(Ebook PDF) Learn Azure Synapse Data Explorer A guide to building real time analytics solutions to unlock log and telemetry data 1st edition by Pericles Rocha 1803239611 9781803239613 full chapters

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Product details:

ISBN-10 :  1803239611 

ISBN-13 :  9781803239613

Author: Pericles Rocha 

A hands-on guide to working on use cases helping you ingest, analyze, and serve insightful data from IoT as well as telemetry data sources using Azure Synapse Data Explorer Free PDF included with this book Key Features Augment advanced analytics projects with your IoT and application data Expand your existing Azure Synapse environments with unstructured data Build industry-level projects on integration, experimentation, and dashboarding with Azure Synapse Book Description Large volumes of data are generated daily from applications, websites, IoT devices, and other free-text, semi-structured data sources.

Learn Azure Synapse Data Explorer: A guide to building real time analytics solutions to unlock log and telemetry data 1st Table of contents:

Part 1 Introduction to Azure Synapse Data Explorer
Chapter 1: Introducing Azure Synapse Data Explorer
Technical requirements
Understanding the lifecycle of data
Introducing the Team Data Science Process
Tooling and infrastructure
The need for a fast and highly scalable data exploration service
What is Azure Synapse?
Data integration
Enterprise data warehousing
Exploration on the data lake
Apache Spark
Log and telemetry analytics
Integrated business intelligence
Data governance
Broad support for ML
Security and Managed Virtual Network
Management interface
What is Azure Synapse Data Explorer?
Integrating Data Explorer pools with other Azure Synapse services
Query experience integrated into Azure Synapse Studio’s query editor
Exploring, preparing, and modeling data with Apache Spark
Data ingestion made easy with pipelines
Unified management experience
Exploring the Data Explorer pool infrastructure and scalability
Data Explorer pool architecture
Scalability of compute resources
Managing data on distributed clusters
Mission-critical infrastructure
How much scale can Data Explorer handle?
What makes Azure Synapse Data Explorer unique?
When to use Azure Synapse Data Explorer
Summary
Chapter 2: Creating Your First Data Explorer Pool
Technical requirements
Creating a free Azure account
Creating an Azure Synapse workspace
Basics tab
Security tab
Networking tab
Tags tab
Review + create tab
Finding your new workspace
Creating a Data Explorer pool using Azure Synapse Studio
Basics tab
Additional settings tab
Tags tab
Review + create tab
Creating a Data Explorer pool using the Azure portal
Creating a Data Explorer pool using the Azure CLI
Summary
Chapter 3: Exploring Azure Synapse Studio
Technical requirements
Exploring the user interface of Azure Synapse Studio
Running your first query
Creating a database
Loading the data
Verifying whether your data has loaded successfully
Working with data in Azure Synapse notebooks
Saving your work and configuring source control
Managing and monitoring Data Explorer pools
Scaling Data Explorer pools
Pausing and resuming pools
Monitoring Data Explorer pools
Summary
Chapter 4: Real-World Usage Scenarios
Technical requirements
Building a multi-purpose end-to-end analytics environment
Sources
Ingest
Store
Process
Enrich
Serve
User
Summary
Managing IoT data
Processing and analyzing geospatial data
Enabling real-time analytics with big data
Performing time series analytics
Summary
Part 2 Working with Data
Chapter 5: Ingesting Data into Data Explorer Pools
Technical requirements
Understanding the data loading process
Defining a retention policy
Choosing a data load strategy
Streaming ingestion
Batching ingestion
Performing data ingestion
Using KQL control commands
Building an Azure Synapse pipeline
Implementing continuous ingestion
Using other data ingestion mechanisms
Summary
Chapter 6: Data Analysis and Exploration with KQL and Python
Technical requirements
Analyzing data with KQL
Selecting data
Working with calculated columns
Plotting charts
Obtaining percentiles
Creating a time series
Detecting outliers
Using linear regression
Exploring Data Explorer pool data with Python
Creating an Apache Spark pool
Working with Azure Synapse notebooks
Reading data from Data Explorer pools
Plotting charts
Performing data transformation tasks
Creating a lake database
Summary
Chapter 7: Data Visualization with Power BI
Technical requirements
Introduction to the Power BI integration
Creating a Power BI report
Adding data sources to your Power BI report
Connecting Power BI with your Azure Synapse workspace
Authoring Power BI reports from Azure Synapse Studio
Summary
Chapter 8: Building Machine Learning Experiments
Technical requirements
Understanding the application of ML
Introducing ML into your projects with AutoML
Creating an Azure Machine Learning workspace
Configuring the Azure Machine Learning integration
Finding the best model with AutoML
Exploring additional ML capabilities in Azure Synapse
Using pre-trained models with Cognitive Services
Finding patterns using KQL
Training models with Apache Spark MLlib
Building applications with SynapseML
Summary
Chapter 9: Exporting Data from Data Explorer Pools
Technical requirements
Understanding data export scenarios
Exporting data with client tools
Using server-side export to pull data
Performing robust exports with server-side data push
Exporting to cloud storage
Exporting to SQL tables
Exporting to external tables
Configuring continuous data export
Summary
Part 3
Managing Azure Synapse Data Explorer
Chapter 10: System Monitoring and Diagnostics
Technical requirements
Monitoring your environment
Checking your Data Explorer pool capacity
Monitoring query execution
Reviewing object metadata and changes
Setting up alerts
Creating action groups
Creating alert rules
Summary
Chapter 11: Tuning and Resource Management
Technical requirements
Implementing resource governance with workload groups
Managing workload groups
Classifying user requests
Queuing requests for delayed execution
Speeding up queries using cache policies
Summary
Chapter 12: Securing Your Environment
Technical requirements
Security overview
Managing data encryption
Configuring data encryption at rest
Understanding data encryption in transit
Authenticating users
Configuring access to resources
Synapse RBAC roles
Reviewing role assignments
Assigning RBAC roles
Data Explorer database roles
Implementing network security
Using a managed virtual network
Managed private endpoint connection
Enabling data exfiltration protection
Controlling public network access
Protecting against external threats
Summary
Chapter 13: Advanced Data Management
Technical requirements
Managing extents
Extent tagging
Moving extents
Dropping extents
Purging personal data
Enabling purge on Data Explorer pools
Executing data purge operations
Monitoring data purge operations

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