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Boost your career level with our Cloud Data Platform using Snowflake Training | Understand Snowflake’s value proposition and to begin your journey adopting this data platform | Gain the ability to provide massive scale, near-zero maintenance and one single source of truth | Hone your existing skills by working on assignments and projects related to Cloud Data Platform using Snowflake.
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There's a reason that 95% of our alumni undertake 3+ courses as a minimum with Henry Harvin®
The Snowflake training course at Henry Harvin® introduces students to Snowflake. It is a fully-managed, terabyte-scale Cloud Data Platform that you can run on any major cloud platform, be it Microsoft Azure, AWS, or Google Cloud. Snowflake enables us to replicate and synchronize your data across the points of deployment on different cloud platforms. The Data Cloud eliminates the barriers created by siloed data. The technology that unites this ecosystem and enables the Data Cloud is Snowflake’s Cloud Data Platform solving their specific data processing and analysis problems. There are 6 different workloads that it offers:
Snowflake is a complete SAS offering and can run on either AWS, Azure, or GCP in the backend which gives you the option of being multi-cloud as well in your disaster recovery setup.
Become a part of the Elite Cloud Computing Academy of Henry Harvin® and join the 4,60,000+ large Alumni Network Worldwide.
Know the complete offerings of our Cloud Data Platform using Snowflake Course
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Module 1: Snowflake Introduction
Module 2: Snowflake Lab Environment
Module 3: Snowflake User Interface
Module 4: Working with Queries
Module 5: Working with Semi-Structured Data
Module 6: Snowflake SQL
Module 7: Snowflake Administration
Module 8: Integration with BI Tools
Know the complete offerings of our Cloud Data Platform using Snowflake Course
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Cloud Computing
Cloud Data Warehouse
Data Migration
Data Management
Data Engineering
Data Modeling
Our course is exhaustive and this Certification is proof that you have taken a giant leap in mastering the domain
The practical knowledge and actionable skillset you've gained working on projects, simulations, case studies will set you ahead of the competition
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We are dedicated to supporting our students throughout their career journey. Join us, and let's embark on a journey towards a successful and fulfilling career together.
Exclusive access to our dedicated job portal and apply for jobs. More than 2100+ hiring partners’ including top start–ups and product companies hiring our learners. Mentored support on job search and relevant jobs for your career growth.
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A Snowflake account can be hosted on any of the following cloud platforms: Amazon Web Services (AWS) Google Cloud Platform (GCP) Microsoft Azure (Azure)
Snowflake runs completely on cloud infrastructure. All components of Snowflake's service (other than optional command line clients, drivers, and connectors), run in public cloud infrastructures. Snowflake uses virtual compute instances for its compute needs and a storage service for persistent storage of data.
When it comes to performance, Snowflake's capabilities should be similar on both AWS and Azure, as it utilizes the underlying compute resources of the respective cloud platforms.
While both AWS and Snowflake are highly beneficial and well-suited for various applications, Snowflake has the edge over AWS for a few reasons. Snowflake's architecture combines cloud and SQL query engine, while AWS only uses nothing-shared databases, giving Snowflake high-performance speed.
Snowflake supports standard SQL, including a subset of ANSI SQL:1999 and the SQL:2003 analytic extensions. Snowflake also supports common variations for a number of commands where those variations do not conflict with each other.
Snowflake supports both transformation during (ETL) or after loading (ELT). Snowflake works with a wide range of data integration tools, including Informatica, Talend, Fivetran, Matillion and others.
Both platforms enable the user to create SQL databases for data warehousing but the Snowflake SQL database is completely decoupled from the computer resources which use SQL databases. Whereas the Azure technology requires a separate SQL pool to develop an SQL database for the warehousing
The Snowflake Data Cloud provides the perfect environment for dataops and devOps, including CI/CD. Snowflake customers can industrialize data pipelines in and around Snowflake.
Transforming Business Through The Power Of Data | Accenture & Snowflake. Srini Nachinarkiniar, Accenture's Global Snowflake Practice Lead, sees every business as a data business.
There has been a great demand for Snowflake developers, the world over and the reasons are quite simple. Thanks to the salient features that Snowflake offers and its increasing popularity quotient, a Snowflake developer is considered a great asset for organizations today.
Snowflake does not require any additional software, hardware, or maintenance over and above other platforms' needs. Data storage, query processing, and cloud services are the three layers that make up the Snowflake architecture. Each layer serves a specific purpose.
Snowflake is rapidly becoming the platform of choice for businesses seeking to manage their data resources in a secure and efficient manner. Its advanced security features, centralized platform, and data-sharing capabilities position it as a frontrunner in the future of data management.
NET, Python, C, Node. js, etc. For general users, Snowflake provides complete ANSI SQL language support for managing day-to -day operations. It's cloud agnostic, with unlimited, seamless scalability across Amazon Web Services (AWS) and Microsoft Azure (with the prospect of adding Google Cloud soon).
Snowflake streamlines big data engineering, while delivering performance and reliability, allowing organizations to easily ingest, transform, and deliver data for faster, deeper insights.
Is Snowflake a SaaS or Paas?
SaaS
Snowflake is an SaaS solution. A cloud-based data warehouse that holds no physical space and takes care of maintenance itself. It's fast, responsive and highly scalable.
Snowflake is super easy to learn and use, with an almost zero admin footprint.
Django is commonly used with OLTP databases for its backend, but Snowflake can be a great backend for Django when you need the power of the data cloud behind your app. In this Quickstart, we'll demonstrate how to use Snowflake as a backend for your Django application using the django-snowflake Python package.
You can connect to Snowflake in many languages. If your language of choice is Python, you'll want to begin here to connect to Snowflake. We'll walk you through getting the Python Connector up and running, and then explore the basic operations you can do with it.
Structured, semi-structured, and unstructured data intake are all handled by Snowflake in batches and continuously. Data engineers can use the data more efficiently and smoothly thanks to this. Moreover, because of its simplified data transformation and architecture, less time in managing infrastructure is required.
ACCOUNTADMIN: Role that encapsulates the system-defined roles SYSADMIN and SECURITYADMIN. It's the highest-level job in the system, and it should only be given to a small number of users in your account. SECURITYADMIN: Create, monitor, and manage users and roles, as well as manage any object grant globally.
There are few options if you miss a class. You get free access to LMS where you can find course content in an organized form. You view recorded class sessions.
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You will receive the digital certificate post training completion via learning enhancement tool after registration. However you can also get the hardcopy of the course on request.
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