What Is a Data Modeler?

Written by Coursera • Updated on

A data modeler ensures an organization’s data is organized correctly and optimized into an information system to help achieve critical objectives. Learn more about what the data modeling career entails and the steps you can take to become a data modeler.

[Featured image] Staff working on data input

Data modelers are systems analysts who work with data architects and database administrators to design computer databases and are at the forefront of data management measures that underpin organizational data structures. In more ways than one, these systems analysts play an integral role in helping organizations achieve end goals in nearly every area of operation, including product lifecycle and customer experience.

Knowing what data modeling is, what data modelers do in their roles, and the skills, education, and experience needed to become a data modeler can help determine if this career path is right for you.

What is data modeling?

Data modeling is the process by which data is evaluated, organized, measured, and managed in particular business processes. Data modeling produces usable computer systems from complex business data at its core [1].  The overarching goal of the data modeler role is to design and construct databases that enable organizations to access and utilize their data more effectively.

Data modeled through data modeling is represented visually and can illustrate either an entire information system or parts of the whole. Within this visual representation are various points and structures that comprise the data that is or will be stored within the information system.

Importance of data modeling

The importance of data modeling rests with the treatment of specific data. Not all data can or should be treated the same. Therefore, it is a part of the data modelers’ responsibility to determine how to structure data to ensure it meets the needs of both the organization and its end customers.

Another critical aspect of data modeling is using the data as a resource for achieving organizational objectives. Predefined requirements and rules govern data management in databases and information systems to ensure that the data’s incorporation into the system is correct. This step also ensures that the data is efficiently used and applied and can adapt to the needs and expectations of stakeholders and end-users.

In an ideal situation, data models are dynamic and fully and functionally support business processes and planning, no matter how complex.

What do data modelers do?

As a data modeler, you will design and manage data systems that are architecturally sound enough to support your organization's goals. In most cases, you will be working with other information technology (IT) professionals like data scientists and database administrators to model critical data and information that will play an essential role in the organization’s decision-making and customer experiences processes. Additionally, you will be responsible for understanding how core data is utilized and supporting all organizational stakeholders and operations, including its products, customers, and staff.

Skills you need to succeed as a data modeler

Data modelers are expected to possess critical skills that will be especially important in helping them operate efficiently and keep them focused on fulfilling their roles. Such skills include but are not limited to:

  • Data modeling experience

  • Database administration experience

  • Ability to learn and adapt quickly

  • Ability to work independently and as a part of a team

  • Software development experience

  • Experience with data modeling tools such as ERWin and Power Design

  • Experience with SQL

  • Experience with Microsoft Word, Excel, and PowerPoint

  • Good analytical skills

  • Ability to exercise creative and solution-based thinking

  • Excellent verbal communication

  • Ability to think abstractly

Read more: Is Data Analytics Hard? Tips for Rising to the Challenge

Job opportunities for data modelers

There is no shortage of job opportunities for data modelers. After acquiring the education, skills, and experience needed to become a data modeler, you have the qualifications necessary for several job opportunities across a spectrum of data management roles and capacities, including:

  • Lead data modeler

  • Data modeling consultant

  • Senior data modeler

  • Data integration manager

  • Data engineer

  • Data analyst

Benefit from a strong job outlook

Data modeling remains a growing field in the data science industry. According to the US Bureau of Labor Statistics, the field of data modeling is expected to grow by 8 percent over the next decade [2].

Suppose you decide to step into a career as a data modeler. In that case, you will appreciate knowing that the growing need for data management coupled with the consistent success of the role (with organizations within a variety of industries) makes this a secure line of work for the near future.

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Common career path for becoming a data modeler

The road to becoming a data modeler, though straightforward, may not look the same for each person. Some data modelers start their careers as data analysts. At the same time, some others may wait until they have earned all the education, experience, and certifications needed to go straight into a data modeling road.

Once you’ve decided to secure a career in this field, consider this common career path for becoming a data modeler:

Get a degree

Most companies require that you have earned, at minimum, a bachelor’s degree in either information science, computer science, applied mathematics, or some other related field [3]. Hence, one of the first things you’ll need to consider is earning a degree that will later qualify you to obtain a data modeler role.

Read more: How Long Does It Take to Get a Bachelor’s Degree?

Work experience

Alongside the proper education, organizations typically want to know that you have working experience as a data professional. Having served in a data modeling role may not be necessary. Still, the company will likely want to confirm that you’ve either worked in data management or data design and architecture.

Certifications

Obtaining the proper certifications can be vital in helping you prove your expertise, increase your skills, and enhance your opportunities to secure data modeling roles.

Average potential salary 

The average base salary of a data modeler in the United States is more than $94,000 [4].

Of course, the salary you secure will depend on other factors as well, such as the amount of education and training you’ve received, certifications earned, and the number of years of experience in the field, among other things.

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Next Steps

For an introduction to data modeling, consider taking the Introduction to Big Data course offered through the University of California, San Diego on Coursera.

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course

Introduction to Big Data

Interested in increasing your knowledge of the Big Data landscape? This course is for those new to data science and interested in understanding why the Big ...

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Average time: 1 month(s)

Learn at your own pace

Skills you'll build:

Big Data, Apache Hadoop, Mapreduce, Cloudera

Coursera also offers several certificates, including the IBM Data Science Professional Certificate, or a Google Cloud Data Engineering, Big Data, and Machine Learning on GCP Specialization.

Related articles

Article sources

1. JobHero. “What is a Data Modeler? https://www.jobhero.com/career-guides/interviews/prep/what-is-a-data-modeler." Accessed April 4, 2022.

2. US Bureau of Labor Statistics. “Database Administrators and Architects  https://www.bls.gov/ooh/computer-and-information-technology/database-administrators.htm." Accessed April 4, 2022.

3. Dataversity. “So You Want To Be a Data Modeler?  https://www.dataversity.net/so-you-want-to-be-a-data-modeler/." Accessed April 4, 2022.

4. Glassdoor. “How Much Does a Data Modeler Make  https://www.glassdoor.com/Salaries/data-modeler-salary-SRCH_KO0,12.htm." Accessed April 4, 2022.

Written by Coursera • Updated on

This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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