Data Analysis and Data Modelling - What's the difference?

Nowadays, we are seeing an increase in data-related analysis skills in business analysis jobs. Some data skills are crucial 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.

We take a look at the set of skills required for both data analysis and data modeling, investigate how data modeling can require some data analysis, and detail how skilled business analysts complete this level of analysis without technical data analysis skills.

What is Data Analysis?

Data analysis is a technique to gain insight into an organisation’s data. A data analyst might have the following responsibilities:

  • To create and analyse important reports (possibly using a third-party reporting, data warehousing, or business intelligence system) to help the business make better decisions.
  • To merge data from multiple data sources together, as part of data mining, so it can be analysed and reported on.
  • To run queries on existing data sources to evaluate analytics and analyse trends.

Data analysts will have hands-on access to the organisation’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 mathemetical experience.

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 analysing a specific type of data or using a specific type of tool to analyse data.

What is Data Modelling?

Data modeling is a set of tools and techniques used to understand and analyse how an organisation should collect, update, and store data. It is a critical skill for the business analyst who is involved with discovering, analysing, and specifying changes to how software systems create and maintain information.

What does a Data Modeller do?

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

A data modeller would not necessarily query or manipulate data or become involved in designing or implementing databases or data repositories.

Data Modeling sometimes needs Data Analysis

BA's often need to analyse 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. This is why you may see a technical skill like SQL in a business analyst job description.

Many BA's succeed without knowing these more technical skills, instead, they rely on their ability to collaborate with technical professionals and other knowledgeable stakeholders to ensure the data is understood well enough to make the right modelling decisions.

The non-technical BA can also evaluate sample data, interview stakeholders to discover possible data-related issues, review current state database models, and analyse exception reports.

While data analysis skills are valuable for the business analyst, they are not essential. However, data modelling falls squarely within the business analyst’s domain.





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