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Data Integration

What is Data Integration?

Data integration is:

  1. The agreement and documentation of data representation, format and structure across all the organisation’s data sources going forward,
  2. Mapping of data from existing sources, using the new schema, to the new system/s.

What We Do>

We analyse all your data sources, data sharing policies and data reporting obligations, and model a unified data structure that is agreed upon all the data stakeholders.

We create a data model and data dictionary that document the new schemas and all the data items that would be used.

If the data integration process is undertaken as part of a systems integration process, we map data from the existing sources to the new system/s. Otherwise, we plan for the implementation of the changes within the existing system/s.

As part of the Data Cleaning process, we remodel your existing data to match the new schema.

What does Data Integration Remedy?

Historical Use of Disparate Systems

Issue: Existing data resides in different systems (such as accounting software, Excel Sheets, old databases, bulk mailing tool, etc.), denying users a unified view of the data.

Consequence: Each user only sees part of the picture, and data must be updated in multiple places in order to maintain accuracy.  

Heterogeneous Data Sources

Issue: Multiple data collection points, for example, online registration or subscription forms, different paper forms, referrals from related organisations and more, utilise different data definitions, option values and interpretations of the data.

Consequence: Lack of uniformity in the data collected makes it impossible to compare or aggregate the data and turn it into useful information.

Data Collection Silos

Issue: Data relating to same or similar entities is collected in information silos across the organisation.

Consequence: Frustration for the user who has to deal with each silo as if it were a separate organisation. Difficulty in aggregating the data and turning it into useful information.

Discrepancies between Data Collected and Data Reported

Issue: Data collected schema is different to data schema required for reporting.

Consequence: Need for time consuming re-work of data for each reporting period.