The Relationship of Cloud Technologies and Big Data

Cloud technologies are a basic need to design digital architecture with its ever-growing data structure. In a world where transactions, inventory, and even IT infrastructure can exist in a completely virtual state, the big data approach has enabled a holistic overview by extracting data from multiple sources, including:

  • Virtual logs
  • Security events and patterns
  • Global network patterns
  • Abnormal reflection and resolution
  • Compatibility information
  • Customer portfolio and preference tracking
  • Location datas
  • Social channels data for brand tracking
  • Inventory levels and shipping
  • Other specific data affecting your organization

Big data is not only an important part of the future, but it can also be the future itself. The way businesses, organizations, and IT professionals approach their mission will continue to be shaped by advances in storing, moving and understanding data. 

Big data, cloud and serverless computing

Before cloud platforms, all big data processing and management was done in-house. The introduction of cloud-based platforms such as Microsoft Azure, Amazon AWS, and Google BigQuery now makes it possible – and advantageous – to complete data management processes remotely.

Cloud computing in a serverless architecture provides businesses and organizations with lots of benefits, including:

  • Efficiency – Both the storage tier and the compute tier are decoupled. You pay for as long as you keep the amount of data in the storage tier and the time it takes to do the necessary computation.
  • Reduced implementation time – Unlike deploying a managed cluster that takes hours to days, a serverless big data implementation only takes a few minutes.
  • Fault tolerance and availability – Serverless architecture managed by a cloud service provider offers fault tolerance and availability based on service level agreement (SLA).
  • Easy scaling and autoscaling – Defined autoscaling rules allow the application to scale according to the workload. This could help to significantly reduce operating costs.