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Difference Between Data Modeling and Data Analysis

Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. it applying statistical or logical techniques to describe and illustrate, condense and recap, and evaluate data. An essential component of ensuring data integrity is the accurate and appropriate analysis of research findings.

Data modeling is the process of creating a data model for the data to be stored in a Database. This data model is a conceptual representation of. Data objects. The associations between different data objects. it defines how the logical structure of a database is modeled. DataModels are fundamental entities to introduce abstraction in a DBMS. Data models define how data is connected to each other and how they are processed and stored inside the system.

Difference Between Data Modeling and Data Analysis

Data Analysis evaluates the Data Itself. It’s doing things like running reports, customizing reports, creating reports for business users, using queries to look at the data, merging data from multiple different sources to be able to tell a better and more informed story than when you look at each source independently.
Data analysts will have hands-on access to the organization’s data repositories and use their technical skills to query and manipulate the data. They may also be skilled in statistical analysis, having a high-level of mathematical experience. A data analyst job responsibilities

  • Create and analyze meaningful reports 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.

Data Modeling evaluates How an Organization Manages Data. you might use techniques in data modeling like an ERD, to explore the high-level concepts and how those concepts relate together across the organization’s information systems. BA’s often need to analyze data as part of making data modeling decisions, and this means that data modeling can include some amount of data analysis. A lot can be accomplished with very basic technical skills, such as the ability to run simple database queries. A data modeler job responsibilities

  • 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.

Data modeling requires a little bit of data analysis. In order to say this field is going to map to this field in a systems integration project, you probably need to look at the data and understand how the data is put together. This is why we see some job descriptions requiring concepts or technical skills like SQL because if you know SQL and can query the database, it’s a little bit easier to be able to research that information and figure it out for yourself using a little bit of data analysis to inform your data models.