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iReuby

Aug 15 • 5 tweets • 2 min read

Hello Data Analyst,

A soft skill you should develop is problem-solving.

How do one solve a problem if one can’t identify the root cause?

There are many root cause analysis tools. In this thread, I have shared my 3 favourite ways of identifying the root cause of a problem.

1. 5 WHYs: Asking “Why” multiple times to drilldown to the root cause of the problem. Recall diagnostic analytics.

E.g. Manchester United lost again last week 😭. Why? The players were uncoordinated, and defense was weak. Why?... Why?...

2. By asking the question “When does it happen and when does it not happen?”

E.g. I can’t make a call with my phone.
Can I make a call when I insert my SIM in another device? If yes, that means the fault is from my phone and not the network provider.

3. Scatter plot diagram: To uncover if there’s a relationship between the suspected causes and the problem.

E.g. My profit is shrinking. What’s the relationship between the discount amounts I give to boost cash sales and the bottom line?

Overall, when trying to identify the root cause of a problem, stand back and scrutinize the system as a whole & not in silo.

Please feel free to share how you identify problem sources to enrich the thread.

🥂

#Problem_Solving #RootCauseAnalysis

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More from @Magnanimo_s

iReuby

@Magnanimo_s

Aug 18

Hello Data Analyst,

Let’s talk about #dashboards.

They assist you to share insights effectively to guide decision makers.

If done with care, they are visually appealing & tell insightful stories about the data.

10 things you should bear in mind when designing a dashboard...

1. Design for a target. Who will use the dashboard? What are their needs? Do the insights in the dashboard address the needs?

2.Pick the right charts.

See my previous tweet on visualization.

https://twitter.com/Magnanimo_s/status/1558438891807555587?s=20&t=kIr7h9k_7fzKova8IbLS7A

3. Keep it simple. How easy is it to access key insights? Leave out the noise.

4. Keep everything at a glance. Don’t overcrowd the dashboard. Enhance accessibility.

5. Show important context – Filters, tooltips, chart titles, descriptions etc.

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iReuby

@Magnanimo_s

Aug 16

Hello Data/Business Analyst,

You know how frustrating change of requirements from stakeholders can be.

Besides following a clear change management process, developing mental agility will boost your efficiency and overall productivity.

What is mental agility?

Mental agility is the ability to think and apply insights quickly from one context to another.

In simpler terms, it is how well your mind can quickly adjust to new conditions/ideas.

Thankfully, your mental agility can be improved.

Use these 5 simple ways to get started.

1. Be curious. Ask “Why” & “What If”.
2. Read, observe & listen. Read widely & learn to listen to understand not to reply.
3. Be less defensive. Have an open mind.
4. Schedule time to meditate & think.
5. Gain domain knowledge. This helps to understand other possible use cases.

Read 4 tweets

iReuby

@Magnanimo_s

Aug 13

Hello Data Analyst,

Let’s talk about visualization.

Your visuals should convey messages to users in an effective & efficient way.

Try to strike a balance btw creating a beautiful visual & having an informative visual.

Thread contains recommendations 4 some use cases.

1/17

1. Changes over time. E.g. Last month, you entered a supermarket and saw someone screaming “God abeg” and you ask your data analyst friend… “What was Nigeria’s headline inflation from Jan – Jun 2022?”

Need: To display changing TREND of measures (prices).

2/17

Changes over time (contd.)

Recommendations: Line chart (my favourite), Area chart, Sparkline by OKViz, Card with States by OKViz, you could also try a combination of column chart and line chart if you have different sets of values.

3/17

Read 17 tweets

iReuby

@Magnanimo_s

Aug 12

Hello Data Analyst,

Are you aware of the 5 types of analytics?

In the order of increasing difficulty & value:

1. Descriptive Analytics: Answers questions about what has happened. E.g. Man Utd lost to Brighton last weekend. The match ended 1-2 in favour of Brighton.

1/5

2. Diagnostic Analytics: Helps answer questions about why things happened. E.g. Man Utd lost the game because the players made mistakes on the ball & organisation mistakes in defending.

2/5

3. Predictive analytics: Helps answer questions about what will happen in the future. E.g. Despite the first loss, current issues in the dressing room & with the quality of players and coaching, Man Utd will finish top 4 in this season’s EPL.

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iReuby

@Magnanimo_s

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Hello Data Analyst,

Are you looking for free and structured Excel resources to learn data analysis?

Use below links from #ExcelIsFun to improve your knowledge. In 6 hours, you are done with all videos.

1.Introduction: