Often used interchangeably, data modeling and data analytics evaluate separate components of data. Data modeling requires setting parameters on data to better understand it. Rather than seeking to understand the meaning of data, modeling only seeks to shape data into a usable form to help visualize company strategy. On the other hand, data analysis considers the data itself, allowing you to make informed business decisions. Here are some distinguishing qualities between modeling and analytics.

How Data Mining Helps Business

Modeling considers what data a company should take into account and discerns the useful from the unhelpful. Also, data modeling informs a company about how to view high-level concepts about the organization, which is even more essential later with analytics. During the data modeling process your company could:

  • Draw up a data dictionary to set data requirements based on the company
  • Generate a data map to clean the data and discover missing or duplicate fields, which ensures all the data you have is useful
  • Create an Entity Relationship Diagram (ERD) to visualize how business concepts interact with one another within your company’s information systems

data modeling and analytics boardroom meeting

Next Steps: Data Analysis

Frequently, data analysis requires a more human touch and less artificial intelligence than modeling. After developing a predictive model of the data, analysis can begin to evaluate the main takeaways that your data shows. This means customizing measurements and reports to view overarching patterns and recognizing their relevance. With data analytics, you might:

  • Run reports on the data to inform your company on strategies moving forward
  • Manipulate data to see patterns across data points and sources to tell a story

Although separate parts of the data process, modeling and analysis share gray areas. For example, while data modeling utilizes a more technical approach to the data, some human intuition helps to evaluate relevant data and eliminate unhelpful information. Likewise, knowing what problem you want to solve during the analytics process can help determine how you set up the data modeling.

Both processes benefit from experienced experts who have dealt with modeling and analytics before. AnswerOn’s nearly 20 years of experience in the world of data lends itself well to understanding how to model and how to analyze data. To learn more about how we create predictive data models or how we analyze data, reach out to us today or download a case study.