Comparing Data Modelers to Data Scientists
Data modelers create the outline for the databases data scientists will use to make sense of vast quantities of information. Readers will learn about the differences between these two professions, including their degree requirements, salaries, career outlooks, and typical responsibilities.
|Job Title||Educational Requirements||Median Salary (2017)*||Job Growth (2016-2026)**|
|Data Modelers||Bachelor's Degree||$80,969||9% (Computer Systems Analysts)|
|Data Scientists||Master's Degree||$91,423||19% (Computer and information Research Scientists)|
Sources: *PayScale, **U.S. Bureau of Labor Statistics
Responsibilities of Data Modelers vs. Data Scientists
Data modelers and scientists share the ultimate goal of making data useful to companies. Whether dealing with ecommerce data related to product sales or shipping information, or collecting data on human genetics, these professionals make it possible for organizations to turn raw data into information that can be interpreted and used to make business decisions. Data modelers develop the rules and labels used in a database, streamlining the collection and input of data. Data scientists, however, find patterns in the database using computer software they typically develop themselves.
By developing a model, or a kind of road map, to explain the nature of the content and the rules governing a database, data modelers help a company track information. These professionals determine which data will be collected, where to gather it from, and how often it will be collected. They also explain how the data will be used by employees. All of this information is submitted by data modelers in a document that teaches users how to implement the data model. When building a physical database design, these modelers label the columns and data elements to keep them standardized within the company.
Job responsibilities of a data modeler include:
- Reverse engineering data from previous sets to better understand established models
- Meeting with end users and executives to understand any corporate data standards
- Bringing data from various systems and departments together, making the data more accessible
- Testing the physical model to ensure it is intuitive
Data scientists develop algorithms that help them find patterns in large amounts of data. In fact, they use new analytical techniques, including machine learning, which is similar to artificial intelligence that allows the computer to run algorithms and recognize patterns. Some also use SAS and Python programming languages to build computer programs that can help store data. Financial transactions, patient information, and computer traffic to a website all create data that these professionals work with. To find the meaningful data that actually demonstrates something about a company or its customers, data scientists scrub away the unnecessary information.
Job responsibilities of a data scientist include:
- Determining which data should be saved based on what is informative in regards to the company goals
- Looking for errors in the data results
- Creating visual representations of the data, such as charts, to make the results simple to understand
- Understanding statistics and distribution patterns within information
For anyone considering a career as a data modeler, you may also think about a possible future as a computer information systems manager because both use technology to address the needs of a company. For those who may want to become a data scientist, you could look into a position as a database administrator, as both deal with information storage.