Data Analytics for Business: Data Storytelling as a Financial Analyst

Data Analytics for Business: Data Storytelling as a Financial Analyst

In the last three editions of the Data Analytics for Business at The FinData Lake Newsletter, we discussed three important questions in the workplace: (1)How to incorporate Data-Driven Change, (2)How Data Can Improve Business Revenue, and (3)Data Analytics for Business: Data Modeling Variations. We’ve focused on the aspect of changing business environments and how we can utilize internal decision support systems and their benefits to organizations, as well as primarily discussing the five key indicators that guarantee returns through the implications of data analytics on your business workflow, as well as discussing the difference between different data modeling techniques, where we have Descriptive, Diagnostic, Predictive, and Prescriptive Analytics Modeling.


The role of the financial analyst has changed significantly in recent years, as technology has made it more and more important to understand how data can help you make better decisions. Now, one of the most important skills for a financial analyst is storytelling: understanding how to present data findings in ways that will keep your audience engaged and help them truly understand what those findings mean for their business. In this article, we’ll explore why data storytelling matters and how you can incorporate it into your work as a financial analyst.


Data storytelling is a new approach to presenting data. It’s not quite the same as traditional storytelling — you can’t create an arc or plot and characters with data, but you can take an interesting pattern and give it context, which makes it more relatable and easier to understand.

It’s easy to see why this would appeal to financial analysts. As a group, they need to understand complex information quickly and make decisions based on that information before anyone else in the company has had time to digest it all. In addition, they often have little room for creativity because their reports are created by someone else (usually called “the client”).


Presenting data findings is an essential part of the data storytelling process. It’s a critical step in the cycle, because you can’t expect to make an impact on your clients or stakeholders if you don’t communicate effectively. In order to effectively communicate, it is important that you use visual elements such as charts and graphs when presenting data.

It’s also important for you to understand the challenges that your audience may have with understanding information presented through charts or graphs. For example, some people may not be familiar with certain types of charts and graphs, so it would be helpful if they could get help from someone who understands them better than they do (i.e., yourself).

In this section, we’ll go over some tips on how to present your findings more efficiently and effectively by using visual elements like charts and graphs that are easy for everyone — including those less familiar with them — to understand at a glance!


As a data analyst, you will be responsible for collecting, analyzing, and reporting on data. You will work with your team to analyze the available information in order to solve business problems. This can include interpreting data and presenting your findings to decision-makers. In addition, you may also be responsible for recommending solutions to the identified problem based on your analysis of the available information.


Data storytelling can be an effective way to tell a story that is relevant to your audience.

Incorporating data into your work can help you better explain the impact of changes in financial performance and provide insight into what’s driving those changes. Data visualization is one way of communicating this information, as it allows users to quickly scan and process large amounts of information. Visualizations should focus on providing context and understanding rather than just presenting raw numbers, which will help ensure that the right messages get across.

For example, in one financial model that we built in the past for a private organization, it was demanded to have certain questions answered regarding multiple demographic and financial details that have to be addressed on a daily basis, we had to ask certain questions that would determine the outcome of the dashboard needed, such as:

  1. How will this information be presented afterward?
  2. To whom will it be shown?
  3. Is there a threshold for the amount of information presented?
  4. Does the model have to be static or dynamic?
  5. Will the model have to include values from multiple sources?
  6. Is there a possibility to redesign the current database structure?

All of these questions were asked to avoid double-work and hassle through the data visualization model creation process. to avoid wasted time and to ensure the efficiency of the analyst’s working hours.


Here’s an example of a social media post that visualizes a categorical percentage.

When it comes to representing data visually, there are a wide variety of options.

  • Graphs: One of the most common ways to visualize data is through graphs. You can use bar graphs, line graphs, and scatterplots (or bubble charts).
  • Maps: If you have spatial data that you want to represent on a map, there are several different types of maps you can choose from. You can use choropleth maps if you want to show differences between regions or states; cartograms if you want people’s attention drawn to specific geographic areas based on some other variable (e.g., population density); and dot-density maps if you want viewers’ attention drawn toward particular areas (e.g., high crime rates).


The human element is an important part of data storytelling. People-centered design (PCD) is a design philosophy that focuses on the needs of the people using the product or service. PCD helps you make better decisions, take advantage of opportunities, and build better products by understanding how people interact with your brand or business.

There are many benefits to understanding how your customers feel about their product experience with your company:

  • You can easily boost customer satisfaction and loyalty by improving areas such as ease of use, aesthetics, and personalization when it comes to interactions with your brand.
  • You can more easily identify opportunities for growth by examining user behavior patterns and identifying areas where users may need additional support.

One of the factors that you MUST avoid is an intentional misrepresentation of data, showcasing an upward trend on a monthly basis to deceive whoever is viewing the data model that you created while having an actual downward trend on an annual scale.



When you’re working in financial services, storytelling is a powerful tool for sharing your findings with others. In fact, it’s essential that you learn how to combine storytelling with data analysis if you want to make an impact at your job.

The goal of data analysis is to turn raw information into something meaningful and actionable — that is, something that can be used by decision-makers. This means that what we need are stories that help people understand why certain decisions are being made or trends are developing. For example: if there’s a rise in mortgage fraud activity, one person may tell a story about the number of cases reaching record levels over the past six months; another might tell a more personal tale about how an elderly couple had their house robbed by someone who posed as their grandson online; still, another might write about how he used technology from his bank (and some good detective work) to track down where all this money was going after he noticed suspicious activity on his account.

When you create such stories using real-life examples from your organization’s products or services — and especially when those stories can be corroborated with data — you’ll find that they resonate with audiences more than any other kind of presentation could.

There are two great books that I strongly recommend for you to start your journey of acquiring the correct skill-set as a data analyst/scientist for the data visualization part by the one and only Cole Nussbaumer Knaflic:

  1. storytelling with data: a data visualization guide for business professionals
  2. storytelling with data: let’s practice!

Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You’ll discover the power of storytelling and how to make data a pivotal point in your story. The lessons in this illuminating text are grounded in theory but made accessible through numerous real-world examples — ready for immediate application to your next graph or presentation.

This bundle is a strong weapon for every Data Analyst/Scientist that wants to truly showcase their data visualization skills to the next level.


Data storytelling is an effective tool for financial analysts to communicate and engage with clients. It can be used to find insights and present information in a compelling way that’s easy for your audience to understand. When you combine data analysis skills with storytelling abilities, you’ll have a powerful combination that could lead to success on your job.

You can follow up on the data storytelling soft skill set over at my post, which discussed the Top 5 Must-Have Soft Skills for Data Scientists/Analysts.


Tell me what you think is demanded from financial analysts nowadays. What can be improved further from your point of view? Do you think that the applicability of changing your organization’s culture would be possible for the greater good?

About me

I’m an articulate Finance Analytics and Business Intelligence expert with more than five years of progressive and continuous experience in the BI and decision-making fields and project management, as well as four years of experience in the finance sector. personable with strong knowledge and experience in Operations, Risk, Data Analytics & Visualization. I am helping financial institutes and directors to perform accurate financial data analysis and analytics that will benefit in volume, growth, brand, and profits; and mitigate associated risks with taken actions.

➡️For more content like this, subscribe to this newsletter, and please follow me on LinkedIn. Let’s grow together and share our insights and knowledge with a broader audience! ⬅️



⚡Risk Advanced Analytics Expert | Specialized in identifying, analyzing, and mitigating potential risk through Advanced Data Analysis | 👨🏻‍🏫 Instructor

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
Ahmed ElShamy, FMVA®, CBCA®, BIDA™, CFA®IF

⚡Risk Advanced Analytics Expert | Specialized in identifying, analyzing, and mitigating potential risk through Advanced Data Analysis | 👨🏻‍🏫 Instructor