What are some real-world examples of data heterogeneity?

What are some real-world examples of data heterogeneity?

Data heterogeneity refers to the differences in data types, formats, and sources. For example, in healthcare, patient data can come from various sources like electronic health records, wearable devices, and lab results, each with different formats.

Can you give more examples from different industries?

Sure! In finance, data heterogeneity can be seen in transaction records, market data, and customer profiles, which may vary in structure. In retail, customer data from online and in-store purchases can differ significantly.

How does data heterogeneity affect data analysis?

Data heterogeneity can complicate data analysis by making it challenging to integrate and compare data from different sources. It often requires specialized techniques to harmonize the data for accurate insights.

What techniques are used to handle data heterogeneity?

Common techniques include data normalization, data integration frameworks, and the use of machine learning algorithms that can handle diverse data types.