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1 Highlight, isolate and solve business problems

2 Ingest data more widely than previously possible

3 Store far more data than before

4 Enable deeper analytics (machine learning, predictive analytics, etc.)

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  • Incorporate and analyse data literally as it arrives, in a variety of formats regardless of structure and source.
  • Understand more about their customers and supply chain, as it happens.
  • Automate the execution of responses to data insights through microservices within an API framework.
  • Leverage existing data assets and warehouses to create a two-speed architecture by modernising the ingestion layer.
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  • Streamline business processes to maximise resources and reduce costs.
  • Enhance demand and sales forecasting, improved inventory control.
  • Optimised supply chain process integration.
  • Improved store/branch network planning and configuration.
  • Superior selection of target market prospects for cross-sell and up-sell initiatives.
  • Enhanced management of customer churn, enriched customer segmentation.
  • Enhanced understanding of customer sentiment (satisfaction, frustration, etc).
  • Superior management of customer loyalty, profitability and life-time value.
  • Improved product, services and channel pricing, optimisation of merchandising.
  • Better management of credit, operational and market risk, with enhanced fraud detection.
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