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Best Data Modelling Tools

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cloudy tech
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2 min read

Data modeling relates to the application of certain methodologies and techniques on the data for converting it into a form that is not only meaningful but also easier to comprehend. In other words, it is used to convert intricate software design into a more straightforward format.

Data modeling

Benefits of Data Modeling

  • Integrate data from various sources that may not communicate well with each other.
  • Use free data modeling tools for creating big data so that information is easy to access.
  • Know your business by trying out graphic descriptions of complex concepts.

List of Data Modeling Tools:

1. RapidMiner

RapidMiner

Pros

  • It has a flow-based programming approach that allows the visualization of pipelines.
  • It contains modules for machine learning, statistical analysis, etc.
  • No coding is required.
  • Easy to set up.

Cons

  • Costly.
  • ‘No coding’ sometimes creates challenges for the users.

2. MapBusinessOnline

MapBusinessOnline

Pros

  • It optimizes the information for sales.
  • An essential tool for analyzing the real impact.
  • Easy to use.

Cons

  • Navigation around the maps is a bit messy.
  • Mapping curves creates issues.

3. Vertabelo

Vertabelo

Pros

  • Innovative and flexible.
  • Amazing UI and easy-to-use features.

Cons

  • Performance issues sometimes cause glitches.
  • Costly.

4. Lucidchart

Lucidchart

Pros

  • It provides convenience in a traditional flowchart system.
  • Overall performance is amazing.
  • Great visual features.

Cons

  • Users can face issues while finding the documents into many elements.
  • The saving and storing system is a bit messy and, thus, creates challenges for the user.
  • A little issue can cause a huge error. Sharing option should be improved.

5. SQL Database Modeler

SQL Database Modeler

Pros

  • Features Many varieties of the database.
  • Fast for:
    • Searching and querying of data.
    • Recovering data from multiple tables.
  • Can manage large numbers of transactions.

Cons

  • Can be hard to turn data from objects into database tables.
  • Vertically scalable.
  • Loss of partition tolerance.

Conclusion

Currently, there are various data modeling tools available that can help you to gain meaningful insights from huge proportions of data.

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