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Snowflake
Logical Solution Architecture on Microsoft Azure
Architecture
Business insights no longer merely depend on Transactional data, but also on data that presents itself with varying degrees of Volume, Variety and Velocity.
This expectation alone has compelled Organizations to move their entire Data and Analytics landscape to cloud platforms and for the obvious advantages and promises that the cloud offers.
Architecture
Our Approach
indigoChart's recommended Conceptual Architecture can model to your expectations and the value that you intend to derive from your DataWarehouse systems. This Architecture can be applied to Structured, Semi Structured and Unstructured data that can either be at Rest or sourced from IoT, Sensors, Social Feeds, APIs, and Events in the form of streaming real-time data feeds.
Design Elements
Data Security and privacy by design, using capabilities such as data masking, data access control and easily configurable RBAC structure. Data Sharing made simpler via secured data sharing with outbound streams that can be easily implemented in minutes.
Integration Aspects
Strategic integration of your batch and streaming data can provide immense value and thus ability to leverage your growth KPIs.
Architecture Types
As Organizations embark upon modernization of Data and Analytics Platforms, we highly recommend starting out with establishing a Conceptual Architecture. Once A Conceptual Architecture has been identified the next Step is to be able to establish a Logical Solution Architecture.
indigoChart's proposed Architecture comprises of a Logical Solution Architecture leveraging Snowflake's Datawarehousing capabilities using Microsoft Azure as an example. The same can be developed on Amazon AWS, or Google cloud as well.
Secure your copy of the white paper to get started with designing your Reference Architecture.
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