tomi.

@__B0rnSinner got raptured ||
Jack of all trades, master of all || ex MUFC💔 || Dreamer

[tomi. @arduinounoboy]

Fell in love with you and I almost died.

[tomi. @arduinounoboy]

Now paying direly for the sin of not using these no-see alibis

[tomi. @arduinounoboy]

Where’s the fun in forever anyway

[tomi. @arduinounoboy]

Why when you wipe the mist that naturally drops from the eyes, they keep streaming down?

[tomi. @arduinounoboy]

Light a Roman candle with me.

[tomi. @arduinounoboy]

@BukkyOA Congrats Oreoluwa

[tomi. @arduinounoboy]

Little trust issues so just serve my jollof with the stew.

[tomi. @arduinounoboy]

@DabereNnamani Happy birthday Annie

[Ibukun Amosu 🇳🇬🇬🇭 @amosuibk]

Senior Java Software Engineer Job at Mintyn Digital Bank

Location: Lagos (Hybrid)

Requirements:
Must have international Passport for Traveling
Minimum of 5 years of hands-on software development experience with Java and Spring Boot.
Strong proficiency in both Spring WebFlux (Reactive) and Spring MVC frameworks.

Apply 👇

[J.A Olaoye @JA_Olaoye]

Having tons of reports does not make an organization data-driven.

A company can have hundreds of dashboards and still make decisions based on:

Gut feeling
Seniority and opinions
Politics
“We’ve always done it this way”

Being data-driven means:

✅ Decisions start with a business question.
✅ Data is trusted and accessible.
✅ Metrics are agreed upon.
✅ Leaders actually change actions based on insights.
✅ Reports lead to decisions and outcomes.

A lot of organizations suffer from reporting overload:

200+ reports
Thousands of KPIs
Nobody knows which number is correct
The same metrics calculated differently everywhere
Reports opened once and never again

That’s not being data-driven. That’s creating noise.

I often say:

Reports are outputs. Decisions are outcomes.

A data-driven organization measures itself by the quality and speed of its decisions, not by the number of dashboards it produces.

This is why Data Governance and Data Ownership matter so much. Without them, reports become expensive decorations.

A good executive dashboard should answer only three questions:

What happened?
Why did it happen?
What should we do next?

Everything else is usually just noise.

[Oreoluwa Bukola, CFA. @BukkyOA]

Got this exact question in my community yesterday and these are my thoughts:

First, stop trying to feel calm. You won’t. The nerves are not the problem. The problem is walking in unprepared so the nerves run the show.

Don’t memorise answers. You’ll forget them the second they word the question differently. Pick a few real stories from your own work and know them well. You won’t forget things that actually happened to you.

Keep one cheat sheet page for yourself for quick revisions. Not full answers. Just a few words to jog your memory, two or three numbers that show what you’ve done, and two questions to ask them. When your mind goes blank, one word brings it all back.

Sort your body out, not your head. Breathe out slower than you breathe in. Warm your hands up before you go in. Your body calms down faster than your thoughts will.

It’s okay to pause. Say “great question, then give yourself some 2-3 secs as though you are thinking of the answer” Sitting in silence for a moment makes you look senior. Rushing to talk will put your articulation at risk.

And honestly, remember who these people are. They’re strangers. They don’t feed you. You don’t owe them anything. You’re not there to beg them to pick you, you’re there to see if you even want them. Once you stop performing for people you don’t know, half the fear goes.

The last bit from me is your physical carriage will inform your mind. If you sit and then cross your legs for instance, your brain immediately thinks: Oh, this is a friendly conversation and it is responds to you that way. But if you sit uptight, it signals formality and challenge. So tell your brain through your posture the kind of experience you want.

That’s it. You don’t really get rid of the anxiety. You just walk in ready enough that it can’t take over.

[𝗠𝘂𝗵𝗲𝗲 ♛ @muheediva01]

Does anyone actually have a friend they’ve known for 25+ years?

[tomi. @arduinounoboy]

I wish and pray you flourish as you have potential for.

[J.A Olaoye @JA_Olaoye]

If your goal is to land a data engineering job by December 2026, here’s the self-taught path.
Without talks, just the order that actually works:

[J.A Olaoye @JA_Olaoye]

I remember a time when I learned that data is far more than dashboards.

I was working for a pay-as-you-go gas company as the BI Manager. Our typical responsibilities were building dashboards, sharing insights, and developing the data infrastructure that other teams depended on.

Then a major business problem surfaced.

Whenever our payment gateway provider experienced an outage, customer payments would fail to clear automatically in our system.

The consequences were painful:

• Customers had paid but could not access their gas.
• Customer Service was flooded with calls.
• The official resolution time was 24 hours.

Think about that.

Many customers used the last money they had for the day to buy gas, only to be told to wait until tomorrow before they could cook.

I spoke with the infrastructure team and discovered something important.

The payment data actually existed.

The provider’s records showed successful payments, but Customer Service had no access to that information and therefore could not help customers until the gateway recovered.

So I built a solution.

I connected directly to the raw payment data in Amazon S3 using AWS Glue, pulled the information into Amazon QuickSight, and developed a lookup tool based on our business rules.

The result?

- Customer Service could immediately verify payments and manually resolve cases while the gateway was still experiencing issues.

- Resolution time dropped from 24 hours to approximately 5 minutes.

The impact was so significant that the Customer Experience team continued using the tool even when systems were operational but experiencing delays.

That experience taught me something I will never forget:

Data professionals do not just build reports.

We remove friction.
We restore trust.
We solve business problems that directly affect people’s lives.

[J.A Olaoye @JA_Olaoye]

A beginner sees:

Airflow
Kafka
Spark
Databricks
Snowflake
Flink
dbt, and a ton of other tools to be learned.

A mentored learner sees:

How do I get data?
How do I clean it?
How do I store it?
How do I serve it?
How do I trust it?
How do I scale it?

The tools change every few years.

The principles don’t.

If I were advising a beginner today, I’d focus on only:

Phase 1 (80% of jobs)

SQL(PostgreSQL, SQLServer, MySQL…)
Python
Git
Data Modeling
ETL/ELT
Power BI/Tableau

Phase 2

Cloud (AWS or Azure)
Data Warehouse (Snowflake, or BigQuery)
Airflow

Phase 3

Spark
Kafka
Databricks

Everything else can wait until a real business problem demands it.

The fastest way to become a Data Engineer is not learning 50 tools.

It’s building 5 real projects that move data from Point A to Point B and generate business value.

That’s how careers are built. Not by collecting tool logos like Pokémon cards. 😄

[tomi. @arduinounoboy]

@JA_Olaoye True intelligence requires consciousness really

[tomi. @arduinounoboy]

@Daddyboyy8 @seyikanbai 😂😂😂😂

[tomi. @arduinounoboy]

@cheftee_lead Gat no gym for haterz has me

[tomi. @arduinounoboy]

@ThaBoyYom Some persons will say mentality

[tomi. @arduinounoboy]

And would you say you’re living?