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230302 ||| eng |
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|a 1803239611
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| 020 |
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|a 9781803239613
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| 050 |
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4 |
|a QA76.9.B45
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| 100 |
1 |
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|a Rocha, Pericles
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| 245 |
0 |
0 |
|a Learn Azure Synapse Data Explorer
|h [electronic resource]
|b A Guide to Building Real-Time Analytics Solutions to Unlock Log and Telemetry Data
|c Pericles (Peri) Rocha
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| 250 |
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|a 1st edition
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| 260 |
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|a Birmingham
|b Packt Publishing, Limited
|c 2023
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| 300 |
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|a 346 p.
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| 505 |
0 |
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|a 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
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| 505 |
0 |
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|a 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
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| 505 |
0 |
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|a Cover -- Title Page -- Copyright and Credit -- Dedicated -- Contributors -- Table of Contents -- Preface -- 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
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| 505 |
0 |
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|a 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
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| 505 |
0 |
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|a 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
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| 653 |
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|a Big data / fast
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| 653 |
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|a Cloud computing / fast
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| 653 |
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|a Big data / http://id.loc.gov/authorities/subjects/sh2012003227
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| 653 |
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|a Infonuagique
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| 653 |
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|a Données volumineuses
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| 653 |
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|a Cloud computing / http://id.loc.gov/authorities/subjects/sh2008004883
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b OREILLY
|a O'Reilly
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| 500 |
|
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|a Description based upon print version of record. - Choosing a data load strategy
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| 015 |
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|a GBC328018
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| 776 |
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|z 9781803233956
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| 856 |
4 |
0 |
|u https://learning.oreilly.com/library/view/~/9781803233956/?ar
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 005.7
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| 520 |
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|a This book offers a comprehensive view of Azure Synapse Data Explorer, exploring not only the core scenarios of Data Explorer but also how it integrates within Azure Synapse. From data ingestion to data visualization and advanced analytics, you'll learn to take an end-to-end approach to maximize the value of unstructured data and drive powerful insights using data science capabilities. With real-world usage scenarios, you'll discover how to identify key projects where Azure Synapse Data Explorer can help you achieve your business goals. Throughout the chapters, you'll also find out how to manage big data as part of a software as a service (SaaS) platform, as well as tune, secure, and serve data to end users. By the end of this book, you'll have mastered the big data life cycle and you'll be able to implement advanced analytical scenarios from raw telemetry and log data.
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| 520 |
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|a What you will learn Integrate Data Explorer pools with all other Azure Synapse services Create Data Explorer pools with Azure Synapse Studio and Azure Portal Ingest, analyze, and serve data to users using Azure Synapse pipelines Integrate Power BI and visualize data with Synapse Studio Configure Azure Machine Learning integration in Azure Synapse Manage cost and troubleshoot Data Explorer pools in Synapse Analytics Secure Synapse workspaces and grant access to Data Explorer pools Who this book is for If you are a data engineer, data analyst, or business analyst working with unstructured data and looking to learn how to maximize the value of such data, this book is for you. If you already have experience working with Azure Synapse and want to incorporate unstructured data into your data science project, you'll also find plenty of useful information in this book. To maximize your learning experience, familiarity with data and performing simple queries using SQL or KQL is recommended.
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| 520 |
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|a 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. Azure Synapse Data Explorer helps you collect, store, and analyze such data, and work with other analytical engines, such as Apache Spark, to develop advanced data science projects and maximize the value you extract from data.
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| 520 |
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|a Basic knowledge of Python will help you get more from the examples
|