Question

In a data pipeline, what is the mandatory step taken to transform heterogeneous raw logs from multiple platforms into a uniform format before predictive analysis can occur?

Accepted Answer

The mandatory step is normalization. Normalization is the process of restructuring data from disparate sources into a consistent format, schema, and set of values. Heterogeneous raw logs refer to data generated by different systems or applications that use unique structures, such as varying timestamps, field names, or coding styles. Without normalization, predictive analysis models cannot process the information because they require structured, uniform input to identify patterns accurately. For example, if one platform records a timestamp as DD/MM/YYYY and another as YYYY-MM-DD, a normalization step converts both into a singular ISO 8601 standard format. This ensures that every piece of data is comparable, readable, and ready for ingestion into analytical tools or machine learning algorithms.

In a data pipeline, what is the mandatory step taken to transform heterogeneous raw logs from multiple platforms into a uniform format before predictive analysis can occur?

The mandatory step is normalization. Normalization is the process of restructuring data from disparate sources into a consistent format, schema, and set of values. Heterogeneous raw logs refer to data generated by different systems or appli....

Community Answers

Home → All Courses → Education Courses → Learning Technology Engineering → Flashcard

In a data pipeline, what is the mandatory step taken to transform heterogeneous raw logs from multiple platforms into a uniform format before predictive analysis can occur?

The mandatory step is normalization. Normalization is the process of restructuring data from disparate sources into a consistent format, schema, and set of values. Heterogeneous raw logs refer to data generated by different systems or appli....

Community Answers