Cloud-Native Design for Analytics accelerates time-to-market for new services and reduces IT costs through automation and reduced complexity.

The basis of an excellent cloud-native design for analytics is an architecture that ensures that an organisation only consumes resources when it needs them. As the Cloud offers nearly unlimited resources, an organisation can utilise as much as the scalable cloud-native services and applications as needed at peak times. A cloud-native approach is a fundamental paradigm shift compared with traditional on-premise solutions that emphasise using all the available resources.

Strictly speaking, the Cloud is not a new technology but a new business model that disrupts how companies manage their IT. In the data and analytics domain, cloud transition is often a cornerstone of an organisation’s digital transformation.

The path to cloud-native analytics: Evaluate → Design

Stage 1: Evaluate

Through a series of questionnaires, research and interviews an AlphaZetta team, under the leadership of a senior architect will assess the current situation and target state. The architectural team then publishes a management report and guide for the client to migrate to a data analytics cloud.

In this report, the client will receive

  • A cloud maturity assessment
  • Cost-reduction estimation
  • Required KPIs to meet the service quality of business and user expectations
  • Road map for a phased service transition and recommendation
  • A high-level architecture design
  • Strategy recommendations

Stage 2: Design

A team of AlphaZetta experts will work together with the IT department of the client to work on the following tasks:

  • Service discovery and creation of a service catalog
  • Cloud-native solution design based on a serverless and microservices oriented solution
  • A design for elasticity and polyglot-storage patterns
  • A migration from on-premise to cloud
  • Data pipelining and loading data into the platform
  • DevOps and automatisation of infrastructure
  • Productionising of services and applications
  • Integration of Managed Services

Associated programs: Data and Analytics Cloud Migration, Analytics Experience (AX)

Commonly associated services: Managed Services, Data Acquisition and Integration