Data modeling is an important part of business intelligence that requires the support of skilled professionals. Learn more about what they do.
Databases are central to the operations of many organizations today. However, before developing and utilizing a database, it is crucial to undertake data modeling operations, making necessary adjustments and changes to database designs.
In many cases, this task is handled by a data professional called a data modeler. The following guide offers an explanation of what data modeling means, what a data modeler does, and what it takes to become one, so you can assess whether it is a fitting career path for you.
What is a data modeler?
Data modeling refers to the process of evaluating, organizing, measuring and managing data in particular business processes. It is the documentation of a software system design as a diagram that is easy to understand. Data modeling enables you to conceptually represent data and the relationships between rules and data objects. It can also be used for reverse-engineering efforts to extract models from existing systems.
A data modeler is a computer systems engineer with expertise in these data modeling practices. This is a system analyst who works alongside data architects and database administrators to design computer databases. The data modeler role is also heavily involved with data management policies that support organizational data structures.
SEE: Job description: Big data modeler (TechRepublic Premium)
As a result, data modelers are vital to an organization achieving its goals in almost all areas of operation. They are tasked with designing and managing data systems that are architecturally sound enough to reinforce the goals of an organization. Data modelers collaborate with other IT professionals in an organization to model vital data that will heavily direct not only the decision-making of an organization but also customer experience processes.
Data modeler job responsibilities
The overall responsibility of a data modeler is to design databases that improve the usability and effectiveness of how organizations access and utilize their data. Breaking down this role into further responsibilities, a data modeler:
- Identifies the needs of a business and develops data models that fit these needs
- Helps in defining databases and the physical, logical and conceptual levels involved
- Participates in improving business activities by using their knowledge of data flows to present and implement innovative data solutions
- Maintains the data models they create and defines data modeling and design standards
- Maintains data maps
- Identifies data modeling tools, relevant development techniques and standards for an organization
- Takes responsibility for the evaluation of existing data systems
- Develops best practices around data coding and standard naming conventions, making sure data models are consistent
- Evaluates databases and data models for inconsistencies and variances, ensuring data is represented correctly
- Troubleshoots and optimizes data systems
- Presents optimization and standardization recommendations for various information systems in an organization
- Carries out reverse-engineering of physical data models
- Updates and optimizes metadata and local models
How can you become a data modeler?
Before you can take on the responsibilities of a data modeler, it’s important to develop the prerequisite skills and experience for the role:
Data modelers are required to possess a variety of skills that include but are not limited to:
- Hands-on experience with relational and physical data modeling
- Understanding of platform technologies
- Experience with data warehouses and big data platforms
- Understanding of data modeling principles, such as logical and conceptual data models
- Proficiency in using business intelligence tools to represent insights
- Understanding of how to translate relational data models into XML
- Experience in database administration and software development
- A foundational knowledge of mathematical concepts and statistical analysis
- Experience with data modeling tools like Power Design and erwin
- Knowledge of metadata management and related tools
- Practical experience with SQL and programs such as Microsoft Word, Excel and PowerPoint
For individuals who want to pursue a data modeling career, a bachelor’s degree in data science, computer science, information technology, information science, applied mathematics or a related field will likely be required. Some organizations or roles may require a more advanced degree, such as a master’s degree in a relevant discipline.
Education aside, hands-on work experience cements your credibility as a data professional. Your work experience may not be in a data modeling role, but having experience in related areas, such as data design and data management, may boost your eligibility for data modeling positions.
Certifications and additional training
Relevant certification programs are an effective way to certify your competence and boost your skills for data modeling roles. Some helpful data modeling certifications and trainings include the following:
Though it’s not compulsory, combining skills, education, work experience, certifications and further training will increase both your eligibility and your visibility when it comes to open data modeler roles. To learn more about what it takes to become a data modeler—or to hire an effective data modeler—take a look at this big data modeler job description from TechRepublic Premium.