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What is Google Cloud Datalab?

Cloud Datalab serves as an intuitive interactive platform tailored for data exploration, analysis, visualization, and machine learning. This powerful tool, created for the Google Cloud Platform, empowers users to investigate, transform, and visualize their data while efficiently developing machine learning models. Utilizing Compute Engine, it seamlessly integrates with a variety of cloud services, allowing you to focus entirely on your data science initiatives without unnecessary interruptions. Constructed on the foundation of Jupyter (formerly IPython), Cloud Datalab enjoys the advantages of a dynamic ecosystem filled with modules and an extensive repository of knowledge. It facilitates the analysis of data across BigQuery, AI Platform, Compute Engine, and Cloud Storage, using Python, SQL, and JavaScript for user-defined functions in BigQuery. Whether your data is in the megabytes or terabytes, Cloud Datalab is adept at addressing your requirements. You can easily execute queries on vast datasets in BigQuery, analyze local samples of data, and run training jobs on large datasets within the AI Platform without any hindrances. This remarkable flexibility makes Cloud Datalab an indispensable tool for data scientists who seek to optimize their workflows and boost their productivity, ultimately leading to more insightful data-driven decisions.

What is AnyGrids?

AnyGrids is a versatile open-source JavaScript grid library that integrates charts to facilitate the effective visualization of business data. By leveraging the core functionality of AnyGrid, users can easily create interactive tables from a range of data formats, including JavaScript arrays, JSON, and AJAX sources. The library can be incorporated into projects through a simple script tag or by installing it via npm, enabling immediate use without extensive setup. AnyGrid offers a variety of features, such as sorting, filtering, and grouping of data, along with expandable table rows that allow for customizable data rendering. Users can also boost their visual presentations with an array of sparklines, access pre-designed themes, perform calculations within columns, and manage pagination effortlessly. With its adaptability and rich set of features, AnyGrids stands out as an essential tool for developers aiming to showcase data both dynamically and effectively. Furthermore, the ongoing support and updates from the community enhance its longevity and relevance in various projects.

Media

Media

Integrations Supported

DataLab
Google Cloud Platform
Google Workspace
Jupyter Notebook

Integrations Supported

DataLab
Google Cloud Platform
Google Workspace
Jupyter Notebook

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

cloud.google.com/datalab

Company Facts

Organization Name

AnyGrids

Date Founded

2020

Company Location

Finland

Company Website

anygrids.com

Categories and Features

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Data Visualization

Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Categories and Features

Data Visualization

Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery

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