The total cloud computing market worldwide is expected to reach $623.3 billion by 2023. Much of this growth will go toward the public cloud. The reason is simple: it can address complex processes while offering global availability, agility, elasticity, flexibility, and a reduced total cost of ownership. At a basic level, public cloud computing offers compute, storage, and networking – and every data environment requires all of these to perform well.
Consider a public cloud’s applicability to the financial sector. Global financial-services companies process millions of financial payment transactions daily, many across borders. Data-sovereignty regulations have introduced more complexity requiring some data to be managed and stored inland. Yet aggregated data can be utilized for global organization-level decision making, IPs, or value-added services like fraud modeling.
How can global financial-services companies localize data to comply with country-specific regulations while accessing and analyzing their valuable global data? The appropriate technology measures can help them remain compliant, while the right cloud solution can address both of these business demands.
Unleash data with public cloud
Snowflake Data Cloud is a global network where thousands of organizations mobilize data with near-unlimited scale, concurrency, and performance. Snowflake’s platform is the engine that powers and provides access to the Data Cloud. The platform is built to utilize public clouds. The architecture separates data storage from data computing offering elastic scaling, usage-based per-second billing, and secure data sharing over a multi-cloud deployment. Snowflake’s true separation of compute and storage, along with engineering for the service layer, enables it to serve Data Warehouse, Big Data, Reporting, and Analytics applications over a public cloud.
Public cloud natively lets organizations host data locally within a country, with security features that ensure compliance with local and international regulations. In addition to data localization, the Snowflake platform takes advantage of public-cloud capabilities and architecture to solve the complex processing and data-access issues like those described in the financial services example above. Snowflake can deliver these capabilities due to a layered architecture with three distinct components:
1. Snowflake virtual warehouse
Snowflake virtual warehouses do not host data, but leverage a copy of data stored centrally for computing applications. This is key in separating data storage from data consumption. Each virtual warehouse performs its own computing without impacting others while accessing the same version of centrally stored data. And Snowflake virtual warehouses use public cloud compute infrastructure like AWS EC2, offering unlimited elasticity.
2. Snowflake storage
The Snowflake storage layer manages data centrally in a public cloud storage infrastructure like AWS S3 or Azure Blob. This layer offers data encryption, in motion and at rest, and it is not directly accessible to anyone. The data access is only offered via virtual warehouses.
3. Snowflake service layer
The Snowflake service layer is most critical, as it is a single point of entry to the Snowflake system. It manages a complete system; captures metadata automatically; and performs service control, authentication, and authorization. The other two layers are governed and made available through this service layer, which is also responsible for features like data sharing.
Snowflake offers several advantages for companies looking to leverage the public cloud:
Snowflake solution architecture for global payments
This high-level architecture strategy shows how Snowflake could be applied to address the data needs of a global financial services company. The Snowflake architecture opens the broader possibility of data sharing and monetization across partners, as both data providers and consumers, while ensuring that local regulations are followed.
With a Snowflake deployment, this architecture requires only configuration – no other complex engineering, architecture, or solution development. Best of all, it could be operational in a matter of days with continuous industry-leading data security. Deploying a solution with traditional data technologies would require many months of engineering.
Wipro-Snowflake partnership
Wipro is an “Elite” global SI partner for Snowflake in cloud data warehouse services. Wipro offers a variety of services for the Snowflake data platform from architecture consulting, implementation, and migration to support. Wipro leverages the 500+ Snowflake consultant pool that includes more than 120 Snowflake-certified consultants. Wipro was named a Global Solution Partner for 2018 and 2019 with more than 35 implementations and the privilege to build connectors for Snowflake Mainframe and SAP BW.
Looking for more information? Reach out to us at ask.analytics@wipro.com
Sanjeev Mittal
General Manager, Business Head – Data, Analytics & AI, Wipro
Focusing on key industry sectors like Financial Services, Energy, and Utilities, Sanjeev helps clients leverage Data, Analytics, and Artificial Intelligence to drive digital transformation initiatives. He also nurtures alliance partners to deliver comprehensive ecosystem benefits to our clients. Sanjeev brings a broad perspective with 22 years of combined sales, solutions, and delivery experience.
Deepesh K. Shrivastava
Practice Director – Data, Analytics & AI, Wipro
As part of Wipro Data, Analytics & AI Practice Sales team, Deepesh is helping customers transform their business through better data-driven decisions. He brings 21 years of experience in Data Analytics, Business Intelligence, Information Management, and Big Data, as well as specializations in Cloud Data Platforms and Architecture Consulting, Analytics solutions strategy and roadmap, and data practice leadership and management.