Choosing the right tool for business intelligence and data analysis is crucial for organizations looking to leverage their data effectively. Google Looker and SQL represent two different approaches to data exploration and reporting.
Google Looker offers a modern business intelligence platform with an intuitive interface, while SQL is the traditional language for managing and querying relational databases. Both have their strengths and use cases.
This page will compare Google Looker and SQL, detailing their functionalities, ease of use, and how they fit into the data analytics workflow. We'll also explore how Sourcetable provides a modernized, spreadsheet-like interface that syncs with your data as an alternative to using Google Looker or SQL for business intelligence tasks like reporting and data analytics.
Google Looker is a business intelligence platform developed by Google Cloud. It facilitates users in accessing, analyzing, and utilizing their data for business decisions. As a self-service and governed BI platform, it offers a secure and systematic approach to managing data.
Google Looker is a business intelligence platform developed by Google Cloud. It facilitates users in accessing, analyzing, and utilizing their data for business decisions. As a self-service and governed BI platform, it offers a secure and systematic approach to managing data.
Google Looker supports businesses in making informed decisions by offering a platform that is both user-friendly and comprehensive. With its advanced features, organizations can harness the power of their data effectively.
Real-Time Data Access |
Looker offers a fresh, consistent, and governed view of data, ensuring that users have access to real-time insights. |
Integration and Accessibility |
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Data Management and Modeling |
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Enterprise Intelligence |
Provides enterprise-class business intelligence, with features tailored for comprehensive data analysis and reporting. |
Proactive Insights |
Enables proactive insights, allowing users to stay ahead of trends and make informed decisions promptly. |
Multi-Cloud Support |
Accesses data from multiple clouds, offering flexibility in data management across various cloud services. |
Collaboration and Governance |
Allows analysts to centrally define business rules and KPIs, promoting consistency and governance across an organization. |
Extended Functionality |
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Google Cloud Integration |
As a core product of Google Cloud, Looker benefits from the reliability and scalability of Google's infrastructure. |
Data Definition Language (DDL) |
DDL allows for the creation, alteration, and removal of database schemas, tables, and other objects. |
Data Manipulation Language (DML) |
DML is used for inserting, updating, deleting, and retrieving data within a database. |
Query Language |
SQL functions as a query language, enabling users to perform queries to retrieve specific data. |
Transaction Control |
This feature ensures the management of database transactions to maintain data integrity. |
Data Integrity |
Data integrity is enforced in SQL databases through constraints and rules that safeguard the accuracy and consistency of data. |
User Access Control |
SQL provides mechanisms to manage user permissions and control access to database objects. |
Portability |
SQL is portable across various database systems, allowing for interoperability and flexibility in database management. |
Client-Server Execution and Remote Database Access |
SQL supports client-server execution and remote access, enabling distributed database interactions. |
Security and Authentication |
SQL includes features for robust security and authentication, protecting data against unauthorized access. |
Embedded SQL |
SQL can be embedded within other programming languages to create database-driven applications. |
Transaction Control Language (TCL) |
TCL is a subset of SQL that deals with transaction management within databases. |
Advanced SQL Features |
SQL offers advanced features for complex operations, including recursive queries, decision support, and data mining. |
Looker Studio Pro enables in-depth data exploration, aiding businesses in answering complex questions. The tool's robust capabilities allow for the creation of detailed visualizations, facilitating a deeper understanding of data.
The platform is designed for team collaboration, allowing for efficient management of team content. This feature streamlines workflows and improves productivity across medium and large scale enterprise environments.
With access to enterprise support, users can resolve issues promptly, ensuring minimal downtime. Looker Studio Pro's enterprise capabilities cater to the scalability needs of growing businesses.
Looker Studio Pro excels at sharing dashboards and insights, making it an effective tool for reporting and data analytics tasks. It simplifies the dissemination of business intelligence across an organization.
Users experience a lack of connectivity options which hampers smooth integration. Migrating data, especially from AWS to BigQuery, has been reported as a painful process.
Google Looker's interface is not very intuitive, leading to a complicated sharing mechanism. Additionally, the platform's performance issues, such as being slow and laggy, particularly with multiple graphs on a single page, detract from the user experience.
Both new and some existing users find Looker to have a steep learning curve. This complexity is compounded by the scarcity of readily available training materials and documentation.
Support in Japanese is available from 9:00 AM JST to 5:00 PM JST, Monday through Friday, and from 5:00 PM JST to 9:00 AM JST, Monday through Saturday, including weekends and holidays.
Ensure your Looker instance is running an officially supported version. Instances hosted by Looker automatically update, but customer-hosted instances must manually update to a supported version. Additionally, for original Looker instances, the Google Cloud Project number must be entered in the Admin General Settings page.
Looker Support is available to users with the Tech Support EditorIAM role and to administrators and developers on instances using Legacy Support.
Looker Support is available 24/7 only in English.
Before submitting a support request, you may be prompted to choose from a product area.
Reducing client report time for marketing services
Modernizing business intelligence for sports organizations
Embedding analytics in a quote-to-revenue platform
SQL's capability to manage and query databases is integral to business intelligence (BI). Its use in data analytics and reporting simplifies complex data operations.
SQL's capability to manage and query databases is integral to business intelligence (BI). Its use in data analytics and reporting simplifies complex data operations.
SQL streamlines data management, essential for accurate BI outcomes. It provides a robust foundation for data operations.
With SQL, data professionals can perform sophisticated data analytics, crucial for informed decision-making in BI.
SQL's precision in querying databases ensures the reliability of reports, a core aspect of business intelligence tasks.
SQL's role in web development enables seamless integration of BI tools within web applications.
As a must-have skill for data professionals and developers, SQL's ubiquity ensures a broad support community for BI tasks.
SQL's complex interface can pose challenges for users, leading to a steep learning curve and hindering efficient data interaction.
The expenses associated with SQL systems can be significant, including licensing fees and infrastructure costs, impacting budget allocation.
SQL's rigid schema requirements restrict the agility to adapt to changing data types and structures, potentially slowing down data-driven decision-making.
SQL databases often lack the capability for real-time analytics, which is crucial for timely business insights and actions.
When handling large datasets, SQL may experience performance bottlenecks, affecting the speed and efficiency of data retrieval.
The complexity involved in setting up and managing SQL systems requires specialized skills, which can lead to increased operational overhead.
SQL stands for Structured Query Language.
A query is a request for data from a database.
The four types of relationships in SQL are one-to-one, one-to-many, many-to-one, and many-to-many.
DELETE is used to delete records from a table, while TRUNCATE is used to delete all the records from a table and remove all constraints, relations, and access privileges.
ACID stands for Atomicity, Consistency, Isolation, Durability.
Querying and analyzing sales data to optimize business strategies
Combining data from multiple sources to gain comprehensive business insights
Conducting customer behavior analysis to improve marketing efforts
Performing financial analysis to guide budgeting and investment decisions
Generating data-driven recommendations to support executive decision-making
Sourcetable streamlines the process of reporting and analytics by consolidating data from multiple services into an intuitive spreadsheet interface. This simplification removes the complexity involved with Google Looker's BI platform and the technicality of SQL queries.
Unlike Google Looker, which requires a structured approach to data analysis, Sourcetable offers seamless syncing across various services. This functionality ensures that users have up-to-date information without the need for embedded data modeling.
The spreadsheet-like interface of Sourcetable is more accessible compared to the governance-heavy environment of Google Looker and the coding prerequisite of SQL. This eases the learning curve for users seeking to perform self-service business intelligence.
Sourcetable's efficient design allows for quick setup and immediate action on data, bypassing the often extensive process of building workflows and applications as required when using Looker or creating SQL databases.
Both Google Looker and SQL enable users to access and analyze data. They provide the functionality to query datasets, allowing for the extraction of insights and information necessary for business intelligence.
Google Looker offers embedded data modeling, similar to the way SQL is used to define data structures and relationships. Both can be used to create models that represent business logic and data relationships.
Both platforms are utilized for organizational business intelligence and self-service business intelligence. They enable users to create reports, dashboards, and data visualizations for business analysis.
Google Looker is a business intelligence platform that provides self-service and governed BI, while SQL is a language used for managing and querying data in databases. Looker offers a comprehensive suite of BI capabilities, including the ability to access, analyze, act on data, and deliver trusted data experiences.
Looker allows users to build data-powered applications and workflows, whereas SQL does not inherently provide this functionality. Embedded analytics and data modeling are also features of Looker, extending its use beyond traditional data querying.
Google Looker incorporates generative AI features and enables users to chat with business data, offering an interactive experience. SQL, by contrast, is a query language that does not have built-in AI capabilities or interactive chat functions.
Looker can be applied across various use cases such as organizational BI, self-service BI, and embedded analytics. SQL is primarily a tool for data manipulation and retrieval, rather than a comprehensive BI solution.
Business intelligence platform offering both self-service and governed BI.
Enables building of data-powered applications.
Features generative AI capabilities.
Provides access to analyze and act on data.
Delivers trusted data experiences.
Suitable for embedded analytics and data modeling.
Supports organizational and self-service business intelligence.
Allows users to build workflows, applications, and chat with business data.
Structured Query Language (SQL) is used for managing and manipulating relational databases.
Sourcetable is a tool that allows for querying and visualization of data using SQL.
Lacks native generative AI features inherent to the tool itself.
SQL is primarily used for data access and analysis, not for building applications.
Sourcetable facilitates data analysis but may not provide the same level of data experiences as Looker.
While SQL can be used for analytics, it is not specifically designed for embedded analytics or data modeling within applications.
SQL is essential for database management but does not inherently offer business intelligence solutions.
Lacks capabilities to build workflows or chat with business data without integration of additional tools.
Google Looker and SQL with Sourcetable serve different purposes in data management and analysis. Looker is a comprehensive BI platform that integrates various functionalities including AI, application development, and data experience delivery. In contrast, SQL is a fundamental language for database operations, and when used with Sourcetable, it focuses on querying and visual representation of data. Looker's broader scope in BI and application building contrasts with the more singular focus of SQL on data manipulation and Sourcetable's emphasis on visualization. However, both enable data analysis and support decision-making processes.
Sourcetable is a spreadsheet application that allows users to access data from most 3rd party applications, query data, and build live models. It is used by growth teams and business operations teams, and is ideal for those needing to centralize, analyze, and model data that updates over time without requiring coding.
Sourcetable syncs data from over 100 applications and most databases. Data integrations update every 15 minutes on the regular plan and every 5 minutes on the pro plan.
Sourcetable offers a starter plan at $50 per month and a pro plan at $250 per month. All plans come with a 14-day free trial.
No, Sourcetable does not require any coding skills to use.
Additional users can be added to a Sourcetable plan for $20 per month per seat.
Looker's pricing model is composed of two primary elements: platform pricing and user pricing. Platform pricing is a fixed cost for maintaining a Looker instance, which encompasses platform administration, integrations, and semantic modeling features. User pricing, on the other hand, is variable and depends on licensing individual users to access the Looker platform.
Platform pricing is the foundational cost for running a Looker instance. It includes essential services such as platform administration capabilities, integration options, and tools for semantic modeling. Each instance has its own billing account, which accrues charges based on the creation of instances and addition of named users.
User pricing varies according to the type of user and their permissions on the Looker platform. Looker offers three distinct types of licenses: Developer User, Standard User, and Viewer User, each tailored to different levels of platform engagement and responsibilities.
Looker provides three platform editions: Standard, Enterprise, and Embed. The cost associated with these editions depends on the user type and permissions. Subscriptions to these editions are available in one, two, or three-year terms, offering flexibility in commitment duration.
All charges incurred from the operation of a Looker instance or the addition of users are billed to the instance's attached billing account. This streamlined approach ensures centralized management of costs associated with the Looker platform.
The SQL Server 2022 comes in multiple editions with varying costs:
Developer and Express editions of SQL Server 2022 are available at no cost:
Annual licensing options provide a cost-effective alternative:
For flexible billing, monthly and hourly rates are available:
Google Looker, a business intelligence (BI) and analytics platform, has received mixed feedback from users. While some users utilize it for their data analysis needs, there is a notable amount of criticism regarding its performance and usability.
When compared to other tools, both free products like Data Studio and paid ones such as Tableau, users find these alternatives to be superior to Looker. The feedback suggests that these competitive products offer better functionality and user experience.
The insights on Looker's performance are drawn from user reviews and ratings, although specific sources of these reviews are not provided.
Codecademy's SQL offerings have been positively received by users with specific interests in finance. The available reviews underscore the value of the SQL Queries course, which is offered for free. This course has been especially noted for its ability to help learners initiate their journey into the realm of SQL without any financial commitment.
Codecademy's SQL offerings have been positively received by users with specific interests in finance. The available reviews underscore the value of the SQL Queries course, which is offered for free. This course has been especially noted for its ability to help learners initiate their journey into the realm of SQL without any financial commitment.
Users have highlighted the affordability of Codecademy's comprehensive SQL courses. The low-cost SQL course tailored for finance professionals is frequently mentioned in reviews, emphasizing its practicality and relevance in the financial job market.
Codecademy's SQL course has been cited as a significant advantage for those pursuing finance careers. Reviews often point out that the knowledge gained from this course has been instrumental in advancing users' professional skills.
Google Looker and SQL serve different roles in the realm of business intelligence. Looker provides a modern data exploration platform with a built-in modeling language, while SQL is a foundational language for querying databases.
For businesses requiring advanced analytics and custom visualizations, Looker presents a robust solution. SQL, on the other hand, offers granular control over data querying for those with the technical expertise.
Sourcetable offers an alternative by integrating real-time data across various services into a user-friendly spreadsheet interface. This approach simplifies the process of business intelligence, making it accessible without the need for complex tools or specialized knowledge.