Instructor's Method - 6/14/2021

Question 1

Relational Storage

Answer 1

Options are

• SQL (Azure SQL, Managed Instance)
• MPP (Dedicated SQL Pool)

Question 2

Platform as a Service

Answer 2

I need a Database. I don’t have to manage underlying infrastructure.

Question 3

Azure SQL

Answer 3

Platform-as-Service

For SQL Service, MySQL, PostgreSQL

There are differences between Azure SQL and on-prem SQL Server

If starting a new project, recommends to use Azure SQL. Cheaper, much more scalable

Question 4

Database on VM

Answer 4

IaaS

SQL Server, Oracle

Question 5

Azure SQL Managed Instance

Answer 5

Platform-as-a-service

Dedicated infrastructure in Azure datacenter

~100% compatible with on-prem SQL Server

If you want lift-and-shift apps in the could that are using SQL server

Question 6

Symmetric Multi Processing Architecture

Answer 6

DB2, Oracle, SQL Server

Question 7

MPP architecture

Answer 7

Massive Parallel Processing Architecture

Dedicated SQL Pool (earlier it was known as Azure SQL Data Warehouse)

Question 8

Non-relational Storage

Answer 8

Azure Cosmos DB

Azure Storage

Azure Data Lake Store

Question 9

Azure Storage

Answer 9

Object storage

Cheaper service

Not compatible with Hadoop workloads

Lot of features

Question 10

Azure Data Lake Gen1

Answer 10

Object storage
webHDFS compatible (compatible with Hadoop workloads)

Very less features, faster

Question 11

Azure Data Lake Gen2

Answer 11

Combination of Data Lake Gen1 + Storage

Faster, Cheaper, webHDFS compatible

Question 12

Batch Processing

Answer 12

Azure Databricks

Azure HDInsight

Azure Data Link Analytics

Azure Synapse Analytics

Question 13

HDInsight

Answer 13

Earlier, it was Hortonworks distribution of Hadoop

MS took HDP and put it on Azure (you get Spark, Hadoop, Storm…)

HDP on Azure is called HDInsight

Question 14

4 options to use Apache Spark

Answer 14

1. Download Open source Spark
2. HDInsight
3. Azure Databricks
4. Azure Synapse => also has Spark

Question 15

Stream Processing

Answer 15

Azure Stream Analytics

Axure Databricks

Azure HDInsight

Question 16

Orchestration

Answer 16

Azure Data Factory

Question 17

Modern Data Warehouse

Answer 17

Bring together all your data at scale, and get insights through analytical dashboards, operational reports, or advanced analytics for all the users

Question 18

4 layers of Modern Data Warehouse

Answer 18

1. Ingestion (Extract)
2. Storage (Load)
3. Data Preparation (Transform)
4. Model & Serve (Serve)

Question 19

What Products can be used to Ingest data

Answer 19

Azure Data Factory

Question 20

What products can be used to Store data

Answer 20

Azure Storage

Data Lake Gen2

Question 21

What products can be used to Prepare Data

Answer 21

Azure HDInsight

Azure Databricks

Data Lake Analytics

Question 22

What products can be used to Model and Serve Data

Answer 22

Dedicated SQL Pool

Azure Analysis Services

Question 23

What products can be used to Visualize

Answer 23

PowerBI

Question 24

Azure Synapse Analytics

Answer 24

Does following

1. Ingestion (Extract)
2. Storage (Load)
3. Data Preparation (Transform)
4. Model & Serve (Serve)

Question 25

Azure Synapse Analytics features

Answer 25

Set of multiple integrated Azure Data services

Bring in multiple data sources at one place

Bring all your code at one place

Communication between different compute options

Centralized management, privacy, data, security

Question 26

Synapse Workspace / Studio

Answer 26

Storage: Data Lake Gen2

Compute: Dedicated SQL Pools, Apache Spark Pools,
Serverless SQL

Ingestion: Synapse Pipelines (Azure Data Factory integrated into Synapse), Mapping Data Flows (ETL, SSIS)

Platform: Monitoring, Management, Security

Connected Services: Azure Cosmos DB, Power BI, Azure ML

Question 27

Dedicated SQL Pool

Answer 27

SQL-based, fully-managed, petabyte-scale cloud data warehouse