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Free Download Snowflake Hands-On - 50 Live Assignments With Practice Mcqs Published: 3/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.09 GB | Duration: 3h 36m Master Snowflake with 50 Hands-On Assignments/Mini Projects & 50 MCQs - DIY Mini Projects for Practical Experience What you'll learn Understand Snowflake's cloud-based data warehouse, storage mechanisms, and virtual warehouse concepts. Load structured and semi-structured data, apply transformations, and automate workflows using Snowflake tasks, streams, and Snowpipe. Manage user roles, permissions, and optimize queries for cost efficiency and performance. Utilize Time Travel, Cloning, Data Sharing, and Unstructured Data handling to build scalable, secure, and efficient data solutions. Requirements Basic SQL Knowledge A Snowflake Account (Free Trial Available) Willingness to Learn by Doing Description Snowflake Hands-On Course: Master Cloud Data Warehousing with Practical Assignments & MCQsThis hands-on course is designed to provide in-depth knowledge of Snowflake, the leading cloud-based data platform. Whether you are a beginner or an experienced data professional, this course will help you build a strong foundation in Snowflake's architecture, data loading techniques, transformations, automation, and advanced features.With 50 real-world assignments, mini projects, and 50 MCQs, you will gain practical experience in working with Snowflake's powerful functionalities. Each module includes step-by-step exercises, real-world use cases, and DIY projects, ensuring you gain hands-on expertise in handling data efficiently in Snowflake.What You Will Learn?Introduction to SnowflakeUnderstanding Snowflake's cloud-based architectureKey differentiators from traditional databasesBenefits of using Snowflake for data warehousingSnowflake Environment SetupCreating a Snowflake trial accountSetting up virtual warehouses (WH) and databasesUnderstanding roles and permissionsSnowflake Warehouse Setup & Basic Data LoadingConfiguring Snowflake virtual warehousesLoading structured data into SnowflakeData storage best practicesSnowflake Stages & TransformationsWorking with internal and external stagesData transformations using SQL functionsOptimizing data processing with best practicesSnowflake Error HandlingUnderstanding Snowflake's error-handling mechanismsDebugging data load failuresStrategies for data recovery and error resolutionSnowflake Validation Modes & COPY Options/CommandsExploring different validation modes in SnowflakeUsing the COPY INTO command for efficient data loadingHandling various file formatsSnowflake Unstructured DataStoring and processing JSON, XML, Parquet, and other file typesUsing VARIANT data type for semi-structured dataQuerying and transforming unstructured dataSnowflake Snowpipe (Continuous Data Ingestion)Automating real-time data ingestionConfiguring Snowpipe for continuous data loadsMonitoring and troubleshooting SnowpipeSnowflake Tasks & SchedulingAutomating workflows using TasksScheduling SQL-based processesImplementing data pipeline automationSnowflake Time Travel & Table TypesUsing Time Travel for data recoveryUnderstanding Transient, Temporary, and Permanent TablesRestoring historical data snapshotsSnowflake Cloning TablesCreating zero-copy clones for quick data replicationUnderstanding cloning benefits and use casesOptimizing storage with cloningSnowflake Data SamplingSampling data for analytics and performance testingSnowflake Access ManagementRole-based access control (RBAC) in SnowflakeManaging privileges and rolesImplementing security best practicesMonitoring & Performance OptimizationTracking query performance and warehouse usageOptimizing queries for cost efficiencyUsing Snowflake's built-in monitoring toolsWhy Take This Course?50 Hands-On Assignments & Mini Projects - Real-world scenarios to build expertise100+ MCQs - Test your knowledge with concept-based quizzesBeginner to Advanced - Covers all essential Snowflake topicsPractical DIY Approach - Learn by doing, not just theoryIndustry-Relevant Skills - Gain skills for data engineering, analytics, and cloud computingBy the end of this course, you will have hands-on experience in working with Snowflake and be confident in implementing data solutions on the Snowflake Cloud Data Platform.Note : This is not an Official Snowflake Course, Please refer to Snowflake Product Guide or website for official documentation and learning.Enroll now and take your Snowflake expertise to the next level! 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Free Download Snowflake - A Comprehensive Guide To Cloud Data Warehousing Published: 3/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 14.77 GB | Duration: 22h 49m Snowflake training: from beginner to advanced. Transform data strategy, build rapid data insights, accelerate analytics. What you'll learn Understand data warehousing & cloud computing and Snowflake's unique architecture. Set up and navigate Snowflake, creating databases, schemas, and tables. Load and manage structured & semi-structured data (JSON, ORC, Parquet). Optimize virtual warehouses for cost and performance efficiency. Implement data ingestion & real-time streaming using Snowpipe and staging. Use Time Travel & Zero Copy Cloning for data recovery and replication. Improve query performance with caching, clustering, and search optimization. Manage secure data sharing & access control with RBAC. Utilize advanced Snowflake features like table streams, tasks, and UDFs. Monitor and optimize Snowflake costs using pricing and resource analysis. Integrate Snowflake with BI & data tools like Tableau, Power BI, and Spark. Apply security best practices including encryption and row/column-level security. Automate workflows using Snowflake tasks. Gain hands-on experience through assignments, labs, and real-world use cases. Requirements Enthusiasm and determination to make your mark on the world! Description A warm welcome to the Snowflake: A Comprehensive Guide to Cloud Data Warehousing course by Uplatz.Snowflake is a cloud-based data platform that provides data warehousing, data engineering, data lakes, and analytics capabilities. It is built on top of cloud infrastructure providers like AWS, Azure, and Google Cloud. Unlike traditional databases, Snowflake separates compute and storage, allowing for scalability, high performance, and cost efficiency.Snowflake enables businesses to store, process, and analyze massive amounts of structured and semi-structured data in a highly secure, scalable, and serverless manner.How Snowflake Works?Snowflake operates using a multi-cluster shared data architecture, which consists of three key layers:Storage LayerStores structured and semi-structured data in a compressed, optimized, and columnar format.Data is automatically partitioned and distributed across multiple storage units for high availability.Compute Layer (Virtual Warehouses)Virtual warehouses (clusters) process queries and workloads independently.Compute and storage are decoupled, meaning warehouses can scale up/down without affecting stored data.Multiple warehouses can run concurrently, allowing multiple users and teams to work on different workloads.Cloud Services LayerManages security, metadata, query optimization, and authentication.Supports features like auto-scaling, automatic failover, and query optimization.Core Features of SnowflakeMulti-Cloud SupportRuns seamlessly on AWS, Azure, and Google Cloud, allowing businesses to choose their preferred cloud provider.Separation of Compute and StorageUsers can scale compute resources independently from storage, reducing costs by paying only for what is used.Instant & Elastic ScalabilitySnowflake automatically scales up or down based on workload demands, ensuring high performance and efficiency.Zero-Copy CloningUsers can create multiple copies of a dataset without duplicating storage, making it easier to test and develop without extra cost.Data Sharing & CollaborationSnowflake enables secure data sharing across different accounts, organizations, and cloud providers without the need to copy data.Time Travel & Fail-SafeTime Travel allows users to restore data from historical snapshots (up to 90 days).Fail-Safe provides additional protection for recovering lost data.Support for Semi-Structured DataNatively supports JSON, Avro, ORC, Parquet, and XML, allowing schema-on-read flexibility.Automatic Performance OptimizationSnowflake automatically optimizes storage and query execution without requiring manual indexing or tuning.Built-in Security & ComplianceFeatures end-to-end encryption, access control, and role-based security.Complies with GDPR, HIPAA, SOC 2, and other industry standards.Snowpark & Python SupportSnowflake's Snowpark allows developers to use Python, Java, and Scala for data transformation and machine learning.Benefits of Learning SnowflakeHigh Demand for Snowflake ProfessionalsMany companies are migrating to cloud-based data platforms, making Snowflake skills highly valuable in the job market.Better Career OpportunitiesSnowflake knowledge opens doors to roles like Data Engineer, Data Analyst, Cloud Data Architect, and Snowflake Consultant.Competitive SalariesSnowflake professionals earn high salaries, as demand exceeds supply in the job market.Ease of Learning & UseUnlike traditional databases, Snowflake requires minimal administration, making it easier for beginners to learn.Cloud & Big Data ExpertiseLearning Snowflake enhances cloud computing and data warehousing skills, which are essential in the modern data-driven industry.Integration with BI & AI ToolsSnowflake integrates with Tableau, Power BI, Looker, Python, TensorFlow, and many other analytics and AI tools.Future-Proof TechnologySnowflake is growing rapidly as enterprises shift to cloud-based, scalable solutions.By mastering Snowflake, professionals can position themselves at the forefront of cloud data warehousing, analytics, and big data processing, making it a valuable skill for future-proofing careers in data engineering, analytics, and cloud computing.Snowflake: A Comprehensive Guide to Cloud Data Warehousing - Course CurriculumSection 1: Introduction to SnowflakeOverview of Data WarehousingImportance of Cloud ComputingThe Snowflake Story: Evolution & Use CasesSection 2: Getting Started with SnowflakeSigning Up for SnowflakeExploring the Snowflake UICreating Databases, Schemas, and TablesLoading Data into a TableSetting Up Essential Snowflake ToolsAssignment: Create, Load & Query a TableSection 3: Snowflake Compute - Virtual WarehousesCreating Virtual WarehousesWarehouse Sizes & ScalabilityMaximized vs. Auto Scaling ModesMulti-Cluster Warehouse Scaling PoliciesAssignment: Create a New Virtual WarehouseSection 4: Architecture, Features & PricingSnowflake Key Concepts & ArchitectureCloud Platform Support & Global RegionsSnowflake Editions & ReleasesUnderstanding Snowflake PricingData Integration & InteroperabilityQuiz: Snowflake ConceptsSection 5: Loading & Unloading Structured DataData Ingestion Methods & Best PracticesSteps for Managing Data LoadsPreparing & Staging DataLoading Data from Internal & External StagesSnowpipe: Real-Time Data LoadingQuiz: Data Ingestion in SnowflakeSection 6: Semi-Structured Data HandlingLoading & Unloading JSON DataRunning Analytics on JSON DataWorking with ORC & Parquet FormatsAssignment: Load JSON Data from an S3 BucketSection 7: Data Transformations & StagingQuerying & Transforming Data in Staged FilesMetadata Insights for Staged FilesTransformations During Data LoadSection 8: Managing Databases, Tables & ViewsTemporary, Transient & Permanent TablesExternal Tables & Their UsesOverview of Views & Materialized ViewsTable Design ConsiderationsSection 9: Time Travel, Failsafe & Zero Copy ClonesTime Travel: Restoring to a Specific PointAssignment: Implement Time Travel & RecoveryUnderstanding Failsafe & Storage UtilizationAssignment: Analyze Storage Used by Fail-SafeZero Copy Cloning & Cloning with Time TravelQuiz: Time Travel & Zero Copy ClonesSection 10: Performance OptimizationOptimization Strategies in SnowflakeUsing Dedicated Virtual WarehousesScaling Out with Multi-Cluster Virtual WarehousesMaximizing Query Cache UtilizationLab: Query Caching in ActionClustering Large Tables for Better PerformanceLab: Implementing Cluster KeysSearch Optimization TechniquesQuiz: Performance OptimizationSection 11: Secure Data SharingSecure Data Sharing ConceptsSharing Data with Snowflake & Non-Snowflake UsersAssignment: Share a Table with Another UserLab: Sharing Schemas, Databases & ViewsQuiz: Secure Data SharingSection 12: Snowflake Access ManagementSnowflake's Role-Based Access Control ModelRole Hierarchy: ACCOUNTADMIN, SYSADMIN, SECURITYADMINManaging Custom Roles & PermissionsLab: Assigning Privileges via Custom RolesQuiz: Snowflake Access ManagementSection 13: Advanced FeaturesChange Tracking with Table StreamsAutomating Workflows with TasksUser-Defined Functions (UDFs) & Stored ProceduresColumn-Level & Row-Level SecurityImplementing Resource Monitors Overview Section 1: Introduction to Data Warehouse Lecture 1 Part 1 - Introduction to Data Warehouse Lecture 2 Part 2 - Introduction to Data Warehouse Section 2: Dimensional Modelling Lecture 3 Dimensional Modelling Section 3: ETL and ELT in Data Warehouse Lecture 4 ETL and ELT in Data Warehouse Section 4: Introduction to Snowflake and its Architecture Lecture 5 Introduction to Snowflake and its Architecture Section 5: Snowflake Database and Pricing Lecture 6 Snowflake Database and Pricing Section 6: Snowflake Cost Management Lecture 7 Snowflake Cost Management Section 7: Loading Data into Snowflake Lecture 8 Loading Data into Snowflake Section 8: Transformation while Loading the Data Lecture 9 Transformation while Loading the Data Section 9: Copy Option Lecture 10 Copy Option Section 10: Loading of Semi-structured Data (JSON) Lecture 11 Loading of Semi-structured Data (JSON) Section 11: Loading of Parquet Data and File Format Object Lecture 12 Loading of Parquet Data and File Format Object Section 12: Performance Optimization in Snowflake Lecture 13 Part 1 - Performance Optimization in Snowflake Lecture 14 Part 2 - Performance Optimization in Snowflake Section 13: Uploading Data from AWS to Snowflake Lecture 15 Uploading Data from AWS to Snowflake Section 14: Unloading Data from Snowflake to AWS Lecture 16 Unloading Data from Snowflake to AWS Section 15: Snowpipe Lecture 17 Snowpipe Section 16: Stream Lecture 18 Part 1 - Stream Lecture 19 Part 2 - Stream Section 17: Zero-Copy Cloning and Swapping Lecture 20 Zero-Copy Cloning and Swapping Section 18: Time Travel Lecture 21 Time Travel Lecture 22 Time Travel - Practical Section 19: Fail Safe Lecture 23 Fail Safe Section 20: Types of Tables in Snowflake Lecture 24 Types of Tables in Snowflake Section 21: Snowflake Access Management Lecture 25 Part 1 - Snowflake Access Management Lecture 26 Part 2 - Snowflake Access Management Section 22: Snowflake interview Questions Lecture 27 Snowflake interview Questions Data Engineers - To learn how to design and optimize Snowflake-based ETL/ELT pipelines.,Data Analysts - To perform high-performance SQL queries and optimize reporting workloads.,Data Scientists - To leverage Snowflake's powerful compute capabilities for large-scale data analysis.,Database Administrators (DBAs) - To understand multitenancy, storage, and security features in Snowflake.,Cloud Engineers - To manage virtual warehouses, scaling policies, and cloud integrations.,Business Intelligence (BI) Developers - To work with structured and semi-structured data using tools like Tableau, Power BI, and Looker.,ETL Developers - To learn data ingestion, transformation, and loading best practices in Snowflake.,Security Engineers - To implement role-based access control (RBAC), encryption, and data governance.,IT Managers - To understand cost optimization, pricing, and scaling strategies.,Software Engineers - To learn how to use Snowflake's UDFs, stored procedures, and automation tools.,Solution Architects - To design scalable, secure, and optimized cloud data platforms.,Aspiring Data Engineers & Analysts - To gain hands-on skills in data warehousing and cloud analytics.,IT Professionals Transitioning to Cloud & Big Data - To stay relevant in the evolving cloud-based data ecosystem. 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Free Download Snowflake End-to-End Cloud Data Warehousing & Analytics Published 10/2024 Created by Uplatz Training MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 39 Lectures ( 30h 44m ) | Size: 15.3 GB Build Cloud Data Platform with Snowflake. Accelerate your career in data engineering, data science, and cloud computing. What you'll learn Understand Data Warehousing Fundamentals - Gain foundational knowledge of data warehousing, including concepts and principles, and how they relate to Snowflake. Master Data Modeling Techniques - Learn best practices for designing efficient data models to optimize performance and storage in Snowflake. Explore Snowflake Architecture - Understand Snowflake's unique architecture and how it supports cloud-native data warehousing and analytics. Create and Manage Data Warehouses in Snowflake - Develop practical skills in creating and managing data warehouses using Snowflake's interface and tools. Efficiently Load and Unload Data - Learn to load and unload data using various methods, including from external storage solutions (AWS, Azure, GCP). Effectively Manage Complex Data Formats - Handle complex formats like JSON and Parquet using Snowflake. Implement Data Transformations - Gain expertise in performing transformations during the data loading process to clean and structure data efficiently. Learn Snowflake's performance optimization features - caching, clustering and resource monitoring to ensure cost-effective and high-performance data operations. Leverage Time Travel, Fail Safe, and Zero-Copy Clone - Explore Snowflake's advanced features like Time Travel, Fail Safe, and Zero-Copy Clone for data recovery. Manage Secure Data Sharing - Learn how to securely share data within and outside of Snowflake environments, including with non-Snowflake users. Implement Best Practices for Snowflake Administration - Master account administration, access management, and apply best practices for efficient Snowflake usage Requirements Enthusiasm and determination to make your mark on the world! Description A warm welcome to the Snowflake: End-to-End Cloud Data Warehousing & Analytics course by Uplatz.Snowflake is a cloud-based data warehousing platform designed to handle massive volumes of structured and semi-structured data. It's built from the ground up to leverage cloud infrastructure, offering scalability, performance, and ease of use. Snowflake is not tied to any specific cloud provider; it runs on AWS, Microsoft Azure, and Google Cloud Platform (GCP), providing flexibility for businesses to use their preferred cloud platform.Snowflake's architecture, scalability, and advanced features make it a powerful platform for modern data warehousing, analytics, and data engineering. Its flexibility to handle massive datasets, structured and semi-structured data, and multi-cloud capabilities has positioned it as a preferred choice for businesses looking to leverage cloud-native data platforms.How Snowflake WorksSnowflake operates using a unique architecture that separates storage and compute, allowing for independent scaling of resources. Key methodology in its working involves:Data Storage: Snowflake stores data in a compressed, columnar format on cloud storage. Data is logically organized into databases, schemas, and tables, but physically, Snowflake manages how data is stored and optimized on the backend.Compute Layer (Virtual Warehouses): Compute resources, called virtual warehouses, are independent clusters of resources that process queries and workloads. Virtual warehouses can be scaled up or down based on performance needs and can run multiple, parallel queries without interfering with each other.Cloud Services Layer: This layer manages metadata, optimization, security, and query parsing. It handles authentication, query planning, and transaction management, allowing Snowflake to offer features like automated scaling, data sharing, and access controls.The separation of storage and compute makes Snowflake highly flexible. You can store large volumes of data without worrying about compute costs when the data is not being queried. Conversely, you can scale compute resources for demanding queries without impacting the storage cost.Core Features of SnowflakeSeparation of Storage and Compute: Snowflake allows independent scaling of compute resources (virtual warehouses) and storage. This flexibility helps optimize costs and performance based on workload requirements.Multi-Cloud Availability: Snowflake runs on all major cloud platforms (AWS, Azure, GCP), offering cross-cloud functionality and flexibility in choosing cloud providers.Instant Elasticity: Snowflake can instantly scale compute resources up or down based on workload demands. You can run multiple queries simultaneously without performance degradation.Data Sharing: Snowflake offers secure data sharing across organizations or between Snowflake accounts without moving or copying data. This feature allows real-time data collaboration.Support for Structured and Semi-Structured Data: Snowflake natively supports a wide range of data formats, including JSON, Parquet, Avro, and XML, making it easier to load and query semi-structured data alongside structured data.Zero-Copy Cloning: This feature allows you to create a copy of databases, tables, and schemas instantly without duplicating the data. It enables quick testing or development without additional storage costs.Time Travel and Fail-Safe: Time Travel allows users to access historical data versions for up to 90 days, facilitating recovery from accidental data changes or deletions. Fail-Safe provides an additional data recovery mechanism for a defined period.Automatic Scaling and Concurrency: Snowflake automatically manages concurrency, allowing multiple users to query data simultaneously without affecting performance, and automatically scales up or down depending on demand.Security and Compliance: Snowflake includes robust security features such as end-to-end encryption, role-based access controls, and multi-factor authentication (MFA). It complies with industry standards like GDPR, HIPAA, and SOC 2.Snowpipe: Snowpipe is Snowflake's continuous data ingestion tool that automates loading data from external sources (such as AWS S3, Azure Blob, GCP Storage) into Snowflake in near real-time.Snowflake - Course CurriculumIntroduction to Data Warehouse - part 1Introduction to Data Warehouse - part 2Data Modelling - part 1Data Modelling - part 2Introduction to Snowflake and ArchitectureCreate Datawarehouse in SnowflakeLoad Data in a TableSnowflake Pricing and Resource MonitorLoading Data from External StorageTransformations while LoadingCopy Options and File Formats - part 1Copy Options and File Formats - part 2Loading of JSONLoading of ParquetData UnloadingPerformance Optimizations in SnowflakeCaching and ClusteringLoading Data from AWS External StorageSnowpipe in AWSLoading Data from Azure CloudSnowpipe in AzureLoading and Uploading Data from GCPTime Travel - part 1Time Travel - part 2Fail Safe and Types of TablesZero Copy CloneData Sharing - part 1Data Sharing - part 2Data Sharing with non-Snowflake Users - part 1Data Sharing with non-Snowflake Users - part 2Secure vs Normal ViewData SamplingScheduling TasksMaterialized View - part 1Materialized View - part 2Dynamic Data MaskingAccess Management and Account Administration - part 1Access Management and Account Administration - part 2Best Practices in Snowflake Who this course is for Data Engineers - Looking to build data pipelines and handle data transformations within Snowflake. Data Analysts - Aiming to perform data querying, reporting, and analysis on cloud-based data platforms. Beginners and newbies aspiring for a career in Cloud Data Warehousing and Snowflake. Data Architects - Designing scalable cloud data architectures using Snowflake's features. Solution Architects - Architecting comprehensive solutions that integrate Snowflake for efficient data management and analytics. Cloud Engineers - Implementing and managing cloud infrastructure for data operations on Snowflake. Business Intelligence Professionals - Using Snowflake for analytics, reporting, and generating business insights. ETL Developers - Handling Extract, Transform, Load (ETL) processes using Snowflake for efficient data movement and transformation. Data Scientists - Working with large datasets, performing advanced analytics, and leveraging Snowflake for machine learning workflows. Cloud Data Engineers - Focused on developing data solutions in the cloud using Snowflake's infrastructure. Database Administrators (DBAs) - Transitioning to cloud data platforms like Snowflake for managing and optimizing data storage and access. Developers - Needing to integrate Snowflake with other applications and services. IT Professionals - Transitioning to cloud-based data solutions and aiming to broaden their cloud data expertise. 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Free Download Major Snowflake Pitfalls You Should Learn About Published 10/2024 Created by Cristian Scutaru MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 59 Lectures ( 10h 52m ) | Size: 5.79 GB Traps you should be aware of and things you may struggle to understand properly when learning about Snowflake What you'll learn Confusing concepts about Snowflake Why Snowflake implemented some features in a certain way Traps you should learn to avoid when using Snowflake Some difficult areas you may struggle to understand Uncommon ways SQL itself evolved and Snowflake had to support it Many other things nobody else will tell you about Requirements Optional basic knowledge of Snowflake Basic SQL programming knowledge Some basic Python or JavaScript programming skills Description If you already know Snowflake, you may not be aware of many traps I'll talk about in this original course. You cannot become an expert in Snowflake unless you learn about them. If you do not know Snowflake yet, here are some things you may struggle to properly understand.This course will focus mostly on pitfalls. For in-depth knowledge of Snowflake, I'll leave pointers and references to other better sources. Most lectures will not have the typical hands-on experiments you will encounter in my other specialized courses. The minimal requirements are some basic SQL and Python programming skills.What will be very valuable here to you is that I'll share my years of experience with Snowflake, to make you aware of pitfalls nobody else may tell you about. I learned about them the hard way. Avoid doing the same.CredentialsThe only world-class expert from Canada selected for the Snowflake Data Superhero program in 2021.SnowPro Certification SME (Subject Matter Expert): i.e. dozens of exam questions have been created by me.I passed five SnowPro certification exams, all from the first attempt: Core, Architect, Engineer, Analyst, Scientist.Highly specialized in Snowflake for the past few years, as a Data and Solutions Architect in AWS, Azure and GCP.I served dozens of clients working for Snowflake Partner companies or as an independent consultant.Enroll today, to keep this course forever! Who this course is for Those who already know Snowflake, but need to find more Beginners in Snowflake, willing to be aware of hidden traps before learning more Homepage https://www.udemy.com/course/snowflake-pitfalls/ Screenshot Rapidgator https://rg.to/file/74ed1f2adb5e5b8a640aa6145da300fc/gqogw.Major.Snowflake.Pitfalls.You.Should.Learn.About.part4.rar.html https://rg.to/file/7c18a7ebc6a4954f41eb18ed4808db12/gqogw.Major.Snowflake.Pitfalls.You.Should.Learn.About.part3.rar.html https://rg.to/file/912ea0ad8ef1074ff6fa41bf9718ee06/gqogw.Major.Snowflake.Pitfalls.You.Should.Learn.About.part2.rar.html https://rg.to/file/9c8ae86fd8d1982c704e31f16283f778/gqogw.Major.Snowflake.Pitfalls.You.Should.Learn.About.part6.rar.html https://rg.to/file/be9907c9305d333d8fd65490f1ba9763/gqogw.Major.Snowflake.Pitfalls.You.Should.Learn.About.part5.rar.html https://rg.to/file/f01e17fc4d85cbf18c631ab275066de4/gqogw.Major.Snowflake.Pitfalls.You.Should.Learn.About.part1.rar.html Fikper Free Download https://fikper.com/C49qIrWcOy/gqogw.Major.Snowflake.Pitfalls.You.Should.Learn.About.part2.rar.html https://fikper.com/JsaJatmrkB/gqogw.Major.Snowflake.Pitfalls.You.Should.Learn.About.part1.rar.html https://fikper.com/RHo1GqRjWY/gqogw.Major.Snowflake.Pitfalls.You.Should.Learn.About.part6.rar.html https://fikper.com/arlvxGZCFs/gqogw.Major.Snowflake.Pitfalls.You.Should.Learn.About.part5.rar.html https://fikper.com/e0d1uvbZuu/gqogw.Major.Snowflake.Pitfalls.You.Should.Learn.About.part4.rar.html https://fikper.com/zVFrXnh5tw/gqogw.Major.Snowflake.Pitfalls.You.Should.Learn.About.part3.rar.html No Password - Links are Interchangeable

Free Download Data Pipelines with Snowflake and Streamlit Published 9/2024 Created by Marcos Vinicius Oliveira MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 40 Lectures ( 5h 17m ) | Size: 2.1 GB Using Snowflake to data engineer Kaggle and Google Trends data with Python procedures and tasks What you'll learn: Setup Snowflake and AWS Accounts Work with Kaggle and SerpAPI Download and manipulate data with Jupyter Notebooks on VS Code Work with External Access Integration and Storage Integration on Snowflake Create Snowflake Python based procedures Create Snowflake tasks Create Streamlit apps inside of Snowflake Requirements: Proficient knowledge on SQL and basic knowledge on Snowflake database Basic knowledge on data modeling and engineering Proficient Python knowledge Description: This course focuses on building a data engineering pipeline that integrates multiple data sources, including Kaggle datasets and Google Trends data (fetched via SerpAPI), to analyze the relationship between Netflix show releases and the popularity of actors. You'll learn to gather and combine data on Netflix actors and their trends on Google, particularly in the weeks following a show's release.You will use Kaggle as a source for the Netflix shows and actors dataset and Google Trends (accessed via SerpAPI) to fetch real-time search data for the actors. This data will be stored and processed within the Snowflake database, leveraging its cloud-native architecture for optimal scalability and performance.Technical Stack Overview:Snowflake Database: The central repository for storing and querying data.Streamlit in Snowflake: A web app framework to visualize the data directly inside Snowflake.AWS S3: For data storage and retrieval, particularly for intermediate datasets.Snowflake Python Procedures: Automating data manipulation and pipeline processes.Snowflake External Access & Storage Integrations: Managing secure access to external services and storage.By the end of the course, you'll have a fully functional data pipeline that processes and combines streaming data, cloud storage, and APIs for trend analysis, visualized through an interactive Streamlit app within Snowflake. Who this course is for: Data Engineers looking to get proficient on Snowflake and Streamlit for building data pipelines Homepage https://www.udemy.com/course/data-pipelines-with-snowflake-and-streamlit/ Rapidgator https://rg.to/file/f0629de1f792eeeebd379ae716fd2bad/yjmzv.Data.Pipelines.with.Snowflake.and.Streamlit.part1.rar.html https://rg.to/file/7f9c73ecc73cc0f8d2c385710cbea0fa/yjmzv.Data.Pipelines.with.Snowflake.and.Streamlit.part2.rar.html https://rg.to/file/6731a5ce1a015365253b5a46c6bf42a0/yjmzv.Data.Pipelines.with.Snowflake.and.Streamlit.part3.rar.html Fikper Free Download https://fikper.com/hKSvOh0u9B/yjmzv.Data.Pipelines.with.Snowflake.and.Streamlit.part1.rar.html https://fikper.com/WRYC5cNE7A/yjmzv.Data.Pipelines.with.Snowflake.and.Streamlit.part2.rar.html https://fikper.com/GRagTmZo87/yjmzv.Data.Pipelines.with.Snowflake.and.Streamlit.part3.rar.html No Password - Links are Interchangeable

Free Download Snowflake Mastery - Easy steps to gain expertise [2024] Last updated 1/2024 Created by AlphaEdge Solutions MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + subtitle | Duration: 167 Lectures ( 19h 3m ) | Size: 6.6 GB Snowflake Mastery: An easy step by step approach to be an expert in snowflake What you'll learn: You will learn about the Snowflake Architecture and Performance management Deep Dive in to the Access management and the type of Db objects Understand in full detail how the data moves from external system to Snowflake Deep knowledge on Dynamic data masking and visualization Extensive knowledge on Data Sharing and Data Protection Requirements: No Programming experience needed. You will learn every thing from scratch. However a basic understanding of relational database and SQl is required. Description: Are you a technology professional or college graduate who have thought multiple times to learn snowflake but couldn't learn it so far? Is your self snowflake learning a struggle? As a busy technology professional, do you feel overwhelmed and frustrated with all the 'answers' to master snowflake, but still not sure which one is right for you? Have you wondered, how many days , weeks and months are passed in just thinking about learning snowflake? The time is NOW to get started.In this course, you will discover exactly what you need to focus on to master snowflake. We will take you through an easy step by step approach to learn and master snowflake in shortest period of time with out overwhelm.Cloud is the new norm, almost all tech giants are moving towards cloud platform for the solutions which are cost effective and scalable. Cloud data-warehousing aka Snowflake warehouse is one the fastest growing technology which most of the technology companies are adopting. This is going to be big in future, hence this is the right time to get into the ship to learn and equip ourselves will all the knowledge of snowflake and prepare ourselves for better career today and in future. So if you find yourself saying "May be I will try it another time ". I would say THE TIME IS NOW. Don't let yourself go another day, another week, another month of learning procrastination. It's time RIGHT NOW to get on the journey of learning and have the life knowledge and excellent career you have designed for you.Added the new section on Dynamic Tables for year 2024.Following modules will be covered in a very easily step by step approachSnowflake Architecture and Performance ManagementIntroductionCreate Trial accountKnow your UI interfaceShared and Non Shared Disk ArchitectureHigh Level ArchitectureCreate Virtual WarehousesScaling PolicyCreate First Database and TableLoad CSV from public S3 bucketSnowflake ArchitectureSnowflake EditionsCreditsCredit Usage ScenariosCredit to Dollar Storage costCredit Storage ConsumptionPerformance ManagementPerformance Improvement MethodsDedicated Virtual WarehousesDedicated Virtual Warehouses CreationScale Up and Scale DownScale Out and Scale InMaximize CachingMaximize Caching demonstrationClustering KeysClustering CostClustering PerformanceMicropartitionsAccess management and snowflake objectsAccess managementAccess control and RBACSecurable objectsRolesTables in snowflakeTable TypesDatabase and schema typeUser Defined Functions (UDF's) and Stored ProceduresUser defined functions (UDF's)Stored procedures (SP's)Secure UDF's and SP'sViewsNon Materialized viewsMaterialized viewsData Movement - Techniques and UnloadingData Loading techniquesTypes of Data loadKnow snowflake stagesInstall SnowsqlInternal StagesUserstageTablestageNamedstageExternal StagesCOPY CommandCOPY TransformationFile Format ObjectCOPY OPTIONSON ERRORSIZE LIMITRETURN_FAILED_ONLYENFORCE_LENGTH / TRUNCATECOLUMNSFORCE / LOAD_UNCERTAIN_FILESLOAD_HISTORYVALIDATION MODELogging rejected recordsData loading best practicesData UnloadingData unloading theoryCOPY into location - Internal Stage -> User stageResolving max_workers must be greater than 0COPY into location - Internal Stage -> Table stageCOPY into location - Internal Stage -> Named Internal StageUnloading using QueryUnloading to Multiple FilesData Movement - Data loadingLoading from AWSCreate AWS free-tier accountCreate S3 bucket, file and roleStorage integration objectLoad file from AWSUnload data to AWSLoading from AzureCreate Azure free trial accountCreate storage and containerIntegration objectLoad data from AzureUnload data to AzureLoading from GCPCreate GCP free trial account, create bucket and upload fileIntegration objectLoad data from GCPUnload data to GCPLoading Semi-Structured DataIntroductionProcess and understanding the demo dataJSON: Load raw data and analyze nested objectsJSON: FLATTENArray/ObjectsHierarchicalJSON: Data transformation and loadJSON: Querying DataPARQUET: File load and transformationSnowpipeOverviewCreate snowpipe, load and configureTroubleshooting and pipe refreshManage snowpipeDynamic Data Masking and VisualizationDynamic data maskingOverviewCreate masking policyChange, Unset and replace masking policyConditional maskingData VisualizationSnowsight - Dashboard and VisualizationGetting started with TableauTableau visualization from snowflake dataPartner ConnectOverviewPartner connect categoriesData Sharing and Data ProtectionData SharingOverviewData sharing demo of Table, External tables and UDF's.Data share to a reader accountImported privilegesData share - entire databaseData share operations - DDL and DML affectSharing views and materialized viewsTime TravelOverview and retrieve data using "at" and "before"Data restoration using direct methodData restoration using indirect methodUNDROPUnderstanding retention timeFail-SafeOverviewFail Safe demoZero-Copy CloningOverviewCloning permanent tablesCopy grants and clone temporary external tablesClone schema and databaseSwapClone using time travel and understand sharing vs cloningStreamsOverviewConsuming streams using insert, update and deleteTypes of streams - default, append only. Consume stream using false conditionInsert only streams for external tablesMultiple consumers with streamsChanges clauseStreams consideration and stale after attributeRecreate, rename and clone effect on streamTasksUnderstanding tasksCreate task using procedure when and troubleshoot taskScheduling tasks using CRONCRON - Daylight savings considerationsDAG - Tree of tasksTask with streamUser managed tasks and warehouse considerationsSampling DataOverviewRow sampling methodSystem block methodAccess management in practiceSystem defined roles and its usersCustom roles and its usersCreate objects from sysadmin role and assign to developer roleCreate custom users - developer1, developer2,qa1 and reader1Problems due to unassigned custom rolesSolution of the problemsPublic RoleBest PracticesAuto resume, success and failure and long running queriesResource monitorColumns storage cost and benchmarking the queriesDynamic Tablesa. Dynamic Table Theoryb. Dynamic Table Create Data Pipeline - Part1c. Dynamic Table Create Data Pipeline - Part2Enjoy and Happy Learning ! Who this course is for: Have you wondered, how many days , weeks and months are passed in just thinking about learning snowflake? In this free challenge you will kickstart your journey towards snowflake. The time is NOW to get started. 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Free Download Data Platforms - Spark to Snowflake Released 9/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill Level: Beginner | Genre: eLearning | Language: English + srt | Duration: 54m | Size: 96 MB Explore the expansive realm of big data in this course from industry leader Pragmatic AI Labs. Instructor Kennedy Behrman covers the essentials of big data processing on key platforms like Apache Hadoop, Apache Spark, and Snowflake. Throughout the course, learn how to work with resilient distributed datasets (RDDs) and leverage Spark SQL for managing dataframes. Delve into Snowflake to understand its unique architecture, navigate its web UI, and utilize its Python connector for data manipulation. Along the way, engaging demos provide opportunities for you to get hands-on experience with each platform, ensuring you not only grasp the theoretical concepts but also how to apply them in practical scenarios. Whether you're a data scientist, a data analyst, an IT professional, or simply eager to learn more about big data, this course offers valuable insights and skills on some of the most cutting-edge data management technologies available today. Homepage https://www.linkedin.com/learning/data-platforms-spark-to-snowflake TakeFile https://takefile.link/yvva6z6adlp2/bzfwb.Data.Platforms.Spark.to.Snowflake.rar.html Rapidgator https://rg.to/file/fd65513876ac5d64a3395b469045cb22/bzfwb.Data.Platforms.Spark.to.Snowflake.rar.html Fikper Free Download https://fikper.com/OBzpli8knd/bzfwb.Data.Platforms.Spark.to.Snowflake.rar.html No Password - Links are Interchangeable

Free Download Unlock Snowflake Snowpro Advanced Architect Strategies Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.37 GB | Duration: 1h 59m Master Snowflake: Architect Modern Data Solutions in Cloud, Insights for Optimal Performance, Security and Helpful Tips. What you'll learn Get a deep understanding of Snowflake's architecture, including its multi-cluster, shared-data model, and separation of storage and compute. Unleash advanced data modeling techniques, such as clustering keys, materialized views, & query optimization, to optimize data organization & query performance. Understand Snowflake's virtual warehouses and learn how to effectively scale resources, allocate compute power, and optimize performance. Ensure security and compliance in Snowflake environments by implementing encryption, role-based access control (RBAC), and secure data sharing practices. Architect and implement data pipelines, real-time data loading, and integration with ETL tools for seamless data processing. Develop disaster recovery plans, implement backup and restore strategies, and ensure business continuity in Snowflake environments. Optimize costs through efficient management of Snowflake credits, auto-suspending and scaling resources, and leveraging query and storage optimization features. Learn emerging trends and innovations in cloud data warehousing, including Snowflake's roadmap and upcoming features, data lake and data mesh architectures. and much more Requirements Willingness or Interest to learn about Snowflake SnowPro Advanced Architect for Success. Description IMPORTANT before enrolling:This course is not intended to replace studying any official vendor material for certification exams, is not endorsed by the certification vendor, and you will not be getting the official certification study material or a voucher as a part of this course."Snowflake Mastery: Architecting Modern Data Solutions in the Cloud"In today's digital landscape, data has become the lifeblood of businesses, driving decision-making, innovation, and competitive advantage. Snowflake, with its revolutionary cloud data platform, has emerged as a powerhouse in modern data warehousing and analytics. This comprehensive course is designed to equip professionals with the advanced skills and knowledge needed to harness the full potential of Snowflake for building robust and scalable data solutions.SnowPro Advanced Architect certification focuses on validating proficiency in designing, architecting, and implementing complex data solutions using Snowflake.Throughout the course, parti[beeep]nts will embark on a journey to delve deep into the intricacies of Snowflake's architecture, exploring its multi-cluster, shared-data model, and the separation of storage and compute. They will gain a profound understanding of how Snowflake ensures security and data isolation, essential for safeguarding sensitive information in today's data-driven world.Moving beyond the fundamentals, parti[beeep]nts will master Snowflake's virtual warehouses, learning how to optimize performance and resource allocation effectively. They will explore advanced concepts such as clustering keys, materialized views, and query optimization techniques, empowering them to fine-tune data organization and enhance query performance.Course will also delve into best practices for data modeling and warehousing, providing insights into crafting effective data models, managing time-travel, and implementing slowly changing dimensions (SCDs). Parti[beeep]nts will learn to navigate between star and snowflake schemas, while also gaining proficiency in handling semi-structured data, a crucial aspect in today's diverse data landscape.Performance tuning and scaling are vital components of any data solution, and this course equips parti[beeep]nts with the knowledge to scale Snowflake resources effectively, monitor query performance, and identify and address performance bottlenecks. They will learn to utilize resource monitors and queues to optimize performance and enhance overall efficiency.Security and compliance are paramount in data management, and parti[beeep]nts will explore Snowflake's robust security architecture, including encryption, role-based access control (RBAC), and secure data sharing. They will gain insights into implementing data pipelines, real-time data loading, and integrating Snowflake with ETL tools, ensuring seamless data integration and processing.Business continuity and disaster recovery planning are critical considerations in today's dynamic business environment. Parti[beeep]nts will understand Snowflake's high availability architecture, craft effective failover and disaster recovery plans, and implement backup and restore strategies to ensure business continuity in Snowflake environments.Cost optimization and management play a significant role in data projects, and parti[beeep]nts will learn to manage Snowflake credits, optimize costs through auto-suspending and scaling resources, and leverage query and storage optimization features for cost efficiency. They will explore strategies for reducing data storage costs, maximizing value while minimizing expenses.Finally, course will provide a glimpse into future trends and innovations in cloud data warehousing, exploring Snowflake's roadmap and upcoming features. Parti[beeep]nts will embrace emerging trends such as data lake and data mesh architectures, preparing them to stay ahead in the ever-evolving landscape of data analytics and architecture.This course empowers professionals to become adept Snowflake architects, capable of architecting modern data solutions that drive business success in the cloud era.Thank you Overview Section 1: Snowflake Architecture Lecture 1 Snowflake's Cloud Data Platform Lecture 2 Snowflake's Multi-cluster, Shared-data Architecture Lecture 3 Snowflake's Separation of Storage & Compute Lecture 4 Security and Data Isolation Section 2: Advanced Snowflake Concepts Lecture 5 Snowflake Virtual Warehouses Lecture 6 Clustering Keys & Data Organization Lecture 7 Power of Materialized Views Lecture 8 Fine-tuning Query Optimization Techniques Lecture 9 Strategies for Effective Data Ingestion and Loading Section 3: Data Modeling & Warehousing Best Practices Lecture 10 Snowflake Data Models Lecture 11 Star and Snowflake Schema Lecture 12 Time-Travel and Data Versioning Lecture 13 Slowly Changing Dimensions (SCDs) Lecture 14 Semi-Structured Data: Best Practices Section 4: Performance Tuning and Scaling Lecture 15 Scaling Snowflake Resources for Enhanced Performance Lecture 16 Monitoring and Optimizing Query Performance Lecture 17 Identify & Address Performance Bottlenecks Lecture 18 Utilize Resource Monitors & Queues for Performance Optimization Section 5: Security and Compliance Lecture 19 Snowflake's Security Architecture: Encryption and Key Management Lecture 20 Role-based Access Control Lecture 21 Secure Data Sharing and External Data Sources Lecture 22 Compliance with Snowflake's Security Standards Lecture 23 Auditing and Monitoring for Enhanced Security Section 6: Data Pipelines and Integration Lecture 24 Data Pipelines with Snowflake Streams Lecture 25 Real-time Data Loading and Processing Lecture 26 Integrating Snowflake with ETL Tools: Best Practices Lecture 27 Change Data Capture (CDC) Lecture 28 Data Replication and High Availability Strategies Section 7: Business Continuity and Disaster Recovery Lecture 29 Snowflake's High Availability Architecture Lecture 30 Failover and Disaster Recovery Plans Lecture 31 Effective Backup and Restore Strategies Lecture 32 Business Continuity Planning in Snowflake Environments Section 8: Cost Optimization and Management Lecture 33 Managing and Monitoring Snowflake Credits for Cost Optimization Lecture 34 Optimizing Costs through Auto-suspending and Scaling Resources Lecture 35 Leverage Snowflake's Query & Storage Optimization Features for Cost Efficiency Lecture 36 Strategies for Reducing Data Storage Costs Section 9: Future Trends and Innovations Lecture 37 Evolving Landscape of Cloud Data Warehousing Lecture 38 Snowflake's Roadmap and Upcoming Features: A Glimpse into the Future Lecture 39 Data Lake and Data Mesh Architectures Lecture 40 Analyzing Emerging Trends in Data Analytics and Architecture Data Architects: Individuals tasked with designing data models, schemas, and architectures that support the organization's analytical and reporting needs.,Data Scientists: Professionals who analyze complex datasets, develop predictive models, and extract valuable insights to solve business problems.,Data Engineers: Professionals responsible for designing and implementing data pipelines, optimizing data storage and retrieval, and ensuring data quality and reliability.,Database Administrators (DBAs): Administrators responsible for managing and maintaining databases, ensuring data security, and optimizing database performance.,IT Managers and Directors: Leaders responsible for overseeing data initiatives, driving digital transformation, and ensuring alignment with organizational goals.,Cloud Architects: Professionals with expertise in cloud computing who are responsible for designing and implementing cloud-based solutions.,Business Intelligence (BI) Analysts: Analysts who work with data to derive insights and drive informed decision-making within the organization.,Anyone interested in advancing their career in the field of data management, analytics, and cloud computing.,Whether you are a seasoned data professional looking to expand your skill set or a newcomer eager to enter the field of cloud data warehousing, this course provides the advanced knowledge and practical skills necessary to excel in today's data-driven world. 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