Data Literacy - Data vs Information

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What Is Data?

Data is raw facts, numbers, or records without meaning on their own
Data often comes directly from systems, sensors, forms, or transactions
On its own, data does not answer questions or support decisions
Data quality issues exist before interpretation even begins

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What Is Information?

Information is data that has been processed, organised, or interpreted
Information answers a question or supports a decision
Context, definitions, and structure turn data into information
Information depends on purpose and audience

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Context Changes Meaning

The same data can mean different things in different contexts
Time period, units, and filters shape interpretation
Business rules define what data actually represents
Missing context leads to wrong conclusions

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Data Does Not Equal Insight

Large volumes of data do not guarantee understanding
Insight requires interpretation, comparison, and explanation
Charts can still show raw data instead of information
Insight comes from relevance, not volume

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Structure Creates Information

Grouping, sorting, and aggregating add meaning
Consistent definitions ensure shared understanding
Good models help data become information faster
Poor structure hides information inside noise

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Decisions Depend on Information

Decisions should be based on information, not raw data
Information reduces uncertainty and risk
Clear information builds trust with stakeholders
Misinterpreted data leads to poor decisions

Best Practices for Turning Data into Information

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Always Define the Question

Start with what decision or question needs to be answered. This guides which data matters and how it should be shaped. Without a clear question, data exploration becomes noise rather than insight.

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Add Context Before Visuals

Include time frames, units, and definitions before showing numbers. Context prevents misinterpretation and aligns understanding across audiences.

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Standardise Definitions

Agree on what key terms mean, such as revenue, active customer, or churn. Consistent definitions ensure data becomes trusted information across reports.

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Summarise Before Detailing

Lead with summaries and trends before drilling into detail. This helps users understand the story before exploring raw data.

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Validate Information Outputs

Check that information aligns with expectations and known benchmarks. Validation ensures transformations did not introduce errors or misleading results.

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Design for the Audience

Different audiences need different information, even from the same data. Tailor aggregation level, language, and framing accordingly.