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You're an investment banker. How can you create data visualizations that wow your clients?

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As an investment banker, you know that data is the key to making smart and profitable decisions for your clients. But data alone is not enough. You also need to communicate your insights and recommendations in a clear, compelling, and convincing way. That's where data visualizations come in. Data visualizations are graphical representations of data that help you tell a story, highlight trends, and reveal patterns. In this article, you'll learn how to create data visualizations that wow your clients and set you apart from the competition.

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Aishwarya Acharya

Finance & Operations | ex-VMWare | ex-Ripple | ex-JPMorgan IB
CA Deepak Garg

CA | CPA | EY | Ex-KPMG | Ex-Ministry of Commerce | Management Consultant
Christian M. D?hnert, FRM, CGA, CGE, CFP?

Estratégia Segmento PF @ Sicredi

1 Choose the right type of visualization

Not all data visualizations are created equal. Depending on your purpose, audience, and data, you need to choose the right type of visualization that suits your message. For example, if you want to show the distribution of a variable, you can use a histogram, a box plot, or a density plot. If you want to show the relationship between two variables, you can use a scatter plot, a line chart, or a correlation matrix. If you want to show the composition of a whole, you can use a pie chart, a donut chart, or a stacked bar chart. The key is to select the visualization that best illustrates your point and avoids confusion or misinterpretation.

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CA Deepak Garg

CA | CPA | EY | Ex-KPMG | Ex-Ministry of Commerce | Management Consultant
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To create data visualizations that impress clients, it's essential to choose the right type of visualization that effectively communicates key insights. Start by understanding the specific data you want to present and the story you want to tell. Consider the audience's preferences and level of understanding when selecting the visualization type. For financial data, options like line charts for trend analysis, bar charts for comparing values, and pie charts for illustrating proportions are often effective. Interactive dashboards can also engage clients by allowing them to explore data dynamically. Utilize colors, labels, and annotations to enhance clarity and highlight important points.

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Aishwarya Acharya

Finance & Operations | ex-VMWare | ex-Ripple | ex-JPMorgan IB
(已编辑)
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Understanding your audience is key in investment banking data visualization. Senior executives often prefer succinct summaries highlighting key metrics and strategic insights, while others may need detailed analyses like in-depth cash flow and market comparisons. Tailoring visualizations to audience expertise ensures relevance and accessibility, possibly requiring different visuals for various meetings to effectively engage and inform each group.

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2 Use colors, labels, and annotations wisely

Colors, labels, and annotations are essential elements of data visualizations that can enhance or detract from your message. You should use colors to highlight important information, create contrast, and convey meaning. For example, you can use red and green to indicate positive and negative performance, or use a color scale to show the intensity of a value. You should also use labels and annotations to provide context, explain concepts, and emphasize key findings. For example, you can use labels to show the names and values of data points, or use annotations to add notes, comments, or questions. However, you should avoid using too many colors, labels, or annotations that can clutter your visualization and distract your audience.

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3 Make your visualizations interactive and dynamic

One way to make your data visualizations more engaging and persuasive is to make them interactive and dynamic. Interactive visualizations allow your audience to explore the data by filtering, zooming, or selecting different options. Dynamic visualizations allow your audience to see how the data changes over time or under different scenarios. For example, you can create an interactive dashboard that lets your clients see the performance of different sectors, regions, or companies. Or you can create a dynamic chart that shows how the market value of a target company changes based on different valuation methods. By making your visualizations interactive and dynamic, you can provide more depth, flexibility, and customization to your clients.

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Christian M. D?hnert, FRM, CGA, CGE, CFP?

Estratégia Segmento PF @ Sicredi
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As vizualiza??es dinamicas ajudam o público a focar exatamente na informa??o que faz mais sentido pra ele, permitindo maior personaliza??o.

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4 Use storytelling techniques to connect with your audience

Data visualizations are not only tools to present data, but also to tell a story that captures the audience's attention, interest, and emotion. To do this well, you must use storytelling techniques such as setting the context and providing the background, motivation, and goal of your analysis. Additionally, building the plot by showing data, analysis, and results in a logical sequence is necessary. Creating the climax by highlighting the main takeaway or recommendation is also important. Finally, adding a resolution to summarize key points or benefits is essential. Through these techniques, you can make your data visualizations more memorable, meaningful, and impactful.

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Christian M. D?hnert, FRM, CGA, CGE, CFP?

Estratégia Segmento PF @ Sicredi
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Quanto mais conectada for a história contada com as experiências dos cliente, mais forte será o engajamento e aten??o ao que será trazido.

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5 Use the best tools and platforms to create and share your visualizations

When creating and sharing data visualizations, it is important to use the best tools and platforms. Excel, PowerPoint, Tableau, Power BI, R, and Python are some of the most popular and powerful ones. Excel offers basic charts and graphs, as well as pivot tables and slicers. PowerPoint can insert and edit charts and graphs, as well as add animations and transitions. Tableau is a data visualization software that can create interactive and dynamic dashboards, charts, and maps. Power BI is a business intelligence software that can create interactive and dynamic reports, dashboards, and charts. R is a programming language that can create advanced and customized visualizations as well as perform statistical and analytical functions. Python is also a programming language that can create advanced visualizations as well as perform data manipulation and machine learning tasks. Depending on your needs, preferences, and skills, you can select the tool or platform that works best for you or combine different tools to create comprehensive solutions.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Aishwarya Acharya

Finance & Operations | ex-VMWare | ex-Ripple | ex-JPMorgan IB
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Before finalizing my data visualizations for presentations, I always make it a point to review them with my colleagues. This step is essential to ensure that the visuals clearly and effectively communicate the intended message. My colleagues, with their diverse perspectives, can spot potential areas of confusion or misinterpretation that I might have missed. They often provide valuable feedback on aspects like color choices, chart simplicity, and the logical flow of information. By incorporating their suggestions, I can enhance the clarity and impact of my visualizations, ensuring that they not only accurately represent the data but also resonate well with the target audience in my presentations.

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You're an investment banker. How can you create data visualizations that wow your clients?

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1 Choose the right type of visualization

2 Use colors, labels, and annotations wisely

3 Make your visualizations interactive and dynamic

4 Use storytelling techniques to connect with your audience

5 Use the best tools and platforms to create and share your visualizations

6 Here’s what else to consider

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