Anaconda vs Datawatch Monarch

Anaconda

Anaconda is great for academic and private organizations that cannot afford more expensive Python/R package managers. Also, it is more appropriate for intermediate to advanced Python users--Anaconda can be somewhat frustrating for beginners, as it takes some practice to get comfortable with the workflow. I find it particularly useful for working in teams, because if everyone uses the same package manager, it is easier to troubleshoot issues and makes for reproducible research. For wealthier organizations, a premium package management system (with tech support) would be ideal. Anaconda is also great for people working independently on code development.

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Maike Holthuijzen

Ph.D student

University of VermontHigher Education, 5001-10,000 employees

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Datawatch Monarch

If you need to quickly export large reports that contain superfluous data, regardless of format or software, you should use Modeler.

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David O'Reilly

Business Operations Manager

Varian Medical SystemsMedical Devices, 5001-10,000 employees

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Feature Rating Comparison

Anaconda

7.5

Datawatch Monarch

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Visualization

7.0

—

Interactive Data Analysis

8.0

—

Anaconda

7.0

Datawatch Monarch

—

Interactive Data Cleaning and Enrichment

7.0

—

Data Transformations

8.0

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Data Encryption

6.0

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Built-in Processors

7.0

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Anaconda

5.7

Datawatch Monarch

—

Automated Machine Learning

4.0

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Single platform for multiple model development

7.0

—

Self-Service Model Delivery

6.0

—

Anaconda

4.5

Datawatch Monarch

—

Flexible Model Publishing Options

5.0

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Security, Governance, and Cost Controls

4.0

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Pros

Anaconda has iPython- Notebook that facilitates code writing in Python
It's very easy to install tour preferred the Python version
The risk of messing up the libraries is completely eliminated

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Mauricio Quiroga-Pascal Ortega

Senior Cognitive Solutions Consultant

Cognitiva IBM Watson Strategic PartnerComputer Software, 51-200 employees

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It allows us to quickly dump large non-ALV SAP reports into Excel. Exporting these reports prior to Modeler was cumbersome at best.
Customizable models allow us to easily gather required data from the same report running different dates. This is perfect for month-end reports.
Quick exports.

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David O'Reilly

Business Operations Manager

Varian Medical SystemsMedical Devices, 5001-10,000 employees

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Cons

Requires dedicated administration.
Expensive.
Removes some control from end-users (analysts).

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Verified User

Analyst in Marketing

Marketing and Advertising Company, 501-1000 employees

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Graphical interface

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Javier Icaza

Remote Services Engineer

Optimal Networks, Inc.Government Relations, 11-50 employees

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Likelihood to Renew

No score

No answers yet

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Datawatch Monarch7.2

Based on 6 answers

It was useful but expensive.

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Javier Icaza

Remote Services Engineer

Optimal Networks, Inc.Government Relations, 11-50 employees

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Alternatives Considered

Anaconda is the best Python environment because you have all the things you need all in one places, at the reach of your hand. You can download and manage libraries as you wish and is very easy to create new projects and API's for all your stuff.It's Multiplatform so you don't have to take care to use your stuff in another computer. I think it is the best characteristic.

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Alejandro Daniel Copati

Desarrollador

Xavia IOTInternet, 1-10 employees

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Datawatch is very good value of money compared to QlikView; QlikView is really more of a BI tool and has a lot of functions that I didn't need. Datawatch is very strong in the real-time area where Tableau, Panorama, and Qlik don't do very well. If you need to set up a visual monitoring dashboard, Datawatch is the best product I've seen for that. if you want to do a lot of in depth statistical analysis of large databases, Tableau is probably a good option.

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Verified User

Executive in Marketing

Computer Software Company, 51-200 employees

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