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Anaconda

Score8.1 out of 10

143 Reviews and Ratings

Top Performing Features

+5%

Single platform for multiple model development

Single place to build, validate, deliver, and monitor many different models

Cat avg: 9.5

+9%

Flexible Model Publishing Options

Publish models as REST APIs, hosted interactive web apps or as scheduled jobs for generating reports or running ETL tasks.

Cat avg: 9.2

+11%

Connect to Multiple Data Sources

Ability to connect to a wide variety of data sources including data lakes or data warehouses for data ingestion

Cat avg: 8.8

+16%

Data Encryption

Data encryption to ensure data privacy

Cat avg: 8.4

Worst Performing Features

-10%

Extend Existing Data Sources

Use R or Python to create custom connectors for any APIs or databases

Cat avg: 8.9

-9%

Interactive Data Analysis

Ability to analyze data interactively using Python or R Notebooks

Cat avg: 8.8

-12%

Data Transformations

Use visual tools for standard transformations

Cat avg: 9.1

Anaconda Features from Reviews

Platform Connectivity

Ability to connect to a wide variety of data sources

9.3+5%
  • Connect to Multiple Data Sources

    Ability to connect to a wide variety of data sources including data lakes or data warehouses for data ingestion

    Category average: 8.8

  • Extend Existing Data Sources

    Use R or Python to create custom connectors for any APIs or databases

    Category average: 8.9

  • Automatic Data Format Detection

    Automatic detection of data formats and schemas

    Category average: 9.2

  • MDM Integration

    Integration with MDM and metadata dictionaries

    Category average: 7.8

Data Exploration

Ability to explore data and develop insights

8.5-1%
  • Visualization

    The product’s support and tooling for analysis and visualization of data.

    Category average: 8.3

  • Interactive Data Analysis

    Ability to analyze data interactively using Python or R Notebooks

    Category average: 8.8

Data Preparation

Ability to prepare data for analysis

9.0+2%
  • Interactive Data Cleaning and Enrichment

    Access to visual processors for data wrangling

    Category average: 9

  • Data Transformations

    Use visual tools for standard transformations

    Category average: 9.1

  • Data Encryption

    Data encryption to ensure data privacy

    Category average: 8.4

  • Built-in Processors

    Library of processors for data quality checks

    Category average: 9

Platform Data Modeling

Building predictive data models

9.2+2%
  • Multiple Model Development Languages and Tools

    Access to multiple popular languages, tools, and packages such as R, Python, SAS, Jupyter, RStudio, etc.

    Category average: 9.2

  • Automated Machine Learning

    Tools to help automate algorithm development

    Category average: 8.9

  • Single platform for multiple model development

    Single place to build, validate, deliver, and monitor many different models

    Category average: 9.5

  • Self-Service Model Delivery

    Multiple model delivery modes to comply with existing workflows

    Category average: 8.3

Model Deployment

Tools for deploying models into production

9.5+8%
  • Flexible Model Publishing Options

    Publish models as REST APIs, hosted interactive web apps or as scheduled jobs for generating reports or running ETL tasks.

    Category average: 9.2

  • Security, Governance, and Cost Controls

    Built-in controls to mitigate compliance and audit risk with user activity tracking

    Category average: 8.6

Anaconda Features from the Vendor

Platform Connectivity

Vendor-contributed
  • Extend Existing Data Sources

    Use R or Python to create custom connectors for any APIs or databases

Data Exploration

Vendor-contributed
  • Visualization

    The product’s support and tooling for analysis and visualization of data.

  • Interactive Data Analysis

    Ability to analyze data interactively using Python or R Notebooks

Data Preparation

Vendor-contributed
  • Data Transformations

    Use visual tools for standard transformations

  • Data Encryption

    Data encryption to ensure data privacy

Platform Data Modeling

Vendor-contributed
  • Multiple Model Development Languages and Tools

    Access to multiple popular languages, tools, and packages such as R, Python, SAS, Jupyter, RStudio, etc.

  • Automated Machine Learning

    Tools to help automate algorithm development

  • Single platform for multiple model development

    Single place to build, validate, deliver, and monitor many different models

  • Self-Service Model Delivery

    Multiple model delivery modes to comply with existing workflows

Model Deployment

Vendor-contributed
  • Flexible Model Publishing Options

    Publish models as REST APIs, hosted interactive web apps or as scheduled jobs for generating reports or running ETL tasks.

  • Security, Governance, and Cost Controls

    Built-in controls to mitigate compliance and audit risk with user activity tracking