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Big Data

Take advantage of all the opportunities
opened by the value-added exploitation of big data

Capitalize on the data explosion

The massive trend to the digitization of information comes along  with a tremendous growth in increasingly heterogeneous formats: traditional information systems, data transmitted by sensors on equipment, smart objects and devices, social networks, collaborative systems.

Data explosion goes well beyond increasing the capacity of decision-making systems. It allows a profound change in the business process management of companies and public services. It enables the creation of new businesses for both citizens and enterprises, as well as radically new environment and territory management capabilities. Finally, it leads to better risk management.

To design and implement value-added use cases, Bull combines two key elements of big data, based on its unique triple expertise in high performance computing, data security, and the implementation of complex integration projects for critical applications:

  • Professional combining close knowledge of business processes, mastery of algorithms and the ability to design and develop technical architectures,
  • Technological resources to acquire, store, process, analyze and display the data, all that in real-time and on a massive volume of data

Two ways to bring Big Data to the enterprise

Value-driven approach

  • Leverage Big Data for increased ROI
  • Enrich data warehouses. Unify your silos
  • Offer new services

Cost-driven approach

  • Industrialize Big Data to integrate it to the IS
  • Demonstrate the added value and then multiply the use cases
  • Initialize in a “Lean startup” mode for increased agility

Partners

EMC, Gigaspaces, MapR, Microsoft, MongoDB, Parstream, Pivotal, QuartetFS, SAP, Sinequa, Software AG, Tibco
Bull also works with many Open sources solutions in the Hadoop, NoSQL, newSQL and CEP ecosystem.

Resources

Livre blanc
White paper

Manufacturing – « What businesses can learn from big data and high performance analytics in the manufacturing industry’ »


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