CASE HISTORY

Implementation of an internal insight/search engine

TOPIC AREA

Data Science

Data Science services, provided by professional figures defined as 'Data Scientists' or more commonly by teams composed of developers, data engineers and data scientists, allow companies to carry out studies and analyses on data with the aim of creating explanatory models of business processes, identifying and quantifying causes and effects, identifying potential predictors of quantities or events of interest, classifying, grouping, characterizing the available data in order to derive a better understanding of the company and its functioning also in relation to the outside world and identifying control actions able to optimize business outputs. The services in this area are completed by training, design and management activities related to the platforms typically used for Data Science activities such as KNIME, Dataiku, Jupyter, Zeppelin, etc.

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Customer

The Client is a U.S. company, one of the largest in the oilfield services industry.

Customer Need

  • Overcoming internal information silos
  • Perform research on large amounts of data in less time than architectures
  • Implement dynamic insights into search result data.

Customer Value

Reduced time to search for information, greater efficiency in business processes. To date there are 3000 registered users with an annual query usage > 500,000, higher than the usage of the internal Tableau platform.

Key differentiators

High degree of expertise in:

  • Distributed systems design
  • Custom search engine design
  • Natural Language Processing

Processes & Technologies

  • Consolidated methodological approach in Data Science
  • In-depth knowledge of Spark/Hadoop stack on premise and on AWS/Azure
  • Machine learning and automatic classification techniques
  • Natural Language Processing

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