Looker vs Power BI

Overview

Looker

Stacks632

Followers656

Votes9

Power BI

Stacks991

Followers946

Votes29

Looker vs Power BI: What are the differences?

Data Sources and Connectivity: Looker primarily connects to cloud-based data sources and requires a data warehouse to function effectively, whereas Power BI offers a wider range of data connections including cloud and on-premises sources, making it more versatile in terms of data accessibility and integration capabilities.
Visualization Capabilities: Power BI provides a larger selection of visualization options and customization features compared to Looker, allowing users to create more complex and interactive visuals, while Looker focuses more on providing a simplified and streamlined approach to visualization, which may be sufficient for basic reporting needs.
Cost Structure: Looker follows a per-user pricing model, which can become expensive as the number of users increases, whereas Power BI offers a more flexible pricing structure with options for both individual and enterprise users, making it potentially more cost-effective for larger organizations.
Learning Curve: Looker is known for its steep learning curve due to its unique data modeling and querying language, LookML, which may require additional training for users to fully utilize its capabilities, whereas Power BI is more user-friendly and intuitive, making it easier for beginners to create reports and dashboards without extensive technical knowledge.
Collaboration and Sharing: Power BI offers robust collaboration features such as seamless integration with Microsoft Teams and the ability to easily share reports and dashboards with other users, while Looker provides limited collaboration tools, requiring users to rely on third-party applications for sharing and collaboration purposes.
Scalability: Power BI is considered to be more scalable in handling large volumes of data and complex analysis compared to Looker, making it a preferred choice for organizations dealing with big data and demanding analytics needs.

In Summary, Looker and Power BI differ in their data connectivity, visualization capabilities, cost structures, learning curves, collaboration features, and scalability, catering to different needs and preferences of users.

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Advice on Looker, Power BI

Vojtech

Head of Data at Mews

Nov 24, 2019

Decided

Power BI is really easy to start with. If you have just several Excel sheets or CSV files, or you build your first automated pipeline, it is actually quite intuitive to build your first reports.

And as we have kept growing, all the additional features and tools were just there within the Azure platform and/or Office 365.

Since we started building Mews, we have already passed several milestones in becoming start up, later also a scale up company and now getting ready to grow even further, and during all these phases Power BI was just the right tool for us.

353k views353k

Comments

Wei

CTO at Flux Work

Jan 8, 2020

Decided

Very easy-to-use UI. Good way to make data available inside the company for analysis.

Has some built-in visualizations and can be easily integrated with other JS visualization libraries such as D3.

Can be embedded into product to provide reporting functions.

Support team are helpful.

The only complain I have is lack of API support. Hard to track changes as codes and automate report deployment.

230k views230k

Comments

Detailed Comparison

Looker	Power BI
We've built a unique data modeling language, connections to today's fastest analytical databases, and a service that you can deploy on any infrastructure, and explore on any device. Plus, we'll help you every step of the way.	It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards.
Zero-lag access to data;No limits;Personalized setup and support;No uploading, warehousing, or indexing;Deploy anywhere;Works in any browser, anywhere;Personalized access points	Get self-service analytics at enterprise scale; Use smart tools for strong results; Help protect your analytics data
Statistics
Stacks 632	Stacks 991
Followers 656	Followers 946
Votes 9	Votes 29
Pros & Cons
Pros 4 Real time in app customer chat support 4 GitHub integration 1 Reduces the barrier of entry to utilizing data Cons 3 Price	Pros 18 Cross-filtering 4 Database visualisation 2 Access from anywhere 2 Powerful Calculation Engine 2 Intuitive and complete internal ETL
Integrations
No integrations available	Microsoft Excel

What are some alternatives to Looker, Power BI?

Metabase

It is an easy way to generate charts and dashboards, ask simple ad hoc queries without using SQL, and see detailed information about rows in your Database. You can set it up in under 5 minutes, and then give yourself and others a place to ask simple questions and understand the data your application is generating.

Superset

Superset's main goal is to make it easy to slice, dice and visualize data. It empowers users to perform analytics at the speed of thought.

Cube

Cube: the universal semantic layer that makes it easy to connect BI silos, embed analytics, and power your data apps and AI with context.

Mode

Created by analysts, for analysts, Mode is a SQL-based analytics tool that connects directly to your database. Mode is designed to alleviate the bottlenecks in today's analytical workflow and drive collaboration around data projects.

Google Datastudio

It lets you create reports and data visualizations. Data Sources are reusable components that connect a report to your data, such as Google Analytics, Google Sheets, Google AdWords and so forth. You can unlock the power of your data with interactive dashboards and engaging reports that inspire smarter business decisions.

AskNed

AskNed is an analytics platform where enterprise users can get answers from their data by simply typing questions in plain English.

Shiny

It is an open source R package that provides an elegant and powerful web framework for building web applications using R. It helps you turn your analyses into interactive web applications without requiring HTML, CSS, or JavaScript knowledge.

Redash

Redash helps you make sense of your data. Connect and query your data sources, build dashboards to visualize data and share them with your company.

Azure Synapse

It is an analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources—at scale. It brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.

Periscope

Periscope is a data analysis tool that uses pre-emptive in-memory caching and statistical sampling to run data analyses really, really fast.

Related Comparisons

Looker vs Power BI: What are the differences?

Data Sources and Connectivity: Looker primarily connects to cloud-based data sources and requires a data warehouse to function effectively, whereas Power BI offers a wider range of data connections including cloud and on-premises sources, making it more versatile in terms of data accessibility and integration capabilities.
Visualization Capabilities: Power BI provides a larger selection of visualization options and customization features compared to Looker, allowing users to create more complex and interactive visuals, while Looker focuses more on providing a simplified and streamlined approach to visualization, which may be sufficient for basic reporting needs.
Cost Structure: Looker follows a per-user pricing model, which can become expensive as the number of users increases, whereas Power BI offers a more flexible pricing structure with options for both individual and enterprise users, making it potentially more cost-effective for larger organizations.
Learning Curve: Looker is known for its steep learning curve due to its unique data modeling and querying language, LookML, which may require additional training for users to fully utilize its capabilities, whereas Power BI is more user-friendly and intuitive, making it easier for beginners to create reports and dashboards without extensive technical knowledge.
Collaboration and Sharing: Power BI offers robust collaboration features such as seamless integration with Microsoft Teams and the ability to easily share reports and dashboards with other users, while Looker provides limited collaboration tools, requiring users to rely on third-party applications for sharing and collaboration purposes.
Scalability: Power BI is considered to be more scalable in handling large volumes of data and complex analysis compared to Looker, making it a preferred choice for organizations dealing with big data and demanding analytics needs.

Looker vs Power BI

Overview