Data integration

What is meant by Data integration?

Data integration refers to the process of combining data from different sources into a unified, usable format. The goal of data integration is to create a consistent and comprehensive view of the data, which can be used for analysis, reporting, and business processes. This is particularly important in organizations that need to consolidate data from various departments, systems, or external sources.

Typical software functions in the area of "data integration":

1. Data Extraction:

   • Extracting data from various sources such as databases, APIs, files, and cloud services.
   • Support for different formats and protocols.

2. Data Cleaning:

   • Identifying and correcting errors or inconsistencies in the data.
   • Removing duplicates and aligning data formats.

3. Data Transformation:

   • Converting data into a unified format or schema.
   • Aggregating, normalizing, and computing new data values.

4. Data Merging (Integration):

   • Combining data from different sources into a consistent data collection.
   • Matching and merging records based on common keys or attributes.

5. Data Loading:

   • Loading the integrated data into a target system such as a data warehouse, database, or analytics tool.
   • Supporting various loading methods like batch and real-time processing.

6. Data Monitoring and Management:

   • Monitoring data integration processes to ensure data quality and integrity.
   • Managing data integration jobs and troubleshooting errors.