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Integrate

Selecting the right data pipeline tools

Data integration is the process of combining data from different sources and formats to create a unified and consistent view of the data. This involves merging data from multiple databases, applications, and other sources into a single repository, and transforming and formatting data so that it can be easily accessed and analyzed. Data assets need quality controls to ensure they are valid and reliable as many teams within an organization leverages the same data for different purposes.

Understanding the Necessity of ETL in Data Integration

In today's data-driven world, businesses are constantly generating vast amounts of data, which can provide valuable insights into their operations and customers. However, before data can be analyzed and used for decision-making, it often needs to be cleaned, transformed, and organized in a way that makes it usable. This is where ETL comes in.

The 1, 2, 3, of cleansing data

Most organizations experience some level of data quality challenge. Solving data quality challenges and cleansing data can exist in three ways: Data at source: requires business owners and subject matter experts to ensure data quality at the point of entry. It becomes important to identify what data quality issues exist, and identify ways to ensure a certain level of quality before any ETL/ELT takes place.