Looker - Detailed Review
Data Tools
Looker - Product Overview
Looker Overview
Looker, integrated within the Google Cloud ecosystem, is a comprehensive data platform that specializes in business intelligence, data applications, and embedded analytics. Here’s a brief overview of its primary function, target audience, and key features:
Primary Function
Looker’s main function is to provide a unified, governed, and real-time view of your business data. It enables organizations to access, analyze, and act on their data, facilitating data-driven decision-making across various departments and levels of the organization. Looker acts as a central hub for data insights, allowing users to build actionable data-driven workflows and create custom data applications.
Target Audience
Looker’s target market includes businesses of all sizes and industries, such as retail, healthcare, finance, and technology. It caters to organizations seeking advanced data analytics solutions to drive growth, innovation, and operational efficiency. The platform is particularly useful for enterprises looking to scale their data analytics capabilities and democratize data access across their organization.
Key Features
Data Modeling and Governance
Looker uses LookML (Looker Modeling Language), a SQL-based modeling language, to centrally define and manage business rules and definitions. This ensures consistent and governed data across the organization.
Real-Time Insights
Looker provides fast, proactive insights embedded in the places users work, enabling better business decisions through proactive alerts and deep integrations.
Enterprise-Class BI
The platform simplifies the creation of reports and dashboards, avoiding stale data and siloed approaches to business logic. It offers prebuilt integrations and robust APIs for customization.
Embedded Analytics
Looker allows for the seamless integration of fully interactive dashboards into applications, transforming data into value-driving experiences. It also integrates with Vertex AI for custom AI workflows.
Integration with Google Cloud
Looker is built on Google Cloud infrastructure, offering features like single sign-on with Google Cloud IAM, private networking, and seamless integration with BigQuery.
Self-Service Capabilities
Looker offers two main tools: Looker for governed data and Looker Studio for ad-hoc and interactive reports. This combination allows users to analyze both governed and ungoverned data effectively.
Overall, Looker is a versatile and scalable platform that helps organizations make the most of their data by providing a consistent, governed, and real-time data environment.
Looker - User Interface and Experience
User Interface of Google Looker
The user interface of Google Looker, particularly within the context of its AI-driven features and data tools, is crafted with a strong focus on ease of use and a positive user experience.
Customizable and Intuitive Interface
Looker offers a highly customizable interface that allows users to create and interact with data reports and dashboards in a user-friendly manner. The platform provides intuitive data exploration features, including a web-based interface where users can interact with data through simple point-and-click actions, creating custom queries, applying filters, and drilling down into datasets without needing extensive technical expertise.
Interactive Visualization Options
Users can leverage interactive charts and graphs that enable deeper exploration of specific data points. This interactivity is a key aspect of Looker’s design, ensuring that users can derive meaningful insights from the data presented.
Consistency and Simplicity
The UI adheres to basic UX design principles such as simplicity and consistency. The design language is uniform throughout the dashboards, avoiding clutter and ensuring that the data presented is easy to understand. This consistency helps in maintaining a clear and organized visual representation of data.
Real-Time Data Access and AI-Driven Insights
Looker integrates seamlessly with various data sources, providing real-time data access. This ensures that users are always working with the latest information, which is crucial for spotting trends, monitoring KPIs, and making strategic decisions. The integration with AI, such as Duet AI, enhances accessibility by allowing users to interact with data using conversational interfaces, making insights more accessible to a broader audience.
Feedback Mechanisms and Continuous Improvement
Looker has a system in place for gathering user feedback, which is crucial for continuous improvement. Users can submit feedback directly, vote on ideas, and see what features have been released recently and what is coming soon. This feedback loop helps in refining the interface and adding new features that align with user needs.
Integration with Other Tools
As part of Google’s ecosystem, Looker integrates smoothly with other Google services like BigQuery, Google Analytics, and Google Cloud. This integration ensures a smooth data flow and analysis, making it easier for businesses to consolidate and interpret their data across various platforms.
Component Library for Custom Applications
Looker’s component library allows developers to use Looker’s design elements and UI patterns through React components. This enables the creation of seamless experiences between Looker and custom-built applications, such as creating Looker-like UI for page navigation or dashboard filters within embedded Looker content.
Conclusion
Overall, the user interface of Google Looker is designed to be intuitive, customizable, and highly interactive, ensuring that users can easily explore and derive meaningful insights from their data. The emphasis on real-time data access, AI-driven insights, and continuous improvement through user feedback makes the user experience both engaging and effective.
Looker - Key Features and Functionality
Looker Overview
Looker, a cloud-based Business Intelligence (BI) and data analytics platform, offers a wide range of features that make it a powerful tool for data exploration, visualization, and collaboration. Here are the main features and how they work, including the integration of AI:Data Exploration
Looker allows users to connect to multiple data sources, providing a centralized hub for exploring both structured and unstructured data. Its user-friendly interface and drag-and-drop functionality enable users, including non-technical ones, to perform complex analyses without heavy reliance on IT teams.Data Governance and Security
Looker emphasizes data governance with features such as centralized access control, data permissions, and auditing capabilities. This ensures fine-grained role management, allowing for secure and controlled data access and sharing.Customizable Dashboards
Users can create and customize dashboards with various visualizations, from simple charts to interactive graphs. These dashboards can be aligned with specific business objectives, transforming raw data into actionable insights.Collaborative Environment
Looker fosters collaboration by enabling users to share insights, collaborate on analysis, and annotate data within the platform. This collaborative approach enhances communication and promotes data-driven decision-making across the organization.Embedded Analytics
Looker allows organizations to embed analytics directly into their existing workflows and applications, such as CRM systems or e-commerce platforms. This ensures that data-driven insights are readily accessible wherever they are needed.Alerting and Monitoring
The platform includes an alerting engine that enables users to set personalized thresholds for data metrics. Notifications are sent when these thresholds are reached or breached, allowing for instant reactions to changes with real-time monitoring.LookML Semantic Model
Looker uses LookML, a unique data modeling layer that translates database language into business language. This model follows software development best practices, such as DRY (don’t repeat yourself) principles, making data modeling more efficient.Integration with Google Cloud Platform (GCP)
As part of the Google Cloud Platform, Looker integrates seamlessly with other GCP services. This integration includes tools like BigQuery and Vertex AI, enhancing the platform’s capabilities in data analytics and AI.AI Integration
Generative AI and Duet AI
Looker has integrated generative AI capabilities, particularly through Duet AI, an AI assistant that streamlines analytics workflows. Duet AI uses powerful language models to auto-create explore queries based on natural language queries, summarize dashboard results, and provide analysis and guidance. This integration lowers technical barriers, enabling both technical and business users to perform complex analyses with less effort.Vertex AI Integration
The integration with Vertex AI allows for custom AI experiences, enabling organizations to develop custom data experiences and applications. This integration facilitates advanced machine learning capabilities, such as AI-powered visualizations and insights, and enhances the analytical capabilities of Looker.Natural Language Processing
Looker’s AI integration includes natural language processing capabilities for querying and report generation. Users can interact with data using natural language queries, making the analytics process more intuitive and interactive.Conclusion
In summary, Looker’s features combine to create a powerful BI platform that enhances data exploration, visualization, and collaboration, while the integration of AI technologies like Duet AI and Vertex AI further democratizes data analytics and streamlines complex analytical tasks. Looker - Performance and Accuracy
Performance Issues
Query Execution Time
One of the primary performance issues with Looker Studio is its query execution time. The platform has a 6-minute limit on handling queries, which can lead to slow loading times or timeouts for large data requests.Data Refresh Rates
The frequency of data refreshes can significantly impact performance. Adjusting the data freshness rate to longer intervals can speed up dashboard loading times by utilizing cached data instead of fetching it directly from the underlying data set.Extract Data Connector
Using the Extract Data connector can improve performance by caching subsets of data, making it faster to load reports compared to using live connectors. However, this requires periodic updates to maintain data freshness.Accuracy and Data Handling
Data Blending Limitations
Looker Studio has limitations in blending data from different sources, particularly with large datasets. It restricts the number of rows that can be displayed, which can lead to inaccurate data analysis due to limited input on the screen.Real-Time Updates
Looker Studio does not support real-time dashboard updates. Data is often cached, and manual refreshes are required, which can delay insights and make it less ideal for monitoring current trends.Customization and Visualization
The platform lacks options for complex data visualizations and has limited custom design options, which can be frustrating for users seeking advanced formatting and dashboard preferences.User Interface and Experience
UI Responsiveness
Users often report UI bugs and hiccups, especially when handling massive datasets, which can slow down progress and impede workflow.Learning Resources
The lack of adequate learning resources and online BI guides makes the learning curve steeper, which can be challenging for new users.Optimization and Best Practices
Query Performance Metrics
Looker provides tools like the Query Performance Metrics Explore to help identify and address query performance challenges. This includes recommendations for optimizing dashboard settings, reducing the number of tiles and merged queries, and using features like persistent derived tables (PDTs) to simplify complex SQL logic.Aggregate Awareness
Using aggregate awareness in Looker can significantly speed up queries by creating smaller aggregate tables that act as summary tables, reducing the need to query large tables directly.Areas for Improvement
Customer Support
Many users, especially those using the free version, complain about limited customer support access and slow response times from the development team.Data Connector Limitations
The limitations in data connectors, such as the inability to handle gigantic files efficiently, can be a significant drawback for large-scale firms and businesses. In summary, while Looker Studio is a capable data visualization tool, it faces several performance and accuracy challenges, particularly with large datasets and real-time updates. Optimizing query performance, adjusting data refresh rates, and using features like the Extract Data connector can help mitigate some of these issues. However, the platform’s limitations in data blending, customization, and real-time updates may necessitate considering alternative tools for more demanding use cases. Looker - Pricing and Plans
The Pricing Structure of Looker
The pricing structure of Looker, a business intelligence and data analytics platform, is segmented into several key components and tiers. Here’s a detailed breakdown:
Platform Pricing
Looker’s pricing is divided into two main categories: platform costs and user licenses.
Platform Editions
Looker offers three primary platform editions, each with different features and capacities:
Standard Edition
- This tier is suitable for small organizations or teams with fewer than 50 users.
- It includes one production instance, 10 Standard Users, and 2 Developer Users.
- Features include up to 1,000 query-based API calls and 1,000 administrative API calls per month.
Enterprise Edition
- Designed for larger organizations needing advanced security and extensive analytics capabilities.
- Includes one production instance, 10 Standard Users, and 2 Developer Users.
- Provides up to 100,000 query-based API calls and 10,000 administrative API calls per month.
Embed Edition
- This tier is for deploying and maintaining external analytics and custom applications at scale.
- Includes one production instance, 10 Standard Users, and 2 Developer Users.
- Offers up to 500,000 query-based API calls and 100,000 administrative API calls per month.
User Licensing
In addition to the platform costs, there are fees for licensing individual users:
- Viewer: $30 per user per month
- Standard User: $60 per user per month
- Developer User: $125 per user per month
Pricing Models
The costs for the different editions are not explicitly listed on the public website, but here is what is known:
- Annual Commitments: For all editions (Standard, Enterprise, and Embed), you need to contact sales to identify a solution that works for your organization. Annual subscriptions are available in one, two, and three-year terms.
- Monthly Costs: The Standard tier starts at $5,000 per month, while the Enterprise and Embed tiers require custom annual contracts through the sales team.
Free Options
There is no free version of the full Looker platform, but it’s worth noting that Google offers a free service called Looker Studio (formerly Google Data Studio), which allows limited data integration from various Google services. However, this is not the same as the full Looker platform and has significant limitations in terms of data sources and features.
Looker - Integration and Compatibility
Integrations with Other Tools
Looker integrates with numerous external data sources and applications, including marketing automation platforms, customer relationship management (CRM) systems, social media platforms, and more. Some notable integrations include:- Google Analytics: Allows for the import and analysis of web analytics data.
- Salesforce: Enables the integration of CRM data for comprehensive customer insights.
- Zendesk: Integrates customer support data for a holistic view of customer interactions.
- Github: Connects with version control systems to track development metrics.
- Google Sheets: Facilitates data import and export between spreadsheets and Looker.
Google Cloud Integrations
As a Google Cloud product, Looker has deep integrations with various Google services:- BigQuery: Allows for the analysis of large datasets stored in BigQuery.
- Cloud SQL: Supports connections to Cloud SQL for MySQL and PostgreSQL.
- Cloud Storage: Enables data import and export from Cloud Storage.
- Google Drive: Integrates with Google Drive for seamless data sharing.
- Google Maps: Can be used for geospatial data analysis.
- Google Sheets: Facilitates real-time data synchronization with Google Sheets.
Compatibility Across Platforms
Looker’s compatibility varies depending on the instance type and network configuration:Instance Types
- Looker (Original) vs. Looker (Google Cloud core): While the interface and functionality are similar, there are differences in administrative functions, database dialects, and feature availability. For example, Looker (Google Cloud core) instances manage some settings through the Google Cloud console rather than the Looker Admin section.
Network Configurations
- Public, Private, and Public & Private IP: Looker (Google Cloud core) instances can be configured with different network settings. For instance, private IP connections may require additional configuration to connect to external resources, and some features like the Looker Action Hub are not available on private network connections.
Device Compatibility
- Mobile Access: Looker is accessible through the Looker Studio mobile app, allowing users to view and interact with data on mobile devices.
Setting Up Integrations
To set up an integration in Looker, you typically need to:- Connect your data sources to Looker.
- Select and configure the desired integration from the Looker Admin panel.
- Map data, schedule updates, and set up notifications as needed.
Technical Expertise and Support
While setting up and maintaining Looker integrations can require technical expertise, businesses without dedicated IT teams can outsource these tasks to third-party providers or invest in training their staff. Additionally, Looker offers various security features such as encryption, access controls, and audit logging to ensure data security.Specialized Integrations
Looker also supports specialized integrations, such as with Microsoft Viva Goals, which enables automated real-time tracking of objectives and key results (OKRs). This integration allows users to link their OKRs to Looker dashboards and looks, ensuring that progress is updated automatically. In summary, Looker’s integrations are designed to be flexible and scalable, allowing businesses to access and analyze data from multiple sources in one place, while ensuring compatibility across various platforms and devices. Looker - Customer Support and Resources
Looker Support
Accessing Support
- Looker Support is accessible through the Google Cloud console, providing 24/7 support in English, 5 days a week (Sunday 5:00 PM PST – Friday 5:00 PM PST), and specific hours for Japanese language support.
- Support is available only for Looker instances running officially supported versions. For customer-hosted instances, ensuring the Google Cloud Project number is filled in on the Admin General Settings page is necessary to connect the instance to the Google Cloud support plan.
- Users must have the Tech Support Editor IAM role to access support, focusing assistance on the most involved users who need in-depth help.
Service Level Agreements (SLAs)
- Looker Support details include service level agreements (SLAs) that outline the response times and support coverage. These can be found on the Looker Technical Support Services Guidelines page.
Additional Resources
Looker Marketplace
- Looker Marketplace: This platform offers a variety of applications, blocks, and custom plug-ins to enhance data analytics. Users can find pre-built code blocks, custom visualizations, and integrations with other services like Google Cloud and contact center solutions.
Looker Studio
- Looker Studio: A free tool that allows users to create fully customizable reports and interactive dashboards with access to over 1,000 data sources. Looker Studio Pro offers additional enterprise capabilities and technical support.
Documentation and Guides
- Documentation and Guides: Comprehensive documentation is available on the Google Cloud Looker docs page, including best practices, product variations, and detailed guides on how to use Looker and its features.
Real-Time Assistance
- For real-time collaboration, Looker support can be accessed through Slack and Teams, providing prompt and responsive assistance without the need to open separate ticketing systems.
By leveraging these support options and resources, users can ensure they are getting the most out of Looker’s features and resolving any issues efficiently.
Looker - Pros and Cons
Advantages of Looker
Intuitive Data Exploration and User-Friendly Interface
Looker offers a user-friendly interface that allows users to explore data visually and interactively. Its drag-and-drop functionality makes it easy for both technical and non-technical users to perform complex analyses without heavy reliance on IT teams.Data Modeling and Transformation
Looker’s unique modeling layer enables organizations to define their data relationships and calculations, ensuring data consistency and accuracy. This feature allows users to create customized metrics and dimensions, which is crucial for data-driven decision-making.Integration with Google Cloud Platform
Being part of the Google Cloud Platform, Looker benefits from scalability, data integration capabilities, AI and machine learning services, enhanced security and governance, and reliable infrastructure. This integration also includes seamless connections with other Google services like BigQuery, which enhances data analytics capabilities.Collaborative Environment
Looker fosters collaboration among teams by allowing users to create and share interactive dashboards, reports, and visualizations. This shared data experience enhances transparency and aligns different stakeholders based on data insights.Embedded Analytics
Looker seamlessly integrates with existing workflows and applications, enabling organizations to embed analytics directly into their products or customer-facing portals. This feature provides real-time insights to customers and partners, enhancing the user experience.Comprehensive Data Integration
Looker, particularly through Looker Studio, allows users to connect to a wide variety of data sources, including Google Analytics, Google Ads, Google Sheets, SQL databases, and flat files like CSVs. This integration simplifies analysis and helps in drawing more comprehensive insights.Real-Time Insights and AI-Powered Analytics
Looker delivers real-time insights and leverages AI to accelerate analytical workflows, such as visualization creation, formula creation, and data modeling. The integration with Vertex AI enables powerful custom AI workflows and advanced analytics.Disadvantages of Looker
Cost
Looker is a premium BI tool with a pricing model based on personalized quotations, which may not be suitable for small businesses or startups with limited budgets. Organizations need to carefully evaluate their requirements and compare pricing options before committing to the platform.Customization Complexity
Advanced customization in Looker often requires expertise in LookML, Looker’s proprietary modeling language. This can limit the ability of users without programming skills to create complex data models or calculations, potentially necessitating additional training or external assistance.Limited Offline Access
Looker requires an internet connection to access data, which can be a disadvantage for remote work or situations where internet connectivity is unreliable.Performance Issues
The software can experience performance issues, such as slow loading times when running larger queries. Users may need to divide some views multiple times for proper functioning.Declining Customer Support
Some users have reported that the support team seems unfamiliar with the tool and often shares articles that users already know, indicating a decline in customer support quality.Limited Interface Customization
The new interface for switching between read-only and developer modes is not as user-friendly as the older version, according to some users. By considering these points, you can make an informed decision about whether Looker aligns with your organization’s needs and capabilities. Looker - Comparison with Competitors
When Comparing Looker to Other AI-Driven Data Analysis Tools
Several key features and differences stand out:
Customizable Dashboards and Data Exploration
Looker is renowned for its customizable dashboards and its ability to seamlessly connect to various data sources, allowing users to explore both structured and unstructured data effectively. This is similar to tools like Tableau and Microsoft Power BI, which also offer advanced data visualization and exploration capabilities. However, Looker’s integration with Duet AI enhances its analytics capabilities by providing real-time insights and recommendations based on natural language queries.
Augmented Analytics
Looker’s use of Duet AI sets it apart by offering augmented analytics that include identifying trends, spotting anomalies, and predicting outcomes. This is comparable to IBM Cognos Analytics, which also uses AI-powered automation and insights, including automated pattern detection and natural language query support. However, Looker’s Duet AI is more tightly integrated with Google Cloud services, such as Vertex AI and BigQuery, which can provide more customized and interactive data experiences.
Collaboration and Integration
Looker facilitates efficient collaboration by enabling users to share insights, collaborate on analysis, and annotate data using both visualizations and natural language queries. This collaborative approach is also seen in tools like Domo, which supports the creation, training, and integration of AI models and includes an intelligent chat for querying data. However, Looker’s integration with Looker Studio (formerly Data Studio) allows for a simpler, more accessible data visualization tool that can connect to Looker models, making it a unique offering in the market.
User Interface and Accessibility
While Looker is a fully-fledged platform with advanced features, it can be more complex for new users. In contrast, tools like AnswerRocket and Tableau are designed to be more user-friendly, especially for those without extensive data backgrounds. AnswerRocket’s natural language querying makes it easy for business users to get insights quickly, and Tableau’s AI capabilities, such as Tableau GPT and Tableau Pulse, make data analysis more intuitive and accessible.
Cost and Scalability
Looker, like some of its competitors, can be costly, especially for premium features. Microsoft Power BI, for example, can become expensive with its premium features, and IBM Cognos Analytics can be prohibitively expensive for small to mid-sized companies. However, Looker’s scalability and ability to handle large datasets make it a strong choice for larger organizations. Domo also scales well but includes an AI service layer that helps streamline data delivery and insights, which might be more cost-effective for some users.
Unique Features and Alternatives
- Looker’s Integration with Google Cloud Services: Looker’s integration with Vertex AI and BigQuery BQML allows for advanced visualizations and insights generation using generative AI, which is a unique feature compared to other tools.
- Alternatives: For users looking for a more user-friendly interface, Tableau or AnswerRocket might be better alternatives. For those already integrated with Microsoft products, Microsoft Power BI could be a more seamless choice. If cost is a concern and a simpler data visualization tool is needed, Looker Studio or Domo could be considered.
Conclusion
In summary, Looker stands out with its customizable dashboards, augmented analytics through Duet AI, and strong integration with Google Cloud services. However, the choice between Looker and its competitors depends on the specific needs of the organization, including user experience, cost, and the level of complexity desired.
Looker - Frequently Asked Questions
What is Looker and what primary purpose does it serve in Business Intelligence?
Looker is an enterprise platform for business intelligence, data applications, and embedded analytics. It helps organizations explore and share insights in real time by integrating data from various sources and providing a unified interface for analysis. Looker’s primary purpose is to enable in-depth data analysis, integrate insights from diverse data sources, and drive actionable, data-driven workflows and custom data applications.
How does Looker handle data from multiple sources?
Looker seamlessly connects to various data sources, allowing users to explore both structured and unstructured data through a unified interface. This capability enables users to analyze complex datasets effectively and ensures that the data is fresh, consistent, and governed in real-time.
What are the key features of Looker’s dashboards?
Looker’s dashboards are highly customizable, allowing users to create visualizations and reports that align with their specific business objectives. These dashboards can include simple charts, interactive graphs, and other visualizations. Additionally, Looker’s dashboards are integrated with AI capabilities, such as Duet AI, which provides real-time insights and recommendations based on natural language queries.
How does Looker facilitate collaboration among users?
Looker enhances collaboration by enabling users to share insights, collaborate on analysis, and annotate data using both visualizations and natural language queries. This collaborative approach promotes knowledge sharing and decision-making across teams, driving greater alignment and consensus within the organization.
What is the role of AI in Looker?
Looker leverages AI, particularly through its integration with Duet AI, to augment its analytics capabilities. Duet AI provides real-time insights and recommendations, helps identify trends, spot anomalies, and predict outcomes. Additionally, Looker’s AI assistant accelerates analytical workflows, including the creation and configuration of visualizations, formula creation, and data modeling.
How does Looker ensure data governance and consistency?
Looker’s trusted modeling layer provides a single place to curate and govern the metrics most important to your business. This ensures that users see consistent results regardless of where the data is consumed. The platform also integrates with Google Cloud’s secure ecosystem, offering features like SSO with Google Cloud IAM and private networking.
What are the different user roles and their associated costs in Looker?
Looker offers various user roles, each with different capabilities and costs. These include:
- View User: Can view, filter, and schedule pre-made reports ($400 per year).
- Standard User: Can query modeled data, drill down, and create content ($799 per year).
- Dev/Admin User: Can build and administer the data model ($1,665 per year).
How much does Looker cost?
The pricing for Looker varies based on several factors, including the number of users, database connections, and the scale of deployment. The starting price is around $35,000 per year, but there are different tiers such as Standard, Advanced, and Elite, with costs ranging from $66,600 to $198,000 per year for the platform, depending on the features and scale.
Can users without SQL knowledge use Looker?
Yes, Looker’s user interface generates SQL queries automatically, allowing users to access and analyze data without needing to know the underlying data structure or SQL. This makes it accessible to a broader range of users within an organization.
How does Looker support embedded analytics?
Looker goes beyond just placing dashboards in apps; it transforms data into deeply integrated, value-driving experiences. Fully interactive dashboards can be seamlessly integrated into applications, and the robust API coverage allows for extensive customization and integration with other tools, including Vertex AI.
What is Looker Studio and how does it differ from the main Looker platform?
Looker Studio is a free, fast, and easy-to-use tool that offers interactive, collaborative, and ad hoc reports and dashboards. It allows access to over 800 data sources and connectors and features a flexible drag-and-drop canvas for ad hoc analysis on both governed and unmodeled data. This contrasts with the main Looker platform, which is more focused on enterprise dashboards and governed data.