Looker BI: A Beginner’s Guide to Smart Data Analysis with Use Cases

As the world becomes more and more dependent on data, it becomes increasingly important to be able to make sense of Business Intelligence. Meet Looker, a promising business intelligence (BI) platform that is revolutionizing the way companies engage with data. This comprehensive guide will help you understand what Looker is, how it works, the advantages and disadvantages of using it, and whether or not it can meet your business needs.

What is a looker?

Looker is a business intelligence and data analytics tool that runs in a browser to help companies understand their data. Founded in 2012 by an American company and purchased by Google in 2019, Looker is a BI platform within the Google Cloud environment.

What is Business Intelligence tools that demand data be loaded into their systems, Looker relies on what is known as the ‘extract, load, transform’ approach. Coupled with the intuitive interface and the robust analytical tools, Looker is an excellent choice in the highly competitive BI space.

Why should you consider Google Looker?

Google Looker offers several compelling advantages that make it a strong contender in the BI market:

• Reduced Time-to-Insight: Looker makes it easier to design dashboards and reports and minimizes the time taken to get from problem recognition to solution implementation.”
• Democratization of Data: Looker makes it easy for people who are not familiar with SQL to navigate through the data and build visualizations.
• Real-Time Data Access: Looker integrates with the data sources, so you are always working with the latest data.
• Scalability: Being a Google Cloud platform, Looker can readily handle the needs of companies that are in the process of expanding.
• Advanced Analytics Capabilities: Some of the features include predictive modeling and machine learning integration, which give more information that can be analyzed.

Deep dive into the Core Values of Looker as a Modern BI tool

Looker’s core values revolve around making data accessible, understandable, and actionable for all users within an organization. 

Key principles include:

• Data Governance: Looker focuses on data model management and security by having a single source of truth and a controlled way of accessing data.
• Self-Service Analytics: It thus allows users to search for data on their own and has less dependence on the IT department.
• Collaboration: Looker allows for real-time collaboration and sharing of insights so that the company can encourage a culture of data analysis.
• Flexibility: The tool is flexible, can work with different data structures, and can be configured to meet the needs of a business.

Looker Use Cases

Looker’s versatility makes it suitable for a wide range of industries and applications.

• E-commerce: To understand the buying habits of the customers, sales patterns, and managing the stock.
• Finance: controlling the main performance indicators, the evaluation of potential risks, and the prevention of fraud.
• Healthcare: It also summarizes the patient’s outcome, resources used in managing the patient, and compliance with the nursing care plan.
• Marketing: campaign performance tracking, segmentation of the customers, and the return on investment analysis.
• Manufacturing: This is the improvement of supply chain management, quality assurance and control, and production performance evaluation.

Pain Points Addressed by Looker BI

Looker addresses several common challenges faced by organizations in their data analytics journey:

• Data Silos: Looker connects data from different sources and does not allow the data to be stored in separate compartments.
• Slow Reporting: The availability of real-time data and easy-to-use interfaces enhance the time taken to produce reports.
• Limited Data Exploration: Looker’s model is fully self-service, which permits for greater levels of data analysis and customization.
• Inconsistent Metrics: Standardized data definitions help to avoid the differences in definitions that could be used across the organization.
• Scalability Issues: Cloud-based architecture provides a framework that can easily be expanded as the data size increases.

Target Personas for Looker BI

Looker caters to various roles within an organization:

• Business Analysts: sophisticated queries as well as the visualizations that can be created using the software, although the users can do it without much concentrating on the mechanics of the tool. For those looking to enhance their skills in this area, a comprehensive Business Analyst Course can be beneficial.
• Executives: Produce comprehensive summaries of the numerous and intricate sub-systems, accompanied by a clean and straightforward interface to enable the top officials to comprehend.
• IT Professionals: Altogether, Looker possesses quite a great set of security features and appearance, as well as possibilities to integrate with other systems.
• Marketing Teams: They include the ability to track the results of the campaign and the behavior of the customer in a real-time manner.

Looker Features that Redefine Business Intelligence

• LookML: LookML is a language that’s exclusive to Looker that can be used to build more operational, sustainable, and versioned data models.
• Explores: An interactive GUI for juicy data searching and data visualization generation.
• Drill-Down Functionality: Enables other users to analyze particular data points with greater precision by providing additional information on the subject.
• Embedded Analytics: System ability to integrate the Looker dashboards and/or visualizations into various applications.
• Data Actions: Allows users to invoke other workflows in other systems within Looker.

Integration of Looker BI in your existing Data Analytics

Incorporating Looker into your existing data analytics ecosystem can be a smooth process:

• Data Source Connections: Looker integrates with SQL data warehouses, other cloud data warehouses, and big data platforms.
• API Integration: Specific and strong APIs will enable the integration of the systems with other business systems.
• Single Sign-On: Click to support single sign-on because user information can be managed efficiently and security can be boosted.
• Custom Visualizations: Actively implemented capability of creating and incorporating special visualizations to solve certain problems.

The challenges of using the Looker business intelligence platform

While Looker offers numerous benefits, it’s important to be aware of potential challenges:

• Learning Curve: LookML and the approach that Looker has taken might just take teams some time to get up to speed with.
• Initial Setup Complexity: However, the setup and modeling of data are critical aspects in the sector that require a good approach in order to yield maximum results.
• Cost Considerations: Looker may be more expensive than some of the other comparable BI tools, although it is a quite advanced tool that is considered one of the best.
• Performance Tuning: Big data may also need certain enhancements for the best performance of analysis.
• Dependency on Data Quality: Similar to all the BI tools, Looker’s usage depends on the quality of data fed into the system.

These difficulties can be overlooked by a business willing to incorporate a powerful and effective Looker’s solution into its reporting arsenal. If you want to go further and have a deeper insight into business intelligence and its uses, you may want to consider Edureka’s comprehensive Business Intelligence Course. These programs can provide you with the skills and knowledge needed to excel in the data-driven business world.

Conclusion

Looker represents a significant evolution in the world of Business Intelligence tools. Its modern approach to data analytics, user-friendly interface, and powerful features make it a compelling choice for organizations looking to drive data-driven decision making. While there are challenges to consider, the potential benefits in terms of insights, efficiency, and data democratization are substantial.

As with any major technology decision, it’s essential to carefully evaluate Looker against your organization’s specific needs, existing infrastructure, and long-term data strategy. Consider a pilot project or proof of concept to fully understand how Looker can integrate with and enhance your current Business Intelligence platform. 

FAQ

Is Looker BI a Tool?

Yes, Looker is a Business Intelligence (BI) tool. It’s a software platform designed to help organizations analyze and visualize their data, create reports and dashboards, and share insights across the business. 

Is Looker better than Power BI?

The choice between Looker and Power BI depends on specific organizational needs. Looker excels in its data modeling capabilities and real-time data access, while Power BI is known for its user-friendly interface and tight integration with Microsoft products. Both are powerful BI tools with their own strengths.

Is Looker better than Tableau?

Looker and Tableau have different strengths. Looker’s in-database architecture and data modeling language (LookML) set it apart, while Tableau is renowned for its intuitive drag-and-drop interface and powerful visualization capabilities. The “better” tool depends on your specific requirements and use cases.

What is Looker tool used for?

Looker is used for a wide range of data analytics tasks, including:

• Creating interactive dashboards and reports
• Exploring and analyzing data from various sources
• Sharing insights across an organization
• Embedding analytics into other applications
• Predictive modeling and advanced analytics

By leveraging these capabilities, businesses can make more informed, data-driven decisions across all levels of the organization.