12 Data Modeling Tools for Data Analysis

By Indeed Editorial Team

Published March 11, 2022

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

Data modeling is the process of creating models for analyzing large amounts of data. If your work involves drawing relevant conclusions from unsorted data, you can improve your output by using a data modeling tool. Learning about common data modeling tools can be a useful career step. In this article, we list 12 popular data modeling tools and discuss their uses and benefits.

Read more: What Is Data Modeling?

12 data modeling tools

Consider these 12 data modeling tools for your data analysis tasks:

1. ER/Studio

This data modeling tool helps you analyze data and reduce redundancies for both new and existing datasets. It integrates with Git, which is an open-source distributed control system that helps users improve efficiency and speed when handling various projects, by using SSIS and SRSS standards. It can also handle the reverse engineering of data, which is the process of analyzing a database or a script and determining the data model used to create it.

2. ConceptDraw

This data modeling tool can be helpful for analyzing data for your business and explaining the results to non-technical professionals. It helps you to do this by allowing you to use specific add-ons that let you add elements like diagrams, flowcharts and infographics. ConceptDraw runs on both macOS and Windows operating systems, allowing users to create a file using a Windows-operated device and edit it with a macOS-operated one, and vice versa.

3. Erwin Data Modeler

This data modeling tool may appeal to non-technical users, mainly because designing, deploying and analyzing data sources with this software requires less complex processes than on similar products. It also allows users to automate and standardize certain tasks required for creating data models, making it easier to make relevant data analyses and integrate them into the business process. Analyzing data structures and their meaning is also a straightforward process, as the tool centralizes logical, physical and conceptual data, helping an organization's stakeholders understand the conclusions.

4. Toad Data Modeler

This data modeling tool can be appropriate for small and medium-sized companies who want to use data to improve their operations, as it makes it simple to design, maintain and document data modeling and analysis. It allows users to quickly and effectively build complex logical and physical data models, compare multiple models, generate SQL/DDL, create and edit database schema and scripts, as well as the ability to reverse and forward engineer databases and data warehouse systems. It can also create in-depth reports that assess existing database structures.

Related: 10 Dimensional Modeling Skills for Data Modelers

5. RapidMiner

This tool can appeal to both data modeling beginners and to data scientists using it for highly complex analyses. It helps those who lack experience with data modeling tools by providing them with extensive tutorials and pre-set case templates that they can use to build their data models and analyze results. It also provides data scientists with over 1,500 native algorithms and functions, plus software integration with R and Python programming languages.

6. SQL Database Modeler

This tool specializes in reverse engineering and forward engineering databases. You can reverse engineer an existing database to discover various ways in which you can enhance its quality and then use forward engineering to assess the most appropriate methods of growing the database in the future. It also features a very user-friendly interface and collaboration functions that allow multiple data professionals and project managers to view and comment on team projects.

7. DbSchema

This data modeling tool can work with both SQL and non-SQL databases, eliminating the need for multiple tools when analyzing different database types. It also allows data uploads from spreadsheet files, making it possible to analyze old and unprocessed data. Besides being an all-in-one database analysis tool, it also makes it easy to manage and document schemas, which are representations of how data is organized within a database.

Related: 10 Predictive Modeling Types (With Benefits and Uses)

8. Whatagraph

This tool helps users aggregate data from multiple sources and create visual representations of their data models. It does so through an intuitive and editable drag-and-drop interface that makes it usable for non-technical people to create data models and generate meaningful conclusions. Watagraph also integrates with many external data sources, like analytics tools, social media platforms and e-commerce platforms.

9. ERBuilder Data Modeler

This data modeling tool mainly appeals to data professionals, like data architects and modelers. It features a complex visual user interface and supports some of the most common standard notations, like Crow's Foot, IDEF1x and Codasyl. It also includes forward and reverse engineering capabilities and data generation testing features that help users add meaningful test data to their databases.

10. Archi

This open-source data modeling tool is a toolkit for creating data models and sketches in the ArchiMate language, which is an independent Enterprise Architecture modeling language that supports descriptions, analyses and visualizations of architecture both across and within business domains. It can help beginners understand it better by providing useful hints and a Sketch View system that allows them to refine concepts before exporting them into ArchiMate Views. Archi is a cross-platform software and runs on Windows, macOS and Linux.

11. DeZign for Databases

This data modeling tool aims to simplify the work of database administrators and developers by helping them visualize database structures so they can create new databases or reverse-engineer existing ones. It uses entity relationship diagrams (ERD), which are graphical representations that show relationships between similar database elements, to help users graphically design their own databases. It also features a Datanamic Repository, which is a central data storing repository where users can store data models and where multiple users can work on the same one.

Related: Data Lake vs. Data Warehouse vs. Data Mart: A Definitive Guide

12. HeidiSQL

This open-source data modeling tool enables users to visualize and edit data from multiple database systems, such as Microsoft SQL, MySQL, SQLite, MariaDB and PostgreSQL. Its graphical user interface has multiple features and capabilities, like multiple options for hosting and connecting to servers, database creation and visualization and various database sorting elements, like tables, procedures, columns and indexes. It also allows users to export data from one server or database directly to another.

Please note that none of the companies mentioned in this article are affiliated with Indeed.

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