DP-900- Microsoft Azure Data Fundamentals Questions And Answers Rated A+ New Update Assured Satisfaction

Az SQL managed instance benefit - native support for cross-db queries and transactions Azure Cosmos DB API: Graph Data - Gremlin API Azure Cosmos DB API: JSON Documents - MongoDB API Azure Cosmos DB API: Key/Value data - Table API Azure Data Factory control flow - control flow orchestrate pipeline activities that depend on the output of other pipeline activities Azure Data Lake Storage support RBAC - RBAC at file and folder level Batch workloads collect data and process data when condition is met - Not necessary daily. Can be weekly, monthly etc. Clustered index - is an object associated with a table that sorts and stores the data rows in table based on key values Cognitive analytics - Draw inferences from existing data and patterns, derive conclusions based on existing knowledge bases, and then add these findings back into the knowledge base for future inferences, a self-learning feedback loop Columnar - Lowest latency to retrieve data - Column-family db is the lowest latency store type Compute environment for Azure Data Factory activities - A linked serviceConfigure Azure Storage account to support security level at folder level and atomic directory manipulation - Enable hierarchical namespace - file system performance at object storage scale and prices Control Activity: Until - Do-Until loop Data movement Activity: Copy - Copy data from source to sink data source Data transformation: Mapping data flow - Graphical data transformation logic without writing code. Date Definition Language (DDL) - Crate DB Schema (e.g.: CREATE, DROP, RENAME, ALTER) Descriptive analytics - What occurred in the past Diagnostic analytics - Why events happened Embed documents and query results into a SQL notebook - Azure Data Studio In batch processing, it takes longer time to process in bulk - Latency is expected Massively parallel processing (MPP) engine of Az Synapse Analytics - Distributes processing across computer nodes Normalizing - Reduce data redundancy & Improves data integrity Does NOT eliminate relationshipOnline Transaction Processing (OLTP) characteristics - 1. Heavy writes and moderate reads 2. Schema on write 3. Normalized data Predictive analytics - What will happen in the future Prescriptive analytics - Which actions should be taken Provision Apache Spark clusters - Azure HDInsight and Azure Databricks Read only db replica to offload transactions - e.g. gen reports without affecting transactional workload Supports project-oriented offline db dev - SQL Server data Tools (SSDT) Throughput for an Azure Cosmos DB account - Database or container level Transact-SQL to query files in Azure Data Lake Storage from an Azure Synapse Analytics data warehouse - PolyBase - enables SQL server instance process Transact-SQL queries that read data from external data sources Transparent Data Encryption (TDE) - Encrypts DB to protect data at rest Trigger initiates the execution of a pipeline - Pipeline is a logical grouping of activities that together perform a task. Use OLAP to query a dimensional model in datawarehouse - Online Analytical Processing (OLAP) allows multidimensional analysisWhen ingesting data from Azure Data Lake Storage across Azure regions will incur costs - Costs for bandwidth