored and shared through Google Drive.
|6.||Data Source Variety:
|Supports various data sources including databases, cloud storage, and third-party services.
|Supports various data sources, with a strong emphasis on Google services.
|Role-based access control:
Provides options for managing and controlling data access.
Data lineage tracking:
Ability to trace data sources and transformations
|Limited access control:
Basic sharing settings and permissions but not as advanced as Looker’s governance features.
Pricing Comparison: Looker vs Data Studio
|Pricing||Looker is an enterprise-grade tool that has a trial version.
For ten users, Looker will cost you around $ 3,000 to $ 5,000.
Even though this is an expensive tool, your investment won’t go to waste.
|It is an entirely free tool. All you need is a Google account.|
Which is better, looker vs data studio?
Choose Looker if you need significant data modeling to perform complex changes and if your users are proficient with SQL. If you want a simple-to-use product with solid Google connectors and a focus on visual design, pick Data Studio. Your choice should be in line with your organization’s technological proficiency, data complexity, need for collaboration, and integration demands.
Data Studio and Looker are two tools offered by Google that allow collaborative dashboards and visualizations. Although they do many of the same tasks, there are significant variations between them. For instance, while Looker is intended to provide a centralized source of truth for organizations with complex data models & built-in machine-learning capabilities, Data Studio meets basic BI needs. Additionally, it can function as a CDP that allows for the creation of comprehensive consumer profiles from online and offline sources.
Looker empowers users to alter their data unprecedentedly and in novel manners and transfer it into systems such as Analytics 360. The ability to work with LookML for schemas and modeling is an appealing feature; moreover, due to its high price and technical requirements in SQL knowledge, this application is only suitable for some. Looker may be the best option if you have complicated use cases that demand more than just basic analytics capabilities.