Data Analysis for Business Analysts: How to Read It, Interpret It Honestly, and Make Better Decisions

DAY 1 | Why Every Business Analyst Needs to Be Comfortable With Data

I want to start with an admission that took me a while to be comfortable making. For the first few years of my career, I avoided data. Not consciously. I would not have described it that way at the time. But when a project involved numbers, I gravitated toward the parts that did not. I was comfortable with process, with requirements, with stakeholders, with documentation. When a report full of figures landed on my desk, I would summarise what it appeared to say and move the conversation back to the areas I felt confident in. It worked, in the sense that nobody called me out on it. But it limited me in a way I did not fully understand until a project sponsor handed me a performance report in a meeting and asked me, directly, what it meant. I gave a vague answer about what the chart was showing. He pressed. What does it mean for the business case? Is the trend reliable or is it noise? Should we be concerned? I did not have answers. I could read the chart. I could not interpret it. And in that moment, in front of the person whose confidence I most needed, the gap between reading data and understanding it became very visible. That gap is the subject of this week.

The Data Confidence Gap

There is a belief among some Business Analysts that data analysis belongs to someone else. To the data analysts, the data scientists, the reporting team, the people with the technical tools and the statistical training. There is some truth in it. Advanced data work - building predictive models, running complex statistical analysis, engineering data pipelines - is a specialist discipline that most BAs neither need nor should attempt. This week is not about turning you into a data scientist. But there is a level of data competence that sits well below data science and well above what many BAs are comfortable with. The ability to read a dataset and understand what it is actually telling you. The ability to spot when a number is being presented in a misleading way. The ability to ask the right questions of a report before you build a recommendation on top of it. The ability to use data to support an analytical judgement rather than decorating a conclusion you had already reached. This level of competence is not optional for a modern Business Analyst. It is core to the role. And the BAs who avoid it are limiting their effectiveness and their careers in ways they often do not recognise.

Why Data Matters More Than Ever for BAs

The role of the Business Analyst has always been to help organisations make better decisions. For much of the history of the profession, the BA did this primarily through process analysis, requirements work, and stakeholder facilitation. Data was part of the picture, but it was rarely the centre of it. That has changed. Organisations now generate and store more data than they have ever been able to use. Decisions that were once made on experience and judgement are increasingly expected to be evidenced with data. Stakeholders bring dashboards to meetings. Business cases are challenged on the strength of their numbers. The BA who cannot engage with data on equal terms is increasingly sidelined from the conversations that matter most.

This is not a trend that is going to reverse. The expectation that decisions are evidenced with data is becoming the baseline, not the exception. And the Business Analyst sits at exactly the point in the organisation where data needs to be translated into decisions. That is the BA's natural territory. But only if the BA is comfortable enough with data to occupy it.

Reading Data Versus Understanding It

The distinction at the heart of this week is the difference between reading data and understanding it. Reading data is describing what is in front of you. This chart shows sales going up. This table shows three regions. This figure is higher than that one. Reading data is a literacy skill. Most professionals can do it to some degree. Understanding data is something else. It is knowing whether the trend the chart shows is real or an artefact of how the data was selected. It is knowing whether the comparison between two figures is fair or whether they are measuring different things. It is knowing what the data does not show, what has been left out, what assumptions are baked into how it was collected and presented. It is knowing whether you should trust the number enough to make a decision on it.

A BA who can read data can produce a summary. A BA who understands data can produce a judgement. The organisation does not need more summaries. It needs judgement. And judgement is what this week is designed to build.

The Honest Interpretation Problem

There is a dimension of data work that matters more for Business Analysts than almost any other professional group, and it is the one I want to flag clearly at the start of this series because we will return to it on Wednesday. Data can be made to say almost anything. The same dataset, presented in different ways, can support opposite conclusions. A chart with a truncated axis can make a tiny change look dramatic. A carefully chosen time period can turn a long-term decline into a short-term recovery. An average can hide a distribution that tells a completely different story.

Most of the time, this is not deliberate deception. It is the natural result of people looking at data through the lens of what they already believe or what they want to be true. The marketing team presents the data that supports the campaign. The operations team presents the data that justifies the resource request. Everyone is being honest in their own mind, and everyone is presenting a partial picture. The Business Analyst's role is to be the person in the room who interprets data honestly. Who notices the truncated axis. Who asks about the time period. Who checks whether the average is hiding something. Who is willing to say that the data does not actually support the conclusion that everyone wants it to support.

This is one of the most valuable things a BA can do, and it is also one of the most difficult, because it often means telling people something they do not want to hear. We will spend Wednesday on exactly this.

The Career Cost of Avoiding Data

The BA who avoids data pays a cost that compounds over time. In the short term, they hand over the most influential part of many conversations to someone else. When data is on the table, and the BA cannot engage with it confidently, the analytical authority in the room shifts to whoever can. The BA becomes the person who documents the decision rather than the person who shapes it.

In the medium term, they get excluded from the work that is increasingly central to the profession. Data-informed decision-making is becoming the core of how organisations operate. A BA who cannot participate in it fully is a BA whose scope is quietly shrinking. In the long term, they cap their own progression. Senior BA roles, and the programme and consulting roles beyond them, require the ability to engage with data as a peer to anyone else in the room. The BA who never built data confidence finds that the ceiling arrives earlier than it needed to. None of this requires becoming a data scientist. It requires becoming data confident. And that is an achievable goal for any Business Analyst willing to spend a week building the foundations.

What This Week Covers

Over the next five days, we are going to build practical data competence from the ground up.

• Day 2: Reading data. The foundations every BA must master, including the types of data, the measures that matter, and how to read a dataset properly before you start drawing conclusions from it.

• Day 3: Interpreting data honestly. The traps that mislead, the techniques people use to make data say what they want, and how to be the person in the room who sees through them.

• Day 4: From data to decision. How to turn numbers into analytical judgement, how to present data so it informs rather than manipulates, and how to build a recommendation that data genuinely supports.

• Day 5: The Data Analysis Toolkit. A practical reference guide to everything in this series, with a free downloadable resource to use on your next data-informed project.

Go out and be successful.

Oluwatosin Ogunkoya | Flotog BA Insights | www.flotogbainsights.com

Tomorrow: Reading Data. The foundations every BA must master before drawing a single conclusion. Types of data, the measures that actually matter, and how to read a dataset properly.