Jupyter Notebook for quick in-depth analysis
May 02, 2021

Jupyter Notebook for quick in-depth analysis

Shivani Pandey | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source

Overall Satisfaction with Jupyter Notebook

We are using Jupyter Notebook for data visualization of JSON and excel data for a banking customer. We are running multiple python scripts on Jupyter Notebook for in-depth data analysis to develop machine learning models.
  • Easy to learn and use
  • Data [modeling]
  • Data analysis and reporting
  • Predefined visualizations models
  • Not much troubleshooting support available
  • No support for IDE
  • Deployment is complex for cloud environments
  • Data visualization
  • Plotting and graphical charts
  • Lightweight
  • Saves a lot of time
  • Quick development and deployment
  • Easy to learn by developers

Do you think Jupyter Notebook delivers good value for the price?

Yes

Are you happy with Jupyter Notebook's feature set?

Yes

Did Jupyter Notebook live up to sales and marketing promises?

Yes

Did implementation of Jupyter Notebook go as expected?

Yes

Would you buy Jupyter Notebook again?

Yes

Jupyter Notebook is best suited for scenarios where you have small to medium size JSON/ Excel data. It is not well suited for large amounts of data.

Jupyter Notebook Feature Ratings

Connect to Multiple Data Sources
9
Extend Existing Data Sources
8
Automatic Data Format Detection
8
MDM Integration
9
Visualization
10
Interactive Data Analysis
9
Interactive Data Cleaning and Enrichment
9
Data Transformations
9
Data Encryption
6
Built-in Processors
6
Multiple Model Development Languages and Tools
9
Automated Machine Learning
9
Single platform for multiple model development
8
Self-Service Model Delivery
8
Flexible Model Publishing Options
8
Security, Governance, and Cost Controls
8