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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Dataform provides a platform for data analysts and engineers to create and manage scalable data transformation pipelines in BigQuery using solely SQL from a single, integrated interface. The open-source core language allows teams to outline table structures, manage dependencies, include column descriptions, and establish data quality checks within a collective code repository, all while adhering to best practices in software development, such as version control, various environments, testing protocols, and comprehensive documentation. A fully managed, serverless orchestration layer seamlessly oversees workflow dependencies, monitors data lineage, and executes SQL pipelines either on demand or on a schedule through tools like Cloud Composer, Workflows, BigQuery Studio, or external services. Within the browser-based development interface, users can receive immediate error notifications, visualize their dependency graphs, link their projects to GitHub or GitLab for version control and code reviews, and initiate high-quality production pipelines in just minutes without exiting BigQuery Studio. This efficiency not only accelerates the development process but also enhances collaboration among team members.

Description

Cloud Datalab is a user-friendly interactive platform designed for data exploration, analysis, visualization, and machine learning. This robust tool, developed for the Google Cloud Platform, allows users to delve into, transform, and visualize data while building machine learning models efficiently. Operating on Compute Engine, it smoothly integrates with various cloud services, enabling you to concentrate on your data science projects without distractions. Built using Jupyter (previously known as IPython), Cloud Datalab benefits from a vibrant ecosystem of modules and a comprehensive knowledge base. It supports the analysis of data across BigQuery, AI Platform, Compute Engine, and Cloud Storage, utilizing Python, SQL, and JavaScript for BigQuery user-defined functions. Whether your datasets are in the megabytes or terabytes range, Cloud Datalab is equipped to handle your needs effectively. You can effortlessly query massive datasets in BigQuery, perform local analysis on sampled subsets of data, and conduct training jobs on extensive datasets within AI Platform without any interruptions. This versatility makes Cloud Datalab a valuable asset for data scientists aiming to streamline their workflows and enhance productivity.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

DataLab No 
GitHub Yes 
GitLab Yes 
Google Cloud BigQuery Yes 
Google Cloud Managed Service for Apache Airflow Yes 
Google Cloud Platform No 
Google Workspace No 
Jupyter Notebook No 
SQL Yes 

Integrations

DataLab Yes 
GitHub No 
GitLab No 
Google Cloud BigQuery No 
Google Cloud Managed Service for Apache Airflow No 
Google Cloud Platform Yes 
Google Workspace Yes 
Jupyter Notebook Yes 
SQL No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial Yes 
Free Version 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 

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) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

cloud.google.com/dataform

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

cloud.google.com/datalab

Product Features

Product Features

Data Analysis

Data Discovery No 
Data Visualization No 
High Volume Processing No 
Predictive Analytics No 
Regression Analysis No 
Sentiment Analysis No 
Statistical Modeling No 
Text Analytics No 

Data Visualization

Analytics No 
Content Management No 
Dashboard Creation No 
Filtered Views No 
OLAP No 
Relational Display No 
Simulation Models No 
Visual Discovery No 

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

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