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. We’ve been asked several times whether business intelligence and business analysis roles are really different roles, and how to build a career path into business analysis without getting wrapped into business intelligence and data analysis.

(By the way, if you are looking to learn more about data modeling, be sure to check out our Free Data Modeling Training.)

In this video, we’re going to pick apart the difference between data modeling and data analysis, and give you a clear view as to when each skill set is required as you plan out your business analysis career path.


For those who like to read instead of watch, here’s the full text of the video:

Today I want to talk about data analysis and data modeling in business intelligence roles and data related requirements in business analysis roles. So, it’s a big topic, but we’re really just going to hit the key points.

We’ve been receiving a ton of questions at Bridging the Gap about how to define a career path in business analysis. Is data analysis required? Is the role being overcome by business intelligence roles? And, really, the key to interpreting what’s happening in the job market, as well as defining where you want to go in your business analysis career, comes down to the distinction between data modeling and data analysis. Let’s talk about what those mean and then look at what it means for you in your business analysis career.

Data Analysis Evaluates the Data Itself

First, is data analysis. Let’s talk about what that means.

Data analysis is evaluating 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. That kind of skill set definitely takes some business acumen. You have to understand what the data means to the business.

But it also takes a lot of technical skills. You need to know whatever database system your organization uses, you need to be able to use those queries. A lot of times, somebody in that kind of role is using a data warehouse or business intelligence system to run those reports. So, you would need to know the ins and outs of that system to use it effectively to tell a story with the data.

Data Modeling Evaluates How an Organization Manages Data

Data modeling evaluates how an organization manages data. On a typical software project, you might use techniques in data modeling like an ERD (entity relationship diagram), to explore the high-level concepts and how those concepts relate together across the organization’s information systems.

You might create a data dictionary that details, field by field, what are the pieces of information we need to store in this database to meet the software requirement features or to implement this business process change.

You might create a data map that shows how we’re going to move data from one system to another, or how we’re going to integrate and make those systems talk to each other on an ongoing basis to make a feature or business process available to our community.

Data Modeling Can Require Some Data Analysis

Here’s where it gets tricky. 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.

However, there’s a lot of technical professionals, or a lot of business analysis professionals, myself included, who don’t know SQL or don’t use it regularly. You think maybe they know it but aren’t granted access to the database. That comes up too. You have to rely on some other skills to get that information.

For me, it’s been a lot about collaborating with the technical professionals asking questions. Sometimes asking for sample data so they can create a dump of some of the records in a spreadsheet format that I could review and look for so I could find potential data mapping or modeling issues. I’m able to analyze the data without having to know how to analyze the data in the database itself. That’s where we start to see a little bit of the overlap, and there’s some confusion.

It’s Not Uncommon to Find Combined BI/BA Roles

A reason there’s some confusion is because there’s this increased abundance of roles that are really combined business intelligence experts with business analysis roles. The competencies that we just talked about, while they are separate skill sets, they really do go hand-in-hand. If you can model the organization’s data and analyze that data to create more intelligence inside the business, that’s a powerful skill set. We’re seeing a lot of roles pull those two things together sometimes.

You can learn more about business intelligence analysis roles in this video:

A lot of times these roles also have the business analyst job title, which just adds to the confusion. You’ll look at it and it’s, “Oh, it’s a business analyst.” “Oh, wait, this is more of a business intelligence analyst. Why isn’t it given the business intelligence analyst role?” That’s just because business analyst job titles are used in multiple different ways, not just here, but in particular here in this area where it can be really confusing when you’re first looking at job descriptions.

It is a very popular growing field to have a business intelligence area of expertise. It doesn’t mean that you have to have it to succeed as a business analyst. We’re still seeing a lot of more general functional business analysis roles out there, and, so, it’s a choice you can make if you are really into that kind of thing for sure. Business intelligence is a ripe field with a lot of career potential. But if you’re not, there are still going to be opportunities for you.

Regardless, data modeling is an important competency to have because you need that if you’re working on a business intelligence project. You need it if you are implementing any kind of software or business change to make sure those information systems are really capturing and storing the right data to meet that end business need that you’re trying to get to with your project.

So this has been a crash course on some different data-related skills and why we see some confusion in the business analysis job marketplace. Hit me up with any questions about this by leaving a comment below.

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