Looker vs Segment

Overview

Segment

Stacks3.3K

Followers941

Votes275

Looker

Stacks632

Followers656

Votes9

Looker vs Segment: What are the differences?

Looker and Segment are two popular data analytics tools that offer different functionalities and features. Understanding the key differences between Looker and Segment is crucial for organizations to determine the best fit for their analytics and data needs.

Data Visualization Capabilities: Looker is primarily known for its robust data visualization capabilities. It offers a wide range of customizable charts, graphs, and dashboards that allow users to easily analyze and present data in an intuitive and visually appealing way. On the other hand, Segment focuses more on data collection and customer data integration, providing a powerful infrastructure for gathering and managing data from multiple sources.
Data Sources Integration: Looker provides seamless integration with various data sources, including databases, data warehouses, and cloud storage platforms. It allows users to connect to these sources directly and create a unified view of their data. In contrast, Segment specializes in data integration and offers a comprehensive set of connectors that enable users to collect data from various sources and send it to different destinations, such as marketing tools or analytics platforms.
Data Transformation and Preparation: Looker offers advanced data transformation and preparation capabilities, allowing users to clean, transform, and enrich their data within the platform. It provides a powerful modeling language (LookML) that enables users to define business logic and calculations. Segment, on the other hand, focuses more on data collection and provides limited data transformation capabilities. It primarily focuses on routing and delivering data to different destinations without extensive data manipulation.
Real-time Data Collection: Segment excels in real-time data collection and processing. It offers robust SDKs and APIs that enable users to collect, track, and send data in real-time, making it ideal for applications that require up-to-date information for analytics or personalization. Looker, on the other hand, is more focused on providing powerful analytics and reporting capabilities rather than real-time data collection.
Collaboration and Sharing: Looker provides extensive collaboration and sharing features, allowing users to easily share reports, dashboards, and insights with others in the organization. It offers user permissions, scheduling options, and the ability to embed reports in other applications. Segment, on the other hand, primarily focuses on data collection and does not provide similar collaboration and sharing features.
Pricing and Licensing: Looker offers a variety of pricing and licensing options, including both user-based and data volume-based models. It provides flexibility for organizations to choose the best pricing structure based on their specific requirements. Segment's pricing model is primarily based on the volume of data collected, making it more suitable for organizations with large data volumes.

In Summary, Looker offers robust data visualization capabilities, extensive data sources integration, advanced data transformation and preparation, while Segment excels in real-time data collection, provides a powerful infrastructure for data integration, and offers a pricing model based on data volume.

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CLI (Node.js)

Manual

Advice on Segment, Looker

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

Segment	Looker
Segment is a single hub for customer data. Collect your data in one place, then send it to more than 100 third-party tools, internal systems, or Amazon Redshift with the flip of a switch.	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.
A single API to integrate third-party tools; Data replay that backfills new tools with historical data; SQL support to automatically transform and load behavioral data into Amazon Redshift; More than 120 tools on the platform; One-click to install plugins for WordPress, Magento and WooCommerce; Mobile, web and server-side libraries	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
Statistics
Stacks 3.3K	Stacks 632
Followers 941	Followers 656
Votes 275	Votes 9
Pros & Cons
Pros 86 Easy to scale and maintain 3rd party services 49 One API 39 Simple 25 Multiple integrations 19 Cleanest API Cons 2 Not clear which events/options are integration-specific 1 Limitations with integration-specific configurations 1 Client-side events are separated from server-side	Pros 4 GitHub integration 4 Real time in app customer chat support 1 Reduces the barrier of entry to utilizing data Cons 3 Price
Integrations
Google Analytics Mixpanel UserVoice LiveChat Olark Marketo Intercom Sentry BugHerd Gauges	No integrations available

What are some alternatives to Segment, Looker?

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.

Power BI

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.

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.

Related Comparisons

Looker vs Segment: What are the differences?

Data Visualization Capabilities: Looker is primarily known for its robust data visualization capabilities. It offers a wide range of customizable charts, graphs, and dashboards that allow users to easily analyze and present data in an intuitive and visually appealing way. On the other hand, Segment focuses more on data collection and customer data integration, providing a powerful infrastructure for gathering and managing data from multiple sources.
Data Sources Integration: Looker provides seamless integration with various data sources, including databases, data warehouses, and cloud storage platforms. It allows users to connect to these sources directly and create a unified view of their data. In contrast, Segment specializes in data integration and offers a comprehensive set of connectors that enable users to collect data from various sources and send it to different destinations, such as marketing tools or analytics platforms.
Data Transformation and Preparation: Looker offers advanced data transformation and preparation capabilities, allowing users to clean, transform, and enrich their data within the platform. It provides a powerful modeling language (LookML) that enables users to define business logic and calculations. Segment, on the other hand, focuses more on data collection and provides limited data transformation capabilities. It primarily focuses on routing and delivering data to different destinations without extensive data manipulation.
Real-time Data Collection: Segment excels in real-time data collection and processing. It offers robust SDKs and APIs that enable users to collect, track, and send data in real-time, making it ideal for applications that require up-to-date information for analytics or personalization. Looker, on the other hand, is more focused on providing powerful analytics and reporting capabilities rather than real-time data collection.
Collaboration and Sharing: Looker provides extensive collaboration and sharing features, allowing users to easily share reports, dashboards, and insights with others in the organization. It offers user permissions, scheduling options, and the ability to embed reports in other applications. Segment, on the other hand, primarily focuses on data collection and does not provide similar collaboration and sharing features.
Pricing and Licensing: Looker offers a variety of pricing and licensing options, including both user-based and data volume-based models. It provides flexibility for organizations to choose the best pricing structure based on their specific requirements. Segment's pricing model is primarily based on the volume of data collected, making it more suitable for organizations with large data volumes.

Looker vs Segment

Overview