Let Your Data Take Centerstage
What is Snowflake?
Snowflake is an integrated cloud-based data storage, processing, and analytics service that is a pioneer in offering DaaS or Datawarehousing-as-a-Service. With Snowflake you can leverage the biggest 3 brands of cloud service providers — Amazon S3, Microsoft Azure and Google Cloud Platform — to store, process and analyze your enterprise data.
Some of the key features and advantages of Snowflake are:
- Separation of storage and compute
- On-the-fly scalable compute
- Data sharing
- Data cloning
- Support for third-party tools
With these and many more features, Snowflake can support your growing and ever demanding enterprise data needs. Snowflake is all about the data enabling governed access to near-infinite volume of data with support of cutting-edge tools, applications, and services.
Your teams can collaborate from anywhere in the world with Snowflake’s Data Cloud to collectively know more about existing customers, identify new customers, create business opportunities, reveal new insights — quickly, easily, securely, seamlessly, and at scale.
Snowflake is one of the most opted data warehouse service providers for building self-managing cloud data warehouses, data lakes, and other cloud storage. It runs on popular cloud providers such as Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform.
The platform can handle all aspects of authentication, configurations, resource management, data protection, availability, and optimization. It is known for its range of unique features, which includes data sharing, time travel, database replication and failover, and inbuilt zero-copy cloning. It enables its users with greater agility by decoupling storage and computing.
The Snowflake ecosystem consists of:
- Unlimited Storage via Data Lake
- Query Processing through Virtual Data Warehouse
- Snowflake for Data Science
- Underlying Cloud Infrastructure Services
Use Cases for Snowflake
Near-infinite Data Storage with Snowflake Data Lake
The Snowflake data lake is a highly scalable repository capable of storing raw data (structured, semi-structured, and unstructured) until further processing. It can hold data from heterogeneous sources in different data formats.
Unlimited and Economical Storage
You can Store data in multiple formats including AVRO, Parquet, ORC, CSV, JSON, XML, and many more. The cost of per Tb storage is very low and comes with unlimited storage limits. The storage uses efficient compression & encryption techniques and applies automatic micro-partitioning. You can also easily load data from different cloud providers through real time streaming and batch uploads.
Leverage SQL
You can run SQL queries for any structured data stored in different formats and structures. You can also work with external data from cloud storage like AWS S3 and Azure Data Lake Storage without loading it to Snowflake. Snowpark allows you to streamline development of data pipelines using SQL or in other languages of choice without the need for managing additional clusters or services, or even making copies of the data.
Reliable and Performant Query Processing
The elastic engine can simplify your workloads and underlying architecture with virtual warehouse capabilities. The issues related to concurrency or resource contention become a thing of the past. Control the data within the lake with a handle on how your data is stored and used allowing easy collaboration and secure data sharing.
Snowflake Data Warehouse for Data Processing
Leverage the Snowflake DWH for executing long-running analytical jobs to yield business insights.
Massively Parallel Processing
The Snowflake DWH runs using MPP to handle multiple query and analysis operations simultaneously using several processing elements. The MPP database can process large volumes of data without compromising execution speed of analytics ops. The centralized storage of Snowflake is shared by all compute nodes that run queries in clusters called virtual warehouses. Snowflake offers the ideal mix of simplicity with scalability.
Seamless Data Integration
Snowflake supports both ETL and ELT operations to let you perform data transformations during or after loading it. With support for multiple data integration tools like Informatica, Talend, Fivetran, Matillion, and others you have virtually the entire universe at your service. Snowpark can be used to build complex data pipelines allowing developers to interact with Snowflake without moving data.
Columnar Storage
Snowflake is a complete SQL database to support data intensive operations with data stored in columnar manner rather than the traditional row manner. The columnar-format allows faster data aggregation, high compression ratio, reduction in physical storage requirements, and at low storage cost.
Data Partitioning
Snowflake tables are automatically partitioned into micro-partitions in contiguous storage blocks. These micro-partitions allow data grouping of rows within tables and are stored in columnar fashion. Each table can have hundreds of millions of micro-partitions of sizes varying from 50 to 500 MB uncompressed and 16MB max as compressed.
Advanced Analytics Support
Snowflake supports running analytics operations on large volumes of data by applying complex ML algorithms helping developers identify data patterns and insights.
Data sharing feature to use cleansed data from data warehouse
Data Analysts and Data Scientists can easily use cleansed and transformed data for their ML by leveraging advanced and secure data sharing. Perform Exploratory Data Analysis (EDA) and develop new models at no additional storage cost.
Snowsight for EDA
Snowsight is a powerful Web UI from Snowflake accelerating users’ querying, scripting, and data visualization capabilities. Identify outliers, point out quality issues, and utilize the data exploration and model distribution capabilities with ease. Data preparation and data visualization come handy with a scalable computing backbone.
Quick and Easy TP Integration
Many Third-party (TP) tools are developed by Snowflake partners that you can easily integrate with your instance. With easy, secure, and quick TP Integration leverage their advanced capabilities for statistical and predictive modeling. Use third-party APIs for data modeling, model production and testing.
Reliable Cloud Infrastructure
Federated Authentication and SSO
Snowflake’s federated authentication service allows you to either use Snowflake’s authentication mechanism or continue to use your user credentials. Security administrators can create users with passwords maintained in Snowflake while also supporting two methods of authenticating users via Browser-based SSO and Programmatic SSO (as of now only for Okta).
Infrastructure Management
The cloud service layer is set as an independent, higher-level, fault-tolerant service bouquet. The Infrastructure manager is responsible for managing virtual warehouses, coordinating data access & updates without impacting its availability or overall performance.
They are also responsible for communication with client applications like Snowflake Web UI, JDBC/ODBC clients, etc. for query processing. It also ensures security of your account, users,and data stored in Snowflake.
Metadata management
Metadata is used to define warehouse objects and functions as a directory or a folder. It helps in better organization and helps locate them faster. Snowflake metadata management ensures the highest level of data governance using processes, policies, workflows, and technology. It can identify, organize, and make metadata available to data consumers by adding actionable context to the assets in the data warehouse.
Snowflake metadata management offers following benefits to users:
- Faster access to insights
- End-to-end visibility
- Improved data quality and trust
- Improved operational efficiency
- Compliance and regulations
- Improve ROI on data
Never Worry about Query Optimization
Snowflake optimizer parses queries optimizing them dynamically. The auto tuning helps users get results faster by speeding up data processing for both structured and semi-structured data alike. As a data user you do not have to worry about query performance at all — you just need to model, load, and query the data!
The cloud services layer handles all tasks related to query planning and optimization based on metadata and data profiles. It determines the most effective distribution of the data and queries across the available compute nodes. Data users need not worry about indexes, partitions & partition keys, pre-sharding data, and most importantly updating statistics.
Access control
Snowflake access control mechanism combines aspects from Discretionary Access Control (DAC) as well as Role-based Access Control (RBAC). In DAC, access to objects are granted by their owners, while in RBAC, access privileges are assigned to roles assigned to users.
Access control in Snowflake revolves around Securable objects, Roles, Privileges, and Users. This model provides a significant improvement for both control over data and flexibility of access.
Why Snowflake?
Snowflake is a complete and truly cloud-based SaaS offering:
- You need not select, configure, and monitor any hardware.
- Or worry about installing, configuring, and managing any software.
- Maintenance, data backup & recovery, system management & upgrades, and performance tuning are all handled automatically.
- Every component and tool from Snowflake — except the optional CLI clients, drivers, and connectors — run on public clouds.
- Snowflake employs virtual compute resources and storage service for persistent storage.
- Get highly performant query processing and speed up your analytics with multiple virtual warehouses, automatic query optimisation, cluster tuning, and micro-partitions.
- The On-demand pricing model allows even the smallest of teams to leverage Snowflake’s capabilities to scale up economically.
- There is literally “Zero” administration and operational costs involved as auto-scaling, auto suspend, and zero-copy data sharing allow you to focus on your work and not admin tasks.
- The UI/UX of Snowflake and its tools is intuitive and user-friendly with ANSI SQL being the language of choice.
- Snowflake is compatible with multiple BI tools giving you power to query large datasets from them along with support for multiple programming languages.
- Scalability is built-in to Snowflake’s architecture as it is a cloud-agnostic solution freeing up your team from worrying about system failures or delays.
- Seamless data sharing allows users to collaborate with anyone, even when they’re not Snowflake users.
- The data is secured with in-store and in-transit encryption at no additional cost.
- No need to learn a new language for data blending, analysis, and transformations and other data p tasks. You only need SQL.
- Support for a variety of file formats for both structured and semi-structured data.
Snowflake Learning Paths
At the core of Snowflake learning is the understanding of the Snowflake Cloud Data Platform concepts and application of the solution in implementing and migrating to Snowflake. At this stage, the necessary knowledge is applied to design, develop and manage secure, scalable Snowflake solutions for driving business objectives.
The advanced learners and practitioners can study and master concepts like:
- Designing an end-to-end data flow and near real-time data streams
- Designing and deploying a data architecture to meet business requirements
- Selecting appropriate tools for optimization
- Sourcing data from Data Lakes, APIs, and on-prem data warehouses
- Transforming, replicating, and sharing data across cloud platforms
- Designing scalable compute solutions for DE workloads
- Implementing Snowflake DS best practices
- Implementing data and feature engineering in Snowflake
- Training and using ML models
- Using data visualization and implementing model lifecycle management
- Managing and administering Snowflake resources like accounts, data security and governance, database objects, and virtual warehouses.
- Performing database monitoring and tuning
- Enabling data sharing and using Snowflake Data Exchange and Data Marketplace
- Administering disaster recovery, backup, and data replication policies
The Snowflake learning journeys can be summed in the following image from who else but Snowflake.
(Image Source: Snowflake)
Prepare for SnowPro Core Certification
You can check the Official SnowPro Certification resources at Snowflake Certifications | Stand Out in the Data Community to check out the learning material and booking your certification exams.
Learning Tracks from Snowflake
- Essential hands-on curated learning journey can be found here.
- Check out courses and community discussion at the Snowflake University.
- Learn more about learning tracks and certifications here.
- Prepare for Advanced SnowPro Certifications for
- Architect
- Administrator
- Data Engineer
- Data Scientist
Watch videos on DataCouch’s YouTube Channel
Getting Started with Snowflake
You can directly click on the following YouTube links to directly watch the videos that interest you the most. :)
Evolution of Data Warehousing Technologies
Challenges with Traditional DWs and Big Data DWs | Data Warehouse | Big Data
About DataCouch
DataCouch is a leading Enterprise IT Training and Consultancy company based in India, Canada, and Malaysia. Our team of experts is a trusted Global Training Partner or have delivered technology training for many Fortune 500 companies including Adobe, Apple, BCG, Google, Microsoft, Neo4j, PayPal, Salesforce, Starbucks, Walmart and many more.
DataCouch is a preferred training delivery partner of Neo4j, Confluent, PayPal, Snowflake, and many others. We continuously improve our Global Training Delivery Model and offer the services of world-class instructors, course content to meet your specific needs, and a proprietary virtual Browser-Based Lab Solution. Our premium Enterprise Training services have benefitted the engineering teams of companies with unique needs in niche markets, emerging domains, serving demanding customers.
The specialized Enterprise Training at DataCouch is delivered by experts having a collective 100+ years’ of experience. The team is at the forefront of bleeding–edge technologies in AI, ML, Data Engineering, Cloud, DevOps, IoT, Blockchain, and RPA domains.
Our consultants are transforming teams and organizations with pragmatic solutions and attainable objectives. We have successfully delivered consultancy services in Data Engineering, Digital Transformation, and DevOps helping clients implement solutions for businesses of all sizes.
For official virtual instructor-led Snowflake classes, please reach out to us at operations@datacouch.io or visit our website — DataCouch for courses related to Agile, AI, Cloud, DevOps, Data Engineering, ML, RPA and many more.
