The Difference Between Data Analysis and Data Modeling

The Difference Between Data Analysis and Data Modeling

In today’s information rich world, we are seeing more and more data-related analysis skills in business analysis jobs. Some data skills are critical for business analysts while others are better suited to other job functions, such as data analyst, financial analyst, reporting analyst, marketing analyst, and product management.

In this article, we’ll look at the set of skills required for both data analysis and data modeling, describe how data modeling can require some data analysis, and explain how skilled business analysts complete this level of analysis without technical data analysis skills.

Data Analysis Evaluates the Data Itself

Data analysis is a set of tools and techniques to gain insight from an organization’s data. A data analyst might hold the following job responsibilities:

  • Create and analyze meaningful reports (possibly using a third-party reporting, data warehousing, or business intelligence system) to help the business make better decisions.
  • Merge data from multiple data sources together, as part of data mining, so it can be analyzed and reported on.
  • Run queries on existing data sources to evaluate analytics and analyze trends.

Data analysts can be expected to have hands-on access to the organization’s data repositories and use technical skills to query and manipulate the data. They may also be skilled in statistical analysis and probably pursued some math classes in higher education.

Common alternative job titles for this type of role include Report Analyst, Data Warehousing Analyst, Business Intelligence Analyst, or even Product/Marketing Analyst. The common thread among this diverse set of job titles is that each role is responsible for analyzing a specific type of data or using a specific type of tool to analyze data.

Data Modeling Evaluates How an Organization Manages Data

In contrast, data modeling is a set of tools and techniques to understand and analyze how an organization should collect, update, and store data. Data modeling is a critical skill for a business analyst that is involved with discovering, analyzing, and specifying changes to how software systems create and maintain information.

A data modeler might:

  • Create an entity relationship diagram to visualize relationships between key business concepts.
  • Create a conceptual-level data dictionary to communicate data requirements that are important to business stakeholders.
  • Create a data map to resolve potential data issues for a data migration or integration project.

A data modeler would not necessarily query or manipulate data or be involved in designing or implementing databases or data repositories.

Data Modeling Can Require Some Data Analysis

You often need to analyze data as part of making data modeling decisions, and this means that data modeling can include an element of data analysis. You can accomplish a lot here with very basic technical skills, such as the ability to run simple database queries. This is one reason that you can see a technical skill like SQL in a business analyst job description.

To view the full article : http://www.bridging-the-gap.com/data-analysis-data-modeling-difference/

Learn more with PHI Learning’s MICROSOFT EXCEL 2019 : DATA ANALYSIS AND BUSINESS MODELING, Sixth Edition by Wayne L. Winston. Buy now Online:  https://www.phindia.com/Books/BookDetail/9789389347180/microsoft-excel-2019-winston

Data Analysis with Excel by Winston

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