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By the Grace of Data

businessbybusiness
October 11, 2022
inHowTo
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data tips
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As a Data, Insight and Root Cause Analyst, you will be tempted to commit one of the biggest flaws of data presentation: throwing Numbers to Your Audience Instead of Telling a Story. Mostly because it’s easier, cheaper and much less time consuming.

If you’re interested in ways of overstepping this common pitfall, continue reading for some few tips.

1. Data always has three themes: SETUP, CONFLICT and RESOLUTION. Always look out for a running theme in your data.

2. Data is stored in categories: TIME, USE, DEMOGRAPHICS. Be sure to run comparisons by either breaking it down or spreading it through.

3. Data has its focal point: KEY POINT OF INSIGHT. Identify the focal point, reduce the noise and then link all other inherent points toward the focus.

4. Data visual presentation should contrast: SIZE, COLOR and ORIENTATION. This is a very efficient way of providing snapshots and especially when looking at high-level insights and or Executive Summaries.

5. Data presentation should be consistent: CATEGORIES and VARIABLES. Say, if your story is about models of cars, ensure there is consistency in what color to give to, say AUDI, throughout the lifetime of the analysis.

6. Data makes sense with the right chart: PIE, BAR, COMBO. Ensure you have an intimate knowledge of your data, its trends, focus and comparative nodes. These will help in identifying which chart to use.

7. Data should be interactive: HISTORIC, PROJECTIVE, DEEP-DIVE and SELF SERVICE. Presenting your data in an interactive way leaves it to the endlessness of its use and the insights it provides to its audience and consumers.

Remember, data should tell a story and not just present a fact.

Thank you for reading through to this point. Will be giving more helpful tips in data analysis soon.

Original article published on: https://theaugustdispatch.com/2022/09/17/by-the-grace-of-data/

By: Francis Stephen Martinson

PhD Candidate – Software and Security Engineer
Interests: Machine Learning, Data Science, Cloud Computing, Software Engineering
Honor Societies: Phi Kappa Phi, Phi Theta Kappa – Beta Mu Rho

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Source: The August Dispatch
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