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Concordia ®

A data delivery service that leverages a flexible, scalable data harmonization platform to solve complex cases of high volume, variety, and velocity.

The amount of time required preparing Big Data for predictive modeling and business intelligence is one of the big problems most companies face. In our experience, 70% of any analytics engagement is dedicated to data preparation.

For global companies with databases and data sources that vary by countries, getting a simple question answered like “how are we performing across the globe?” is very difficult for a brand manager. Furthermore, differences in data structures, currencies, and consumer behavior vary by country, meaning analytics developed from one country may not be relevant in another. Concordia solves this problem by harmonizing global data in weeks, in what would otherwise take months.

Fractal Analytics provides supervised automation services that perform data standardization routines for data cleansing, validations, enrichment and verification, and returns clean and consistent data ready for analysis in any format.

Concordia helps answer these kinds of questions:

  • How effective are my pricing and media promotions across countries?.
  • Which product categories are selling the most or least in a given country?
  • Which countries warrant additional budget to grow a particular product category?
  • How are sales tracking against goals around the globe using the corporate currency metric?
  • How are new product variations performing for men versus women, or Gen X compared to Gen Y?

Concordia system architecture


  • Scalable design: Easy to add new measures and new data sources
  • Flexible: Parameter driven set up
  • Fast: Harmonized data available within 1-2 weeks
  • Customizable: Manages data nuances by country and product category


  • Local harmonization: Align different data sources in market
  • Global harmonization: Align similar data sources across markets
  • Custom metrics: Easy to create new measures
  • Custom attributes: Easy to create new attributes
  • Data granularity: Configurable to control detail in output data
  • Scalable: Easy to add new data sources
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