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Scalable and sustainable analytics ecosystems are driven by modern Data Engineering solutions

We differentiate ourselves from traditional analytics service providers by building modern data products fed from automated data pipelines. Unlike traditional IT outsourcing providers, we don’t engage based upon specific technology stacks.  Instead, we look at the entire data ecosystem through the lens of business outcomes, focusing on what matters. Our Data Engineering practice provides our clients with robust, fault-tolerant and scalable data products. This encompasses:

  • Data Integration from all possible sources (batch and real-time streaming)
  • Data Preparation (e.g. ETL)
  • Data Exploration (e.g. using Data Science notebooks)
  • Data Processing and Analytics using appropriate algorithms and models
  • Data Persistence for performant, secure, and scalable access (SQL and no SQL)

We work pragmatically with our client's existing tool-set where appropriate, complementing, when necessary, with modern tool-sets from the Open Source world, e.g. Apache Hadoop and Spark. The journey to modern data products and architectures can take a while, and in the meantime we also support our customers with more traditional data management services, such as:

  • Data quality management
  • ETL process management
  • EDW application management
  • EDW offload and migration