Meaning to combine data from multiple sources into a unified dataset while ensuring consistency and resolves conflicts from merging.

• Schema Integration : making sure that the format and structure of data are the same across all sources.
• Entity Identification : linking together entries that represent the same thing, even if they have different names.

In other words, it can be said that in many cases, entity identification happens before schema integration.

1. First, you need to know which data points from different systems refer to the same real-world entities (entity identification).
2. After that, ensure the structure, format, and naming conventions are the same across those matched entities (schema integration).

Status: #idea
Tags: data-miningData Mining* [x] data-mining-uts-quiz knowdledge discovery in databases data-warehousing schema 400 400 400 Apriori Algorithm 400 Step 1: Count Distinct Items 400 400 400 400 Step 2: Identify Association Rules 400 400 400 400 FP Growth Algorithm Step 1: Count Distinct Items 400 Step 2: Rearrange Items based count in descending order 400 Step 3: Make FP Growth Tree 1. Make Null Root Node 1. And make children sequentially 400 400 400 400 400 400 400 400 400 400, kddkdddata-prepartion data mining pattern-evaluation knowledge-presentation Status: #idea Tags: data-mining References, data-prepartiondata-prepartionproperly preparing the data to ensure that it is clean, consistent, and ready for analysis. data-cleaning data-integration data-transformation data-reduction Status: #idea Tags: data-mining, kdd References

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