A Complete Looker Tutorials
What Is And How Looker Works
Looker Tutorials
Some of the few technologies that businesses are implementing to better understand their customers are data analytics & business intelligence (BI). In this area, many solutions are developed to aid businesses in learning crucial customer insights. Looker is one of these tools. Looker is a business intelligence tool and big data analytics platform that enables organizations to quickly explore, examine, and share business insights. Looker employs Looker ML (LookML) to explain the connections between different database characteristics.
The language Looker utilizes to describe the dimensions and connections between different entities in a SQL database is called Looker ML. Understanding Looker ML is essential for figuring out the connections between various database entities and for creating the right SQL queries.
In this article, You will learn about Looker ML. Additionally, a brief overview of Looker’s features will be provided so that you may grasp how Looker uses Looker ML to extract insights from SQL databases.
What is Looker?
A cloud-based BI solution called Looker enables you to explore, share, and visualize data to help in the making of better business decisions. Now a part of the Google Cloud Platform, Looker. It enables everyone in your company to swiftly analyze and glean insights from your datasets. Building a data exploration platform with Looker is relatively simple and will provide your entire organization access to your data in a meaningful, user-friendly way.
Looker employs the Data Modelling Language (DML) and has a built-in framework. You may analyze data in a highly effective and beneficial way with Looker. Using Looker, you can quickly connect to many data sources and create custom dashboards, KPI dashboards, etc.
Looker offers tools to support a variety of data experiences, including contemporary BI and embedded analytics as well as integrating workflows and creating unique apps. Looker enables you to access the most recent version of your company’s data, no matter where it is stored. It is a one-stop shop for data management, analytics, visualization, and business intelligence.
The Architecture of Looker
Looker makes use of a Linux server as part of its database architecture. In Looker, numerous connections are made via the Linux server. Looker may be hosted by Looker itself or by a third party. Installation, configuration, and administration of Looker are handled by the Looker instance naturally when using a hosted instance of Looker.
Looker is made up of a variety of components, including the Analytics database, Linux, the internal database of Looker, user clients, as well as external communications. These elements are used to create connections.
The Looker is connected to the databases through the analytics database. SSL connections and SSH tunneling are used to provide encrypted communications and additional authentication to assure security. Both client and web-based access can employ authentication and user-based protocols.
Looker operates on a Linux server and runs on a Java runtime environment-based operating system. Through the use of a firewall or VPC (Virtual Private Cloud), security is enabled throughout the entire Looker deployment. There are established external communications that cover subscription management, looker usage, problem reporting, and Git integration. For big deployments and clustered configurations, the internal database of Looker uses My SQL. The looker program doesn’t get impacted by where the data is stored.
For the internal databases of the Looker program, you can use HyperSQL, which functions as an in-memory database by default. The database’s size can occasionally increase exponentially, which might cause problems with performance. Therefore, you should utilize a MySQL database rather than a HyperSQL database to overcome these problems. Place a cluster of Looker nodes close to the load balancer to further reduce Looker’s heavy traffic control.
What is a LookML?
Between the user and the database, LookML (Looker Modelling Language) creates abstracted SQL and offers a modeling layer. A layer of abstraction for SQL databases is offered by Looker’s proprietary language.
In a SQL database, LookML is a language used to describe dimensions, calculations, aggregates, and data relationships. Looker creates SQL queries for a specific database using a model described in LookML. Between the SQL database and the business user’s interactions with it, a layer is created.
As a result, it provides definitions for a wide range of concepts, including how to join tables, construct custom tables, define database fields, and specify the logic for new columns. You will gain practical familiarity with the foundations of LookML in this lab.
Features of Looker
Breaking Down Barriers to Insight
The ability of Looker to democratize data insights is its main competitive advantage. Traditional data analytics frequently needed expertise in technology, which put non-technical users at a disadvantage. Looker's straightforward, user-friendly interface removes this barrier. By using a range of filters, pivots, and drill-down tools, users may quickly and easily analyze complex datasets. This enables staff members from executives to marketers across your organization to find valuable information without the need for specialized training.
Building Better Data Products, Faster
In today's highly competitive business environment, time is important. Your teams can quickly create effective data products using Looker. You may quickly create reports, dashboards, and visual representations that are catered to your particular needs using its wide collection of pre-built templates and visualization options. You may create and share dynamic presentations using the platform's drag-and-drop interface without having to wait for conventional coding or development to finish.
Increasing Performance and Optimizing Costs
Looker's commitment to performance optimization is a significant advantage. Traditional analytics platforms often faced challenges with slow query response times, hindering effective decision-making. Looker, however, utilizes innovative caching and data modeling techniques to ensure lightning-fast query execution. This not only enhances user experience but also reduces the need for excessive hardware resources, optimizing costs and promoting efficiency.
Augmented Analytics for Proactive Insights
Looker's capabilities are characterized by augmented analytics that are driven by AI and machine learning. With the help of this tool, Looker can more effectively analyze your data by finding patterns, correlations, and anomalies on its own. You are given the ability to take prompt action based on predictive insights thanks to this proactive strategy. Additionally, Looker's capability to produce automated alerts and recommendations guarantees that you are always aware of any changes in your data, assisting you in staying one step ahead of any prospective obstacles or possibilities.
Embedded Analytics
Looker's embedded analytics feature lets you integrate data directly into your applications, websites, or portals. This empowers your customers or partners to interact with data in real time without needing to switch between different tools, enhancing the overall user experience.
Data-Driven Alerts and Notifications
Data-driven alerts and notifications are proactive feature that keeps you informed about important changes, trends, or anomalies in your data. Instead of continuously monitoring data manually, you can set up automated alerts that trigger notifications when specific conditions are met.
How does Looker work?
Looker is a tool that generates SQL queries and executes them against a database connection. Depending on the LookML project, which explains the connection between columns & tables in a database, generates SQL queries.
The procedures that follow describe how a Looker operates:
Viewing the Query
Looker provides users with transparency into the data retrieval process by allowing them to view the SQL queries generated behind the scenes. This feature is invaluable for those who want to understand the mechanics of their analyses or need to troubleshoot issues. By offering a window into the underlying queries, Looker fosters a deeper connection between users and their data, enabling them to grasp the intricacies of how information is extracted and transformed.
The Canonical Form of a Looker Query
The canonical form of a Looker query refers to the structured template that Looker employs to generate SQL queries. LookML, Looker's modeling language, plays a vital role in defining this canonical form. It outlines the dimensions, measures, filters, and joins that make up the query. This standardized format ensures consistency across queries and simplifies the data exploration process. Users can modify parameters within the canonical form to customize queries to their specific requirements, enhancing flexibility while maintaining a coherent structure.
Running Raw SQL in Looker’s SQL Runner
Looker’s SQL Runner offers users the flexibility to run raw SQL queries alongside Looker's canonical form queries. This feature caters to advanced users who possess SQL expertise and prefer to directly write and execute their own queries. Running raw SQL in Looker’s SQL Runner enables users to leverage the power of SQL to perform intricate calculations, complex joins, and other advanced data manipulations. By integrating this capability, Looker ensures that users with varying levels of technical proficiency can harness the platform effectively.
Exploring the URL’s query features
After running the SQL query, reading the URL will return the five essential elements. These features include a explore, model, fields to question along with display, sort and order fields, filter fields, and values.
Looker Applications
Business Intelligence and Reporting
Looker's main function is to provide organizations with a powerful business intelligence tool that they can use to build smart reports and visualizations. Businesses can combine data from several sources to get a cohesive picture of their operations. Decision-makers are empowered by Looker's interactive dashboards to track KPIs, monitor performance, and make wise decisions that will promote growth.
Sales and Marketing Analytics
Looker is a game-changer in terms of sales and marketing. It helps teams in comprehending client behavior, the success of marketing initiatives, and sales patterns. Looker's visualizations make it simpler to see opportunities, improve marketing tactics, and successfully craft campaigns for target audiences.
Web-based Analytics
The Looker application effortlessly transitions into the web-based analytics environment. Organizations can use Looker to get in-depth insights into metrics for engagement, user behavior, and website performance. Looker gives companies the ability to build detailed dashboards that display website traffic, conversion rates, click-through rates, and more by combining data from web analytics tools. With the help of this tool, digital teams may improve user experience, pinpoint areas for development, and make data-driven choices to boost their online presence.
Digital marketing analytics
Looker's capabilities are extremely useful in the quick-paced world of digital marketing. Looker gives businesses the ability to combine data from different digital channels, like social media, email marketing, and online advertising, into a single platform. Marketers can evaluate the effectiveness of their campaigns, keep tabs on important indicators, and comprehend customer journeys with Looker's visualizations and analytics. With the aid of this tool, marketing professionals are better equipped to hone ideas, allocate resources wisely, and produce audience-resonant campaigns that are focused and effective.
Career Opportunities in Looker
Organizations require effective tools that help in the analysis and visualization of data in the data-driven business world of today. One such platform that has grown significantly in popularity over the past few years is Looker, a potent business intelligence and data visualization tool. As a result, Looker has developed a variety of job opportunities for people who are proficient in the platform. In this blog, we’ll look at the various career options offered by Looker and the skills needed to succeed in them.
Looker Developer
Looker Developers are the architects of Looker's customization and integration. They leverage LookML, Looker's modeling language, to design and optimize data models, ensuring data accuracy and accessibility. Looker Developers collaborate closely with data engineers, data analysts, and other stakeholders to create tailored solutions that meet specific business needs. They possess a deep understanding of Looker's functionalities and are skilled in crafting LookML code to transform complex data into meaningful insights.
Looker Analyst
Looker Analysts are the storytellers who bridge the gap between data and decision-makers. These professionals have a keen eye for data trends and possess the ability to translate complex insights into actionable recommendations. Looker Analysts create compelling reports, dashboards, and visualizations using Looker's intuitive interface. They collaborate with various departments to ensure data-driven strategies and help drive business growth.
Business Intelligence Developers
Business Intelligence (BI) developers are the architects behind Looker's data models and structures. They create the foundation upon which analytics solutions are built. By designing and optimizing data pipelines, BI developers ensure data accuracy, availability, and performance, allowing organizations to make informed decisions with confidence.
Data Engineers
Behind the scenes, data engineers lay the groundwork for data analysis. They build and maintain the infrastructure required to gather, process, and store data. Looker's data modeling capabilities are enhanced by data engineers who ensure that the right data is accessible and available for analysis in a timely and efficient manner.
LookML Developers
LookML is Looker's proprietary language used to define and manage data models. LookML developers are adept at crafting Looker-specific code that defines relationships between data, dimensions, and measures. They empower organizations to create a cohesive and reliable data structure that supports accurate reporting and analytics.
Sales Engineer
Sales engineers are essential in demonstrating the benefits of Looker to new customers. These technologically competent individuals have a thorough understanding of Looker's features and functionalities, which enables them to effectively explain how the platform may solve particular business problems. Sales engineers collaborate directly with the sales team, giving technical knowledge, demonstrating products, and sharing knowledge about how Looker helps streamline clients' data analytics procedures. Their contribution to increasing consumer engagement and conversion is crucial.
What are the benefits of a looker?
Streamlined Data Exploration
Looker's data exploration capabilities are a game-changer. Users can navigate through vast datasets with ease, drilling down, pivoting, and filtering to extract meaningful information. This streamlined exploration process saves valuable time and effort, allowing users to focus on deriving insights rather than wrestling with complex queries.
Agility in Reporting and Analysis
Looker's agility in reporting and analysis redefines how organizations operate. The platform's drag-and-drop interface and pre-built templates accelerate the creation of customized reports and visualizations. This means teams can respond swiftly to changing business needs, delivering insights when they matter most.
Collaboration and Accessibility
Looker transcends silos and fosters collaboration. Stakeholders from various departments can access the same data, ensuring alignment and fostering a unified understanding. Moreover, Looker's embedding capabilities enable seamless integration of data insights into applications, websites, and portals, ensuring information is accessible wherever it's needed.
Data-Driven Alerts and Proactive Insights
Looker's data-driven alerts and notifications keep users ahead of the curve. Automated alerts, triggered by predefined thresholds or anomalies, ensure that important changes are promptly brought to attention. Looker's integration with machine learning augments this feature, enabling predictive insights that empower proactive decision-making.
Optimized Performance and Cost Efficiency
Looker's commitment to performance optimization translates to improved user experience and efficient resource utilization. Queries are executed swiftly, and response times are minimized, enhancing productivity. This optimization contributes to cost efficiency by reducing the need for excessive hardware resources.
Conclusion
Looker is undoubtedly a tool to keep an eye on for the functionality and durability that it offers. I hope you now have a basic understanding of Looker and its goal. This marks the conclusion of this blog. I hope it was enjoyable for you to read. You can post your questions in the comments section below if it has anything to do with this blog. We are more than happy to address them. Happy learning and thanks again!