Snowflake
Logical Solution Architecture on Microsoft Azure
Why Snowflake
Single Global Platform. One Copy of Data with different workloads. Snowflake Data on Cloud.
From the customers that implemented Snowflake and were surveyed
84%
achieved more of a Competitive Advantage in terms of Growth
95%
were able to better manage Organizational Risk and thus decreased cost of Service
96%
achieved decreased Administrative Cost
indigoChart's SnowPro and Advanced Architect Certified professionals with over 10 Snowflake implementations can help modernize your data assets by bringing all your data to the Snowflake Cloud Platform workloads such as Data Warehouse, Data Lake, Data Hub, and Data Science from Zero to Production within weeks.
By leveraging our in-house connectors based on a Metadata Driven approach for Snowflake Data Ingestion and Transformation, or by using ETL/ ELT technologies from our technology partners dbt combined with HVR technologies for Change Data Capture, we can assist with the Design, Development and Implementation of Cloud Data Solutions at scale across Snowflake's workloads.
Snowflake Workloads Capabilities
Build simple and reliable Data Pipelines
Implement Change Data Capture (CDC) strategies using HVR technologies to ingest data into Data Lakes from Enterprise Applications.
Facilitate data movement and orchestration using a combination of indigoChart's python based custom connectors and ELT/ETL technologies from our technology partners dbt.
Build metadata driven Data transformation Pipelines using Matillion, Snowflake Streams and tasks with as much as 70% effort reduction in development of ETL/ELT data pipelines.
Data Warehouse Design and Development
Using Snowflake's Cloud data platform and indigoChart's recommended Reference Data Architecture, manage your data heavy workloads with Pay as you Go model and also scale compute and storage on demand, without additional maintenance .
Easily bring your data from various sources, unify, validate, integrate, and analyze as per workload requirements.
Clone and Share your data with few clicks with Snowflakes security architecture. Ideally targeted for analytics or descriptive and diagnostic needs.
Data Lake Architecture and Design
Building a successful data lake from the very beginning, requires a design that embodies data stewardship, governance and security, and easy access to all data.
Leverage Snowflake capabilities as a Data Lake for your structured and semi-structured (JSON, XML, AVRO, PARQUET, RAW) sources and explore RAW data at scale compute performance with Snowflake multi-cluster MPP architecture.
Use native SQL queries against structured and semi-structured types without requiring additional programming and use the Schema-on-Read approach for the semi-structured data.
Separation of compute and storage capabilities enables organizations to store massive volumes of raw data cost-effectively while deploying only the computing capacity needed.
Optimize Data Science Workbenches
Users of Data Science applications demands massive analysis on RAW and un-curated data. Such volumes lead to poor performance on computes and in turn higher time for query processing and getting results from data warehouse or data lakes.
Snowflake's cloud data platform supports massive storage and compute elastic architecture to analyze Data required
for Data Science applications with support of Machine Learning libraries and tools that data scientists rely on.
Snowflake's near-unlimited storage and near-infinite compute resources can rapidly scale to meet performance needs of analysts and data scientists.
Share Data using Marketplace
Share and exchange your data seamlessly at your will within or outside your enterprise in secured way with Snowflake's Data Sharing and Data Exchange features.
While it is not required to move data physically when shared with data consumers, we can help with creation of Data Sharing models using additional security implementations on Column and Row level filtering using Secured Views.
Snowflake Implementations
Data Hub
Collect, standardize, validate and share data within enterprise with single view of truth.
Enforce your data governance rules on data sharing and exchange between applications and business users.
Security and Data Governance
Implement Data Governance and security model with our ready to use custom accelerators for Snowflake
Role Based Access Control (RBAC) with enhanced security using SSO, MFA, OAuth and Private links to your Cloud Tenant.
Snowflake Environment Setup
Instantly create isolated Snowflake Environments (Dev, Test, Acceptance, and Prod) within single or separate Snowflake Accounts.
Apply Data Masking policies for Development, Test and Acceptance environment as per needs.
Snowflake Resource Manager and Usage
Monitor and Control Snowflake Usage on compute credits using our custom build Reports.
Identify scope for improvement on usage Snowflake credits to save costing.
