📌 Data Enrichment Summary

Data enrichment is the process of improving or enhancing raw data by adding relevant information from external sources. This makes the original data more valuable and useful for analysis or decision-making. Enriched data can help organisations gain deeper insights and make more informed choices.

🙋🏻‍♂️ Explain Data Enrichment Simply

Imagine you have a list of names and phone numbers, but nothing else. Data enrichment is like looking up more details about each person, such as their address or job, so your list becomes much more helpful and complete. It is similar to adding more pieces to a puzzle, so you can see a clearer picture.

📅 How Can it be used?

A business can enrich customer records with social media profiles to personalise marketing campaigns more effectively.

🗺️ Real World Examples

An online retailer enriches its customer database by adding demographic data, such as age and location, from third-party providers. This helps the company send targeted promotions and improve customer segmentation.

A financial institution enhances its transaction records by appending credit scores from external agencies, which helps in assessing loan applications more accurately and reducing risk.

✅ FAQ

Data enrichment is about taking basic information and making it more useful by adding extra details from other sources. This helps organisations see a clearer picture, make smarter decisions, and spot new opportunities they might have missed with plain data.

By adding relevant information to your existing data, you get a fuller understanding of your customers, markets, or operations. This means you can make choices based on complete and up-to-date facts, which often leads to better results and fewer surprises.

A shop might add customer location details to their sales records to see where their products are most popular. Or a bank could enhance its account data with credit scores to offer better services. These extra layers of information make the original data much more useful.

📚 Categories

• Data Engineering
• Data Governance
• Data Science

🔗 External Reference Links

Data Enrichment link

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