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Sep 2 • 6 tweets • 3 min read
Hello Data Analyst,

Have you heard of the acronym ALM?
(Application Lifecycle Management)

It is a process that enables you to design, build, test, & distribute BI reports effectively & efficiently.

Let's go over the six main stages. Use the acronym ADDTDM to remember them.
1. Analysis – Gather & analyze business requirements to define the report's goals. Clarify the problem statement & the analysis's purpose.

Struggling with this? See some useful questions to guide you in my previous post.

2. Design – Plan, prepare your data, create the data model and user interface for the report.

Don’t know what a data model is and its benefits? Check this previous post.
3. Development – Create visuals, reports and dashboards. Usually in a dev environment.

Need a guide in creating your visuals? Check this previous post.

and this for guide for creating a dashboard
4. Test & Integration – Verify that the report meets the stakeholders' requirements without errors.

5. Deployment – Publish the report to the target environment where it will be used

6. Maintenance – Maintain the report & keep an eye out for security flaws & poor performance.
These stages essentially summarize your role as a data analyst.

Cheers 🥂 to your growth.

#ALM #DataAnalytics #Data

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More from @Magnanimo_s

iReuby Profile picture
Aug 23
Hello Data Analyst,

I know how difficult it can be to ask the right questions that will generate the key insights you need to solve a problem or make a data-driven decision.

Here are 20 key questions to help you understand and solve problems with data.
1. Why was I asked to review this? – Problem Statement/Purpose

2. What does the product/process do? – Domain knowledge

3. Where are we now? – Actual Performance

4. Where should we have been? – Plan/budget

5. Did we achieve what we planned to achieve? – Variance Analysis
6. Why did we not achieve what we planned to achieve? – Root cause analysis

7. Where are the gaps in our process/strategy? – Gap Analysis

8. What did we not consider before? – Gap Analysis

9. What has changed within this period? – Trend Analysis
Read 7 tweets
iReuby Profile picture
Aug 22
Hello Data Analyst,

Let's discuss data models & benefits of having solid data models.

One of a data analyst's key responsibilities is building a strong data model.

The term "Data Model" refers to the process of arranging data into tables based on relationships & groups...
...to minimize duplication and maximize efficiency.

By performing this task properly, you contribute to making it simpler for people to comprehend your data, which will make it simpler for both you and them to create useful reports and dashboards.
It is challenging to provide a set of guidelines for what constitutes a good data model because every piece of data is unique and is used in different ways.

A smaller data model is preferable because it will operate more quickly and be easier to use.
Read 5 tweets
iReuby Profile picture
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.
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.
Read 6 tweets
iReuby Profile picture
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 Profile picture
Aug 15
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.
Read 5 tweets
iReuby Profile picture
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 Nigeria's Headline Inflation Between Jan - Jun 2022
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

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