Data Literacy Checks — 10 LinkedIn Posts

Data Literacy Check #01

❓ Ask the Right Question

Data Literacy Check #01: Ask the Right Question

Data literacy begins before the chart.

Business problem:
People often ask for a report before defining the decision.

Literacy check:
Ask:
What decision are we trying to make?
Who will use this?
What action could change?
What does success look like?

Common mistake:
Starting with the visual instead of the question.

BI impact:
A dashboard without a decision becomes decoration.

Key idea:
A good question creates a useful analysis.

More practical resources:
https://jobaqui.com
https://hialeahoficios.com
https://miamioficios.com

#DataLiteracy
#BusinessIntelligence
#DataAnalytics
#DataCulture
#PowerBI
#DecisionMaking
#LearningByDoing

Data Literacy Check #02

📘 Understand the Metric

Data Literacy Check #02: Understand the Metric

A metric is only useful when people understand what it means.

Business problem:
Different users may interpret the same KPI differently.

Literacy check:
For every metric, define:
name
formula
source
filters
time period
owner
limitations

Common mistake:
Assuming the metric name explains the metric.

BI impact:
Conflicting interpretations reduce trust.

Key idea:
Do not read a number without reading its definition.

More practical resources:
https://jobaqui.com
https://hialeahoficios.com
https://miamioficios.com

#DataLiteracy
#BusinessIntelligence
#DataAnalytics
#DataCulture
#PowerBI
#DecisionMaking
#LearningByDoing

Data Literacy Check #03

⚖️ Compare Fairly

Data Literacy Check #03: Compare Fairly

Not all comparisons are fair.

Business problem:
Two departments, cities, programs, or products may operate under different conditions.

Literacy check:
Ask:
Are the groups similar?
Are volumes different?
Should we compare rates instead of totals?
Is the time period the same?
Is context missing?

Common mistake:
Ranking totals without adjusting for size.

BI impact:
Unfair comparisons create unfair conclusions.

Key idea:
Compare like with like.

More practical resources:
https://jobaqui.com
https://hialeahoficios.com
https://miamioficios.com

#DataLiteracy
#BusinessIntelligence
#DataAnalytics
#DataCulture
#PowerBI
#DecisionMaking
#LearningByDoing

Data Literacy Check #04

🔗 Correlation Is Not Causation

Data Literacy Check #04: Correlation Is Not Causation

Two things moving together does not prove one caused the other.

Business problem:
A chart may show a relationship, but the reason may be different.

Literacy check:
Ask:
Could another factor explain this?
Did one event happen before the other?
Is there evidence beyond the chart?
Could this be coincidence?

Common mistake:
Turning correlation into a story too quickly.

BI impact:
Bad causal claims lead to bad decisions.

Key idea:
A pattern is a clue, not proof.

More practical resources:
https://jobaqui.com
https://hialeahoficios.com
https://miamioficios.com

#DataLiteracy
#BusinessIntelligence
#DataAnalytics
#DataCulture
#PowerBI
#DecisionMaking
#LearningByDoing

Data Literacy Check #05

📈 Read Trends Carefully

Data Literacy Check #05: Read Trends Carefully

A trend can tell a story, but only if the timeline is understood.

Business problem:
Short time periods can exaggerate change.

Literacy check:
Ask:
What period is shown?
Is seasonality involved?
Was there a one-time event?
Is the scale misleading?
Is the baseline clear?

Common mistake:
Overreacting to one spike or drop.

BI impact:
Executives may make decisions based on noise.

Key idea:
Look for patterns, not panic.

More practical resources:
https://jobaqui.com
https://hialeahoficios.com
https://miamioficios.com

#DataLiteracy
#BusinessIntelligence
#DataAnalytics
#DataCulture
#PowerBI
#DecisionMaking
#LearningByDoing

Data Literacy Check #06

🧮 Watch the Denominator

Data Literacy Check #06: Watch the Denominator

Percentages need denominators.

Business problem:
A 50% increase sounds big, but from 2 to 3 cases may not be operationally meaningful.

Literacy check:
Always ask:
50% of what?
How many records?
Is the sample large enough?
Are counts shown with percentages?

Common mistake:
Showing percentages without counts.

BI impact:
Small numbers can create big misunderstandings.

Key idea:
Percentages need context.

More practical resources:
https://jobaqui.com
https://hialeahoficios.com
https://miamioficios.com

#DataLiteracy
#BusinessIntelligence
#DataAnalytics
#DataCulture
#PowerBI
#DecisionMaking
#LearningByDoing

Data Literacy Check #07

🎛️ Understand Filters

Data Literacy Check #07: Understand Filters

Filters change the story.

Business problem:
A dashboard may show different results depending on hidden filters, slicers, or default selections.

Literacy check:
Ask:
What is included?
What is excluded?
Are dates filtered?
Are inactive records removed?
Are blanks excluded?

Common mistake:
Reading a dashboard without checking filters.

BI impact:
Users may compare screenshots that are not based on the same data.

Key idea:
Before trusting a chart, inspect the filters.

More practical resources:
https://jobaqui.com
https://hialeahoficios.com
https://miamioficios.com

#DataLiteracy
#BusinessIntelligence
#DataAnalytics
#DataCulture
#PowerBI
#DecisionMaking
#LearningByDoing

Data Literacy Check #08

🚨 Recognize Outliers

Data Literacy Check #08: Recognize Outliers

Outliers can be errors or important signals.

Business problem:
Extreme values can distort averages and trends.

Literacy check:
Ask:
Is this value real?
Is it a data entry issue?
Should it be explained?
Should median be used instead of average?

Common mistake:
Deleting unusual values without understanding them.

BI impact:
One extreme value can change the narrative.

Key idea:
Investigate outliers before judging them.

More practical resources:
https://jobaqui.com
https://hialeahoficios.com
https://miamioficios.com

#DataLiteracy
#BusinessIntelligence
#DataAnalytics
#DataCulture
#PowerBI
#DecisionMaking
#LearningByDoing

Data Literacy Check #09

🕒 Know the Data Delay

Data Literacy Check #09: Know the Data Delay

Freshness matters.

Business problem:
A report may refresh today using data that stopped updating last week.

Literacy check:
Ask:
When was the report refreshed?
When was the latest business event?
How often does the source update?
Is there a known delay?

Common mistake:
Confusing report refresh date with data freshness.

BI impact:
Decisions may be made using stale information.

Key idea:
Always ask how current the data really is.

More practical resources:
https://jobaqui.com
https://hialeahoficios.com
https://miamioficios.com

#DataLiteracy
#BusinessIntelligence
#DataAnalytics
#DataCulture
#PowerBI
#DecisionMaking
#LearningByDoing

Data Literacy Check #10

🚀 Turn Insight Into Action

Data Literacy Check #10: Turn Insight Into Action

Data literacy ends with action.

Business problem:
People may understand the chart but still not know what to do next.

Literacy check:
Ask:
What changed?
Why does it matter?
Who needs to act?
What are the options?
What should be monitored next?

Common mistake:
Stopping at “interesting.”

BI impact:
Insights without action do not create value.

Key idea:
The goal is not to see data. The goal is to decide better.

More practical resources:
https://jobaqui.com
https://hialeahoficios.com
https://miamioficios.com

#DataLiteracy
#BusinessIntelligence
#DataAnalytics
#DataCulture
#PowerBI
#DecisionMaking
#LearningByDoing