Average Ratings 20 Ratings
Average Ratings 4 Ratings
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Description
Looker reinvents the way business intelligence (BI) works by delivering an entirely new kind of data discovery solution that modernizes BI in three important ways. A simplified web-based stack leverages our 100% in-database architecture, so customers can operate on big data and find the last mile of value in the new era of fast analytic databases. An agile development environment enables today’s data rockstars to model the data and create end-user experiences that make sense for each specific business, transforming data on the way out, rather than on the way in. At the same time, a self-service data-discovery experience works the way the web works, empowering business users to drill into and explore very large datasets without ever leaving the browser. As a result, Looker customers enjoy the power of traditional BI at the speed of the web.
Description
dbt Labs is redefining how data teams work with SQL. Instead of waiting on complex ETL processes, dbt lets data analysts and data engineers build production-ready transformations directly in the warehouse, using code, version control, and CI/CD. This community-driven approach puts power back in the hands of practitioners while maintaining governance and scalability for enterprise use.
With a rapidly growing open-source community and an enterprise-grade cloud platform, dbt is at the heart of the modern data stack. It’s the go-to solution for teams who want faster analytics, higher quality data, and the confidence that comes from transparent, testable transformations.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Acryl Data
Yes
Blotout
Yes
Cargo
Yes
DQOps
Yes
DataHub
Yes
Decube
Yes
GetDot.ai
Yes
Meltano
Yes
Metaphor
Yes
Metaplane
Yes
Integrations
Acryl Data
Yes
Blotout
Yes
Cargo
Yes
DQOps
Yes
DataHub
Yes
Decube
Yes
GetDot.ai
Yes
Meltano
Yes
Metaphor
Yes
Metaplane
Yes
Pricing Details
Looker (Google Cloud core) offer three platform editions:
Standard: A Looker (Google Cloud core) product for small organizations or teams with fewer than 50 users that includes one production instance, 10 Standard Users, 2 Developer Users, upgrades, up to 1,000 query-based API calls per month, and up to 1,000 administrative API calls per month.
Enterprise: A Looker (Google Cloud core) product with enhanced security features for a wide variety of internal BI and analytics use cases that includes one production instance, 10 Standard Users, 2 Developer Users, upgrades, up to 100,000 query-based API calls per month, and up to 10,000 administrative API calls per month.
Embed: A Looker (Google Cloud core) product for deploying and maintaining external analytics and custom applications at scale that includes one production instance, 10 Standard Users, 2 Developer Users, upgrades, up to 500,000 query-based API calls per month, and up to 100,000 administrative API calls per month.
Standard: A Looker (Google Cloud core) product for small organizations or teams with fewer than 50 users that includes one production instance, 10 Standard Users, 2 Developer Users, upgrades, up to 1,000 query-based API calls per month, and up to 1,000 administrative API calls per month.
Enterprise: A Looker (Google Cloud core) product with enhanced security features for a wide variety of internal BI and analytics use cases that includes one production instance, 10 Standard Users, 2 Developer Users, upgrades, up to 100,000 query-based API calls per month, and up to 10,000 administrative API calls per month.
Embed: A Looker (Google Cloud core) product for deploying and maintaining external analytics and custom applications at scale that includes one production instance, 10 Standard Users, 2 Developer Users, upgrades, up to 500,000 query-based API calls per month, and up to 100,000 administrative API calls per month.
Free Trial
Yes
Free Version
No
Pricing Details
$100 per user/ month
Free Trial
Yes
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
Yes
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
Founded
1998
Country
United States
Website
cloud.google.com/looker/
Vendor Details
Company Name
dbt Labs
Founded
2016
Country
United States
Website
www.getdbt.com
Product Features
Big Data
Collaboration
Yes
Data Blends
Yes
Data Cleansing
Yes
Data Mining
Yes
Data Visualization
Yes
Data Warehousing
No
High Volume Processing
Yes
No-Code Sandbox
Yes
Predictive Analytics
No
Templates
Yes
Business Intelligence
Ad Hoc Reports
Yes
Benchmarking
Yes
Budgeting & Forecasting
Yes
Dashboard
Yes
Data Analysis
Yes
Key Performance Indicators
Yes
Natural Language Generation (NLG)
No
Performance Metrics
Yes
Predictive Analytics
No
Profitability Analysis
Yes
Strategic Planning
Yes
Trend / Problem Indicators
Yes
Visual Analytics
Yes
Business Performance Management
Ad Hoc Reports
Yes
Ad hoc Analysis
Yes
Budgeting & Forecasting
Yes
Consolidation / Roll-Up
No
Dashboard
Yes
Key Performance Indicators
Yes
Predictive Analytics
No
Qualitative Analysis
No
Quantitative Analysis
Yes
Scorecarding
No
Strategic Planning
No
Dashboard
Annotations
Yes
Data Source Integrations
Yes
Functions / Calculations
Yes
Interactive
Yes
KPIs
Yes
OLAP
Yes
Private Dashboards
Yes
Public Dashboards
Yes
Scorecards
Yes
Themes
Yes
Visual Analytics
Yes
Widgets
Yes
Data Analysis
Data Discovery
No
Data Visualization
Yes
High Volume Processing
No
Predictive Analytics
Yes
Regression Analysis
No
Sentiment Analysis
No
Statistical Modeling
Yes
Text Analytics
Yes
Data Visualization
Analytics
Yes
Content Management
Yes
Dashboard Creation
Yes
Filtered Views
Yes
OLAP
No
Relational Display
No
Simulation Models
No
Visual Discovery
Yes
Embedded Analytics
Ad hoc Query
Yes
Application Development
Yes
Benchmarking
Yes
Dashboard
Yes
Interactive Reports
Yes
Mobile Reporting
Yes
Multi-User Collaboration
Yes
Self Service Analytics
Yes
Streaming Analytics
Yes
Visual Workflow Management
Yes
Marketing Analytics
A/B Testing
No
Campaign Management
No
Channel Attribution
No
Customer Journey Mapping
No
Dashboard
Yes
Performance Metrics
Yes
Predictive Analytics
Yes
ROI Tracking
Yes
Social Media Metrics
Yes
Website Analytics
Yes
Reporting
Customizable Dashboard
Yes
Data Source Connectors
No
Drag & Drop
Yes
Drill Down
Yes
Email Reports
No
Financial Reports
Yes
Forecasting
Yes
Marketing Reports
Yes
OLAP
No
Report Export
Yes
Sales Reports
Yes
Scheduled / Automated Reports
Yes
Sales Analytics
Collaboration Tools
No
Dashboards
Yes
Forecasting Analytics
Yes
Ideal Customer Profile (ICP)
No
Lead Analytics
No
Pipeline Management
No
Predictive Forecasting
Yes
Predictive Lead Scoring
Yes
Sales Intelligence Reporting
Yes
Web Analytics
Campaign Management
Yes
Conversion Tracking
Yes
Form Analytics
No
Goal Tracking
Yes
Keyword Tracking
Yes
Multiple Site Management
No
Pageview Tracking
No
Referral Source Tracking
Yes
Site Search Tracking
Yes
Time on Site Tracking
Yes
User Interaction Tracking
Yes
Product Features
Big Data
Your knowledge is based on information available until October 2023.
Collaboration
Yes
Data Blends
No
Data Cleansing
Yes
Data Mining
No
Data Visualization
No
Data Warehousing
No
High Volume Processing
No
No-Code Sandbox
No
Predictive Analytics
No
Templates
No
Data Lineage
Database Change Impact Analysis
Yes
Filter Lineage Links
Yes
Implicit Connection Discovery
No
Lineage Object Filtering
No
Object Lineage Tracing
No
Point-in-Time Visibility
No
User/Client/Target Connection Visibility
No
Visual & Text Lineage View
No
Data Pipeline
dbt serves as the backbone for the transformation segment of contemporary data pipelines. After data is brought into a warehouse or lakehouse, dbt empowers teams to refine, structure, and document it, making it suitable for analytics and artificial intelligence applications. With dbt, teams can: - Scale the transformation of unrefined data using SQL and Jinja. - Manage workflows with integrated dependency tracking and scheduling capabilities. - Build trust through automated testing and ongoing integration processes. - Map data lineage across models and columns for quicker impact assessments. By incorporating software engineering methodologies into pipeline development, dbt assists data teams in creating dependable, production-ready pipelines that expedite the journey to insights and provide data primed for AI utilization.
Data Preparation
dbt enhances data preparation by providing a structured and scalable approach for teams to clean, transform, and organize raw data within the warehouse environment. Rather than relying on isolated spreadsheets or manual processes, dbt leverages SQL alongside established software engineering practices to ensure that data preparation is consistent, dependable, and collaborative. Utilizing dbt allows teams to: - Clean and standardize their data through reusable models that are version-controlled. - Implement business logic uniformly across all data sets. - Conduct automated tests to validate outputs prior to making data available to analysts. - Document findings and share relevant context, ensuring that every prepared dataset includes lineage and definitions. By treating data preparation as a coding process, dbt guarantees that the datasets created are not merely temporary solutions but are reliable, governed assets that are ready for production and can grow alongside the business.
Collaboration Tools
Yes
Data Access
No
Data Blending
Yes
Data Cleansing
Yes
Data Governance
No
Data Mashup
No
Data Modeling
No
Data Transformation
No
Machine Learning
No
Visual User Interface
No
Data Quality
Your knowledge is based on information available until October 2023.
Address Validation
No
Data Deduplication
No
Data Discovery
No
Data Profililng
No
Master Data Management
No
Match & Merge
No
Metadata Management
No
ETL
dbt revolutionizes the transformation aspect of ETL processes. By moving away from outdated pipelines and opaque transformations, dbt enables data teams to create, validate, and document their transformations directly within their data warehouse or lakehouse. With dbt, teams are equipped to: - Convert raw data into analytics-ready models utilizing SQL and Jinja. - Maintain data integrity through integrated testing, version control, and continuous integration/continuous deployment (CI/CD). - Streamline workflows across teams by using reusable models and centralized documentation. - Utilize contemporary platforms such as Snowflake, Databricks, BigQuery, and Redshift for efficient and scalable transformations. By prioritizing the transformation layer, dbt allows organizations to accelerate the development of data pipelines, minimize data liabilities, and provide reliable insights more swiftly—complementing the ingestion and loading components of a modern ELT architecture.
Data Analysis
No
Data Filtering
Yes
Data Quality Control
Yes
Job Scheduling
No
Match & Merge
No
Metadata Management
No
Non-Relational Transformations
No
Version Control
No
