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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. 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