Looker– An Interesting and Leading BI tool

What is a BI tool?

BI stands for Business Intelligence. BI refers to technologies and processes that help organizations collect, analyze, and present business data to support decision-making. There are many tools, software, and cloud services that assist in successfully achieving the mentioned BI goals. BI tools have a vital role in helping organizations make informed decisions by transforming raw data into meaningful insights. Common features of BI tools are data visualization, reporting, data integration, query & reporting, predictive analysis, and data warehousing. Microsoft Power BI, Looker, Oracle BI, Tableau, Datapine, IBM Congno Analytics, and Qlik Sense are a few of the leading BI tools available in the market.

What is Looker?

Looker is a business intelligence and data analytics platform. The recent Looker version available is Looker 24.2, released in February 2024.

Looker deployment options are:

Looker hosted instance: deployed on Looker’s cloud infrastructure. Looker manages and maintains the entire infrastructure, including servers, storage, and security.
Customer-hosted instance: deployed on the customer’s infrastructure, whether it be on-premises servers or private cloud environments.
Looker (Google Cloud core) is the deployment option over Google Cloud. Google Cloud console provides simplified provisioning, configuration, and management of Looker instances. This blog discusses the Looker (Google Cloud Core) instance.

Looker (Google Cloud core) is available in 3 editions:

Standard edition: Recommended for small-sized teams and small or medium-sized enterprises with up to 50 internal platform users. Includes all standard Looker features.
Enterprise edition: comprises all the features of the standard edition, supports unlimited users, includes additional security features such as VPC-SCand Private IP
Embed edition: includes all the features of the Enterprise edition, offering signed embedding, a private label option, custom themes, 500,000 Query API calls per month, and 100,000 Admin API calls per month.

Three types of Looker instance users:

Developer user
Standard user
Viewer user

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Components of Looker

The screenshot gives an idea about the navigation pane displayed on Looker UI. In Looker, contents are stored in the form of Look or Dashboard. A Look can hold a single visualization, while a dashboard can have multiple visualizations. Administrative configurations can be performed through the Admin option. Admin configurations include –

Access control and permission management for users
Connection to database
Log related to user activity and history of Looker instance
Deleting disabled or deleted users’ personal information
Time zone settings
Managing user alerts and schedules, etc.

Looker Explore is a starting point for a query (question to data). It is the place where data is available for creating visualizations. Inside Explore, data is organized in multiple Views. Each view contains dimensions and measures.

Dimensions represent columns, while measures represent aggregation operations which can be performed on data.

The screenshot shows Fruit Basket (mentioned as a title) as an exploration. Below mentioned Fruit Basket is the view. Color, Fruit Type, etc., are a few dimensions from the Fruit Basket view. Average Price, Count, etc., are a few measures from Fruit Basket’s view.

Contents such as looks and dashboards are saved in Folders. My Folder, Shared Folder, and People are different Folders with organized contents. The board is a centralized place that links to other contents available in the Looker instance or to which the user has access. Developer users can create new explorers. Looks and dashboards created in Looker can be shared using multiple options such as download, share, schedule share, etc. Generated visualizations can be formatted in different ways, such as pie charts, columns, bar charts, line charts, maps, etc.

What is LookML

LookML stands for Looker Modelling Language. LookML syntax can create dimensions, aggregates (measures), calculations, and data relationships. LookML is designed to simplify defining and managing data models, which are the foundation for creating reports, dashboards, and analyses within the Looker platform. Using LookML, the model that executes SQL queries against the database is created. Developer users of Looker use LookML to make explorations, which are eventually used for report generation or visualization.

Looker Vs. Looker Studio

Data Studio (Google’s data visualization tool) is renamed Looker Studio. Looker Studio is a dashboarding analytics tool, while Looker is a data modeling, analytics, and dashboarding tool. Looker Studio can be connected with multiple data sources to import data. Explorer in Looker Studio is responsible for creating and designing reports. Reports created in Looker Studio can be shared among users with a view or edit access rights. Looker Studio Pro was recently introduced, and some more add-on features were added to Looker Studio. Using Looker, the same data model can be used by multiple organization users, leading to a standardization approach.

Conclusion

Looker is one of the most powerful BI tools. Using LookML, centralized and reusable data models can be created. Looker can be connected to various data sources such as databases, data warehouses, and cloud storage services. Looker facilitates collaboration through sharing reports, dashboards, and explorations. It supports scheduled reports and alerts.

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