What is a Data Modeler and is it a Good Career Choice?

What is a Data Modeler and is it a Good Career Choice? | Data Science and Analytics | Emeritus

With a projected 9% increase in employment opportunities between the years 2021 and 2031, a data modeler is one of the highest in-demand roles in today’s data-driven world. Today, more and more businesses are converting their existing data models to Non-Structured Query Language (NoSQL) platforms, such as MongoDB, to make data more understandable. Becoming a data modeler, therefore, requires expertise in Relational Database Management Systems (RDBMSes), data warehouses, and the Online Analytical Processing Server (OLAP) model. However, knowing the basics is essential. In this article, you will get to know what is a data modeler, what the job entails and details on the required skills. 

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What is a Data Modeler?

Data modelers are system analysts who collaborate with data architects and database administrators to design computer databases. Their responsibility involves ensuring that business data is maintained effectively and optimized to help achieve business goals.

They are at the forefront of data management measures that ensure organizational data structures become more efficient. 

These system analysts enable firms to accomplish their objectives by using the data modeling process in almost every aspect of the business. This includes customer experience and helping in product development.

Importance of Data Modeling

You must possess extensive technical skills if you want to excel in a data science and analytics career. Processing individual data sets is the primary objective of data modeling as it is not possible or appropriate to treat all data in the same manner. 

It is the responsibility of the data modelers to define how the data should be structured to guarantee that it satisfies the requirements of both the company and the target users of the product.

Utilizing the modeled data as a resource to accomplish corporate goals is yet another essential component of data modeling. These corporate goals include employee engagement, skill development, and improving the productivity of an organization.

Data management in databases and information systems is governed by predefined rules and guidelines. The process helps to ensure that the incorporation of data into the system is accurate. This data modeling stage also guarantees that the data is used and applied effectively and can be adapted to meet the requirements of stakeholders and end users based on information gathered through data modeling. 

Data Modeler Skills

It is essential to acquire the necessary knowledge and expertise to fulfill the requirements needed to for this role.

Core Skills

Organizations look for data modelers with the following core skills.

  • Knowledge about data modeling principles, such as conceptual, logical, and physical data models
  • Familiarity with the mathematical concepts that form the basis of statistical inference and forecasting, including time series analysis, multivariate analysis, cluster analysis, and optimization
  • Ability to express complicated technical ideas in a way that is easier for others to understand 

Advanced Skills

Some organizations look for advanced skills in a field. These include:

  • Experience in software development
  • Knowledge of and ability to use business intelligence tools such as Power BI to represent insights
  • Experience in converting and mapping relational data models into XML and schemas databases

The Data Modeling Process

Data modeling allows an organization to meticulously assess data processing and data storage in the system. Different data modeling methodologies follow different standards that specify how models are organized, how business needs are communicated, and which symbols are used to represent the data. All methods offer structured workflows that list a series of actions to be taken iteratively. 

Here is a list of steps that show how a professional conducts the data modeling process.

  • Identify the entities presented in the data set that is to be modeled
  • Find out the key properties of each individual entity
  • Establish the relationships among the entities
  • Create a comprehensive mapping of attributes assigned to entities
  • Assign keys (numerical identifiers to represent the relationship among entities) as required, and choose a level of normalization that strikes a balance between the need to cut down on redundancy and the demands placed on performance
  • Finalize and test the data model

ALSO READ: What is the Role of Data Scientists in the World of Big Data?

The Job Responsibilities of a Data Modeler

Data modelers have a wide array of responsibilities as they work toward their goal of designing and building useful databases. Some of the main responsibilities that data modelers undertake include:

1. Definition of Company Needs

Data modelers define the needs of the company’s employees and identify areas where data may be used to enhance business operations.

2. Strong Collaboration

Professionals in this job collaborate closely with database engineers to produce the most effective physical data models of data sets.

3. Definition of Modeling and Guidelines

Data modelers have to define and oversee data modeling and design guidelines for data modeling processes, tools (such as ER/Studio), best practices, and related data development techniques for an organization.

4. Data Management

This job requires the creation, maintenance, and management of data maps, as well as system interrelationship diagrams (a network map to identify the root cause of an issue). These diagrams are needed for data domains (such as employers of an organization and students in an institution) and data systems (such as information systems for students and assessment systems for employers).

Advantages and Disadvantages of Data Modeling

Advantages

  • It is helpful in identifying reliable sources of data that will be used to populate the model
  • It enables the company to document the data mappings that take place during the Extract, Transform, Load (ETL) process for data integration

Disadvantages

  • If you are interested in working in designing navigational systems, you need advanced data modeling skills as this requires complicated application development
  • Since data modeling involves the use of databases, it has the high impact of failure due to vulnerability 

How Much do Data Modelers Make?

As of January 26, 2023, a salary.com report states that the average salary for a data modeler in the U.S. is $94,280. However, the range of salaries typically falls between $82,980 and $106,090.

Is Data Modeler a Good Career Choice?

Data modeling is a rising field in the data science industry that is producing a significant number of employment opportunities. According to a U.S. Bureau of Labor Statistics report, approximately 11,500 job opportunities for data modelers are anticipated annually, on average, between 2021 and 2031. So, if you have an idea about what is a data modeler job and find it worth pursuing, you will be choosing a field that appears to be growing steadily.

Online data science courses by Emeritus. These programs will further enable you to learn more about the fields of data science, analytics, and management.

Write to us at content@emeritus.org

About the Author

Content Writer, Emeritus Blog
Mitaksh has an extensive background in journalism, focusing on various beats, including technology, education, and the environment, spanning over six years. He has previously actively monitored telecom, crypto, and online streaming developments for a notable news website. In his leisure time, you can often find Mitaksh at his local theatre, indulging in a multitude of movies.
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