Robust Data Engineering Key Techniques For Planning And Building Scalable And Reliable Data Systems

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Robust Data Engineering Key Techniques For Planning And Building Scalable And Reliable Data Systems
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Author : Deena Conway
language : en
Publisher: Raghava Appikatla
Release Date :
Robust Data Engineering Key Techniques For Planning And Building Scalable And Reliable Data Systems written by Deena Conway and has been published by Raghava Appikatla this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
In today's data-driven world, businesses and organizations rely heavily on robust data systems to gain insights, make informed decisions, and drive innovation. This book serves as a comprehensive guide to understanding the core principles, best practices, and advanced techniques for planning and building scalable and reliable data systems. From understanding fundamental data modeling concepts to exploring distributed systems and cloud-based architectures, this book covers a wide range of topics essential for data engineers of all levels. Learn to design efficient data pipelines, implement robust data quality checks, and ensure data security and governance. Explore real-world case studies and practical examples that demonstrate how to overcome common data engineering challenges. This book is an invaluable resource for aspiring and experienced data engineers, software developers, data analysts, and anyone involved in building and maintaining data-intensive applications. Whether you're just starting your data engineering journey or looking to expand your knowledge and skills, this book provides the foundational knowledge and practical guidance needed to excel in this rapidly evolving field. Equip yourself with the tools and techniques to design, build, and maintain data systems that can handle the ever-growing volumes of data and unlock the true potential of data-driven insights.
Data Engineering With Google Cloud Platform
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Author : Adi Wijaya
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-03-31
Data Engineering With Google Cloud Platform written by Adi Wijaya and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-31 with Computers categories.
Build and deploy your own data pipelines on GCP, make key architectural decisions, and gain the confidence to boost your career as a data engineer Key Features Understand data engineering concepts, the role of a data engineer, and the benefits of using GCP for building your solution Learn how to use the various GCP products to ingest, consume, and transform data and orchestrate pipelines Discover tips to prepare for and pass the Professional Data Engineer exam Book DescriptionWith this book, you'll understand how the highly scalable Google Cloud Platform (GCP) enables data engineers to create end-to-end data pipelines right from storing and processing data and workflow orchestration to presenting data through visualization dashboards. Starting with a quick overview of the fundamental concepts of data engineering, you'll learn the various responsibilities of a data engineer and how GCP plays a vital role in fulfilling those responsibilities. As you progress through the chapters, you'll be able to leverage GCP products to build a sample data warehouse using Cloud Storage and BigQuery and a data lake using Dataproc. The book gradually takes you through operations such as data ingestion, data cleansing, transformation, and integrating data with other sources. You'll learn how to design IAM for data governance, deploy ML pipelines with the Vertex AI, leverage pre-built GCP models as a service, and visualize data with Google Data Studio to build compelling reports. Finally, you'll find tips on how to boost your career as a data engineer, take the Professional Data Engineer certification exam, and get ready to become an expert in data engineering with GCP. By the end of this data engineering book, you'll have developed the skills to perform core data engineering tasks and build efficient ETL data pipelines with GCP.What you will learn Load data into BigQuery and materialize its output for downstream consumption Build data pipeline orchestration using Cloud Composer Develop Airflow jobs to orchestrate and automate a data warehouse Build a Hadoop data lake, create ephemeral clusters, and run jobs on the Dataproc cluster Leverage Pub/Sub for messaging and ingestion for event-driven systems Use Dataflow to perform ETL on streaming data Unlock the power of your data with Data Studio Calculate the GCP cost estimation for your end-to-end data solutions Who this book is for This book is for data engineers, data analysts, and anyone looking to design and manage data processing pipelines using GCP. You'll find this book useful if you are preparing to take Google's Professional Data Engineer exam. Beginner-level understanding of data science, the Python programming language, and Linux commands is necessary. A basic understanding of data processing and cloud computing, in general, will help you make the most out of this book.
Fundamentals Of Data Engineering
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Author : Joe Reis
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-06-22
Fundamentals Of Data Engineering written by Joe Reis and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-22 with Computers categories.
Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle. Authors Joe Reis and Matt Housley walk you through the data engineering lifecycle and show you how to stitch together a variety of cloud technologies to serve the needs of downstream data consumers. You'll understand how to apply the concepts of data generation, ingestion, orchestration, transformation, storage, and governance that are critical in any data environment regardless of the underlying technology. This book will help you: Get a concise overview of the entire data engineering landscape Assess data engineering problems using an end-to-end framework of best practices Cut through marketing hype when choosing data technologies, architecture, and processes Use the data engineering lifecycle to design and build a robust architecture Incorporate data governance and security across the data engineering lifecycle
Business Intelligence Career Master Plan
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Author : Eduardo Chavez
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-08-31
Business Intelligence Career Master Plan written by Eduardo Chavez and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-31 with Computers categories.
Learn the foundations of business intelligence, sector trade-offs, organizational structures, and technology stacks while mastering coursework, certifications, and interview success strategies Purchase of the print or Kindle book includes a free PDF eBook Key Features Identify promising job opportunities and ideal entry point into BI Build, design, implement, and maintain BI systems successfully Ace your BI interview with author's expert guidance on certifications, trainings, and courses Book DescriptionNavigating the challenging path of a business intelligence career requires you to consider your expertise, interests, and skills. Business Intelligence Career Master Plan explores key skills like stacks, coursework, certifications, and interview advice, enabling you to make informed decisions about your BI journey. You’ll start by assessing the different roles in BI and matching your skills and career with the tech stack. You’ll then learn to build taxonomy and a data story using visualization types. Additionally, you’ll explore the fundamentals of programming, frontend development, backend development, software development lifecycle, and project management, giving you a broad view of the end-to-end BI process. With the help of the author’s expert advice, you’ll be able to identify what subjects and areas of study are crucial and would add significant value to your skill set. By the end of this book, you’ll be well-equipped to make an informed decision on which of the myriad paths to choose in your business intelligence journey based on your skill set and interests.What you will learn Understand BI roles, roadmap, and technology stack Accelerate your career and land your first job in the BI industry Build the taxonomy of various data sources for your organization Use the AdventureWorks database and PowerBI to build a robust data model Create compelling data stories using data visualization Automate, templatize, standardize, and monitor systems for productivity Who this book is for This book is for BI developers and business analysts who are passionate about data and are looking to advance their proficiency and career in business intelligence. While foundational knowledge of tools like Microsoft Excel is required, having a working knowledge of SQL, Python, Tableau, and major cloud providers such as AWS or GCP will be beneficial.
Designing Data Intensive Applications
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Author : Martin Kleppmann
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-03-16
Designing Data Intensive Applications written by Martin Kleppmann and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-16 with Computers categories.
Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures
Data Engineering With Apache Spark Delta Lake And Lakehouse
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Author : Manoj Kukreja
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-10-22
Data Engineering With Apache Spark Delta Lake And Lakehouse written by Manoj Kukreja and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-22 with Computers categories.
Understand the complexities of modern-day data engineering platforms and explore strategies to deal with them with the help of use case scenarios led by an industry expert in big data Key FeaturesBecome well-versed with the core concepts of Apache Spark and Delta Lake for building data platformsLearn how to ingest, process, and analyze data that can be later used for training machine learning modelsUnderstand how to operationalize data models in production using curated dataBook Description In the world of ever-changing data and schemas, it is important to build data pipelines that can auto-adjust to changes. This book will help you build scalable data platforms that managers, data scientists, and data analysts can rely on. Starting with an introduction to data engineering, along with its key concepts and architectures, this book will show you how to use Microsoft Azure Cloud services effectively for data engineering. You'll cover data lake design patterns and the different stages through which the data needs to flow in a typical data lake. Once you've explored the main features of Delta Lake to build data lakes with fast performance and governance in mind, you'll advance to implementing the lambda architecture using Delta Lake. Packed with practical examples and code snippets, this book takes you through real-world examples based on production scenarios faced by the author in his 10 years of experience working with big data. Finally, you'll cover data lake deployment strategies that play an important role in provisioning the cloud resources and deploying the data pipelines in a repeatable and continuous way. By the end of this data engineering book, you'll know how to effectively deal with ever-changing data and create scalable data pipelines to streamline data science, ML, and artificial intelligence (AI) tasks. What you will learnDiscover the challenges you may face in the data engineering worldAdd ACID transactions to Apache Spark using Delta LakeUnderstand effective design strategies to build enterprise-grade data lakesExplore architectural and design patterns for building efficient data ingestion pipelinesOrchestrate a data pipeline for preprocessing data using Apache Spark and Delta Lake APIsAutomate deployment and monitoring of data pipelines in productionGet to grips with securing, monitoring, and managing data pipelines models efficientlyWho this book is for This book is for aspiring data engineers and data analysts who are new to the world of data engineering and are looking for a practical guide to building scalable data platforms. If you already work with PySpark and want to use Delta Lake for data engineering, you'll find this book useful. Basic knowledge of Python, Spark, and SQL is expected.
Mysql High Availability
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Author : Charles Bell
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2014-04-10
Mysql High Availability written by Charles Bell and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-10 with Computers categories.
Server bottlenecks and failures are a fact of life in any database deployment, but they don’t have to bring everything to a halt. This practical book explains replication, cluster, and monitoring features that can help protect your MySQL system from outages, whether it’s running on hardware, virtual machines, or in the cloud. Written by engineers who designed many of the tools covered, this book reveals undocumented or hard-to-find aspects of MySQL reliability and high availability—knowledge that’s essential for any organization using this database system. This second edition describes extensive changes to MySQL tools. Versions up to 5.5 are covered, along with several 5.6 features. Learn replication fundamentals, including use of the binary log and MySQL Replicant Library Handle failing components through redundancy Scale out to manage read-load increases, and use data sharding to handle large databases and write-load increases Store and replicate data on individual nodes with MySQL Cluster Monitor database activity and performance, and major operating system parameters Keep track of masters and slaves, and deal with failures and restarts, corruption, and other incidents Examine tools including MySQL Enterprise Monitor, MySQL Utilities, and GTIDs
97 Things Every Data Engineer Should Know
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Author : Tobias Macey
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-06-11
97 Things Every Data Engineer Should Know written by Tobias Macey and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-11 with Computers categories.
Take advantage of the sky-high demand for data engineers today. With this in-depth book, current and aspiring engineers will learn powerful, real-world best practices for managing data big and small. Contributors from Google, Microsoft, IBM, Facebook, Databricks, and GitHub share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges. Edited by Tobias Macey from MIT Open Learning, this book presents 97 concise and useful tips for cleaning, prepping, wrangling, storing, processing, and ingesting data. Data engineers, data architects, data team managers, data scientists, machine learning engineers, and software engineers will greatly benefit from the wisdom and experience of their peers. Projects include: Building pipelines Stream processing Data privacy and security Data governance and lineage Data storage and architecture Ecosystem of modern tools Data team makeup and culture Career advice.
Site Reliability Engineering
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Author : Niall Richard Murphy
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-03-23
Site Reliability Engineering written by Niall Richard Murphy and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-23 with Computers categories.
The overwhelming majority of a software systemâ??s lifespan is spent in use, not in design or implementation. So, why does conventional wisdom insist that software engineers focus primarily on the design and development of large-scale computing systems? In this collection of essays and articles, key members of Googleâ??s Site Reliability Team explain how and why their commitment to the entire lifecycle has enabled the company to successfully build, deploy, monitor, and maintain some of the largest software systems in the world. Youâ??ll learn the principles and practices that enable Google engineers to make systems more scalable, reliable, and efficientâ??lessons directly applicable to your organization. This book is divided into four sections: Introductionâ??Learn what site reliability engineering is and why it differs from conventional IT industry practices Principlesâ??Examine the patterns, behaviors, and areas of concern that influence the work of a site reliability engineer (SRE) Practicesâ??Understand the theory and practice of an SREâ??s day-to-day work: building and operating large distributed computing systems Managementâ??Explore Google's best practices for training, communication, and meetings that your organization can use
Data Pipelines Pocket Reference
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Author : James Densmore
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-02-10
Data Pipelines Pocket Reference written by James Densmore and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-10 with Computers categories.
Data pipelines are the foundation for success in data analytics. Moving data from numerous diverse sources and transforming it to provide context is the difference between having data and actually gaining value from it. This pocket reference defines data pipelines and explains how they work in today's modern data stack. You'll learn common considerations and key decision points when implementing pipelines, such as batch versus streaming data ingestion and build versus buy. This book addresses the most common decisions made by data professionals and discusses foundational concepts that apply to open source frameworks, commercial products, and homegrown solutions. You'll learn: What a data pipeline is and how it works How data is moved and processed on modern data infrastructure, including cloud platforms Common tools and products used by data engineers to build pipelines How pipelines support analytics and reporting needs Considerations for pipeline maintenance, testing, and alerting