Data collection and quality


Data Quality Audit

Knowing the degree of data quality is the first step to carry out corrective measures to have quality data.

  • Descriptive field-level analysis by Data Source
  • Data Quality improvement objectives and strategies
  • Operational plan: tools, processes, data sources
  • Data Quality Dashboard

Data enrichment

Establishing processes to improve data quality is essential. We use our own tools and other market tools such as Google Maps, statistical sources and Open data available.

  • Cleaning and Standardization
  • Deduplication and Consolidation
  • Opendata

Web scraping of data

Programs that simulate a person’s browsing to obtain information identified on websites.

  • Web structure analysis
  • Data collection strategy
  • File generation

Data integrations

Obtain the necessary data for incorporation into a database, for consumption in other systems or for analysis projects.

  • Identification of required data
  • APIs, Web Services, ETL, Sensors
  • Internal and external data


PIM Data Quality Project.

Capturing potential customers.

Opendata data collection and scraping.

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