{"id":41774,"date":"2023-02-27T02:42:55","date_gmt":"2023-02-27T10:42:55","guid":{"rendered":"https:\/\/www.springboard.com\/blog\/?p=41774"},"modified":"2025-01-27T04:37:35","modified_gmt":"2025-01-27T12:37:35","slug":"become-data-modeler","status":"publish","type":"post","link":"https:\/\/www.springboard.com\/blog\/data-science\/become-data-modeler\/","title":{"rendered":"How To Become a Data Modeler: 2025 Career Guide"},"content":{"rendered":"\n

You can think of data modelers as being the unsung heroes of the data science process. While methods of collecting, analyzing, and interpreting data may get more attention, none of this can be done if the data isn\u2019t organized and retrievable, and that\u2019s exactly what data modelers do. <\/p>\n\n\n\n

If you\u2019ve got an aptitude for organization, and are considering a career in data science, then you should definitely be considering a career in data modeling. If that sounds like you, then look no further. Our 8-step guide covers everything you need to know about a career in data modeling\u2014 from educational requirements to essential skills and average salaries\u2014so that you can launch your career today. <\/p>\n\n\n\n

What Does a Data Modeler Do?<\/h2>\n\n\n\n

A data modeler is a database designer, someone who maps out the optimal way for an organization\u2019s data to be stored. Using a variety of skills, data modelers work with stakeholders and other IT professionals to create solutions that make data easier to access, understand, and analyze. <\/p>\n\n\n\n

Is It Hard To Become a Data Modeler?<\/h2>\n\n\n\n

Becoming a data modeler is possible for anyone willing to put in the work. With encouraging growth prospects<\/a> and plenty of openings, there are many opportunities for newly trained juniors to land their first entry-level role. There are also different paths into the industry other than a standard college education. <\/p>\n\n\n\n

How To Become a Data Modeler: An 8-Step Guide<\/h2>\n\n\n\n
\"How<\/figure>\n\n\n\n

If you\u2019re interested in becoming a data modeler, there\u2019s a lot to do before you land your first job. However, the first step is one of the easiest\u2014just open up your laptop and choose a way to study.<\/p>\n\n\n

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  1. \n

    Learn the Basics<\/p>\n

    <\/div>\n<\/li>\n
  2. \n

    Meet the Educational Requirements (and Continue Learning)<\/p>\n

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  3. \n

    Learn Popular Data Modeling Tools<\/p>\n

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  4. \n

    Develop and Hone the Essential Skills<\/p>\n

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  5. \n

    Find a Mentor<\/p>\n

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  6. \n

    Gain Practical Experience Through an Internship<\/p>\n

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  7. \n

    Remember: Your Network Is Your Net Worth<\/p>\n

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  8. \n

    Polish Your Resume, Start Applying for Jobs and Prepare for Each Interview<\/p>\n

    <\/div>\n<\/li>\n<\/ol>\n<\/div>\n\n\n\n\n\n\n

    Learn the Basics<\/h3>\n\n\n\n

    While studying a data-related field at college is still a great option, it\u2019s no longer the only one. Part of what makes the tech industry so accessible for new learners is the number of resources and training you can find online. <\/p>\n\n\n\n

    To learn the basics, you can study independently or take introductory online courses. You can also fast-track your education with online data science bootcamps<\/a>, analytics<\/a>, or engineering<\/a> bootcamps. With industry-leading curriculums and expert instructors, these bootcamps can take beginners to work-ready levels in under a year. <\/p>\n\n\n\n

    Meet the Educational Requirements (and Continue Learning)<\/h3>\n\n\n\n

    Most employers will want to see some form of education or certification of your skills before they employ you. If you\u2019re not attending college, you can do this by passing industry-standard certifications or graduating from a bootcamp, and creating a professional portfolio<\/a>.<\/p>\n\n\n\n

    The interview is where you\u2019ll show off your skills in full and actually land the job, but you\u2019ll still need to create a high-quality resume in order to get a job interview in the first place.<\/p>\n\n\n\n

    Learn Popular Data Modeling Tools<\/h3>\n\n\n\n

    Tools are an important part of a data modeler\u2019s skill set, and you\u2019ll use them on every project to create conceptual, logical, and physical data models. Not everyone uses the same software, so it\u2019s good to familiarize yourself with multiple tools so you can appeal to more employers.<\/p>\n\n\n\n

    Structured Query Language (SQL)<\/h4>\n\n\n\n
    \"how<\/figure>\n\n\n\n

    SQL<\/a> skills are a must for anyone working with data, as it\u2019s a standardized programming language that\u2019s used to access, manage, and manipulate data in relational databases. You can use it to execute queries against a database, retrieve data, delete or insert new data, and many other tasks. <\/p>\n\n\n\n

    Related Read: 10 Best SQL Certifications To Grow Your Skillset<\/a><\/em><\/p>\n\n\n\n

    erwin Data Modeler<\/h4>\n\n\n\n
    \"how<\/figure>\n\n\n\n

    The erwin Data Modeler<\/a> has been a staple piece of software in the industry for over 30 years and is trusted by a number of Fortune 500 companies. It helps data modelers automate complex tasks and reduce errors in their designs so they can produce high-quality conceptual, logical, physical, and relational models more efficiently. <\/p>\n\n\n\n

    ER\/Studio<\/h4>\n\n\n\n
    \"how<\/figure>\n\n\n\n

    The ER\/Studio<\/a> suite includes a range of products for data modeling, conceptual modeling, and business glossaries. It allows data architecture teams to design and implement data solutions from start to finish while keeping the information accessible across the whole organization. <\/p>\n\n\n\n

    Lucidchart<\/h4>\n\n\n\n
    \"how<\/figure>\n\n\n\n

    Lucidchart<\/a> is a streamlined and collaborative diagramming application that can be used to visualize technical systems, among other things. Teams can use it to create conceptual data models that grow and improve as more members contribute to it. It\u2019s used by 99% of Fortune 500 companies. <\/p>\n\n\n\n

    Develop and Hone the Essential Skills<\/h3>\n\n\n\n

    Whether you\u2019re studying independently or with an institution, a good way to develop a sense of the crucial skills you need for data modeling is to read job descriptions. This way, you can see exactly what skills and tools companies expect.<\/p>\n\n\n\n

    Technical Skills<\/h4>\n\n\n\n

    Technical skills and knowledge are very important for data modelers, as you need to know both how to build data models, and how to design systems on a large scale. Technical requirements you\u2019ll often see on job descriptions include:<\/p>\n\n\n\n