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Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

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.

Description

NovoExpress software offers a user-friendly platform for researchers at any expertise level in flow cytometry, facilitating streamlined sample acquisition and analysis. By automating various fluidic operations, it removes tedious and lengthy tasks from the workflow. The system significantly reduces the need for user intervention thanks to its walk-away autosampler feature, along with capabilities for batch analysis, statistical computation, and reporting. This software consolidates sample acquisition and data analysis into a single interface, enhancing user experience. To further boost productivity, users can analyze data as it is being collected, with ongoing sample acquisition occurring simultaneously in the background. The robust compensation tools and straightforward adjustments ensure precise compensation both before and after sample acquisition. Additionally, the batch analysis and reporting functions provide customizable statistical parameters, along with live updates that keep users informed while samples are being processed. Overall, NovoExpress empowers researchers to work more efficiently and effectively in their flow cytometry tasks.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

DataLab Yes 
Google Cloud Platform Yes 
Google Workspace Yes 
Jupyter Notebook Yes 

Integrations

DataLab No 
Google Cloud Platform No 
Google Workspace No 
Jupyter Notebook No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
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 No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

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

Types of Training

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

Types of Training

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

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

cloud.google.com/datalab

Vendor Details

Company Name

Agilent Technologies

Country

United States

Website

www.agilent.com/en/product/research-flow-cytometry/flow-cytometry-software/novocyte-novoexpress-software-1320805

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 

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 

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