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Mastering The Modern Data Stack


Mastering The Modern Data Stack
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Mastering The Modern Data Stack


Mastering The Modern Data Stack
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Author : Nick Jewell, PhD
language : en
Publisher: TinyTechMedia LLC
Release Date : 2023-09-28

Mastering The Modern Data Stack written by Nick Jewell, PhD and has been published by TinyTechMedia LLC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-28 with Computers categories.


In the age of digital transformation, becoming overwhelmed by the sheer volume of potential data management, analytics, and AI solutions is common. Then it's all too easy to become distracted by glossy vendor marketing, and then chase the latest shiny tool, rather than focusing on building resilient, valuable platforms that will outperform the competition. This book aims to fix a glaring gap for data professionals: a comprehensive guide to the full Modern Data Stack that's rooted in real-world capabilities, not vendor hype. It is full of hard-earned advice on how to get maximum value from your investments through tangible insights, actionable strategies, and proven best practices. It comprehensively explains how the Modern Data Stack is truly utilized by today's data-driven companies. Mastering the Modern Data Stack: An Executive Guide to Unified Business Analytics is crafted for a diverse audience. It's for business and technology leaders who understand the importance and potential value of data, analytics, and AI—but don’t quite see how it all fits together in the big picture. It's for enterprise architects and technology professionals looking for a primer on the data analytics domain, including definitions of essential components and their usage patterns. It's also for individuals early in their data analytics careers who wish to have a practical and jargon-free understanding of how all the gears and pulleys move behind the scenes in a Modern Data Stack to turn data into actual business value. Whether you're starting your data journey with modest resources, or implementing digital transformation in the cloud, you'll find that this isn't just another textbook on data tools or a mere overview of outdated systems. It's a powerful guide to efficient, modern data management and analytics, with a firm focus on emerging technologies such as data science, machine learning, and AI. If you want to gain a competitive advantage in today’s fast-paced digital world, this TinyTechGuide™ is for you. Remember, it’s not the tech that’s tiny, just the book!™



Mastering The Data Paradox


Mastering The Data Paradox
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Author : Nitin Seth
language : en
Publisher: Penguin Random House India Private Limited
Release Date : 2024-03-18

Mastering The Data Paradox written by Nitin Seth and has been published by Penguin Random House India Private Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-18 with Computers categories.


There are two remarkable phenomena that are unfolding almost simultaneously. The first is the emergence of a data-first world, where data has become a central driving force, shaping industries and fueling innovation. The second is the dawn of the AI age, propelled by the advent of Generative AI, that has created the possibility to leverage the data of the world for the first time. The convergence of these two, with data as the common denominator, holds immense promise and the opportunities are boundless. This book provides us with opportunities to push our thinking, to innovate, to transform and to create a better future at all levels—individual, enterprise and the world.



The Informed Company


The Informed Company
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Author : Dave Fowler
language : en
Publisher: John Wiley & Sons
Release Date : 2021-10-22

The Informed Company written by Dave Fowler and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-22 with Business & Economics categories.


Learn how to manage a modern data stack and get the most out of data in your organization! Thanks to the emergence of new technologies and the explosion of data in recent years, we need new practices for managing and getting value out of data. In the modern, data driven competitive landscape the "best guess" approach—reading blog posts here and there and patching together data practices without any real visibility—is no longer going to hack it. The Informed Company provides definitive direction on how best to leverage the modern data stack, including cloud computing, columnar storage, cloud ETL tools, and cloud BI tools. You'll learn how to work with Agile methods and set up processes that's right for your company to use your data as a key weapon for your success . . . You'll discover best practices for every stage, from querying production databases at a small startup all the way to setting up data marts for different business lines of an enterprise. In their work at Chartio, authors Fowler and David have learned that most businesspeople are almost completely self-taught when it comes to data. If they are using resources, those resources are outdated, so they're missing out on the latest cloud technologies and advances in data analytics. This book will firm up your understanding of data and bring you into the present with knowledge around what works and what doesn't. Discover the data stack strategies that are working for today's successful small, medium, and enterprise companies Learn the different Agile stages of data organization, and the right one for your team Learn how to maintain Data Lakes and Data Warehouses for effective, accessible data storage Gain the knowledge you need to architect Data Warehouses and Data Marts Understand your business's level of data sophistication and the steps you can take to get to "level up" your data The Informed Company is the definitive data book for anyone who wants to work faster and more nimbly, armed with actionable decision-making data.



Data Engineering For Cloud Applications Leveraging Full Stack Skills For Scalable Solutions


Data Engineering For Cloud Applications Leveraging Full Stack Skills For Scalable Solutions
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Author : AKASH BALAJI MALI PROF. (DR.) SUDEEPT SINGH YADAV
language : en
Publisher: DeepMisti Publication
Release Date :

Data Engineering For Cloud Applications Leveraging Full Stack Skills For Scalable Solutions written by AKASH BALAJI MALI PROF. (DR.) SUDEEPT SINGH YADAV and has been published by DeepMisti Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.


In the rapidly evolving world of cloud computing, data engineering plays a pivotal role in building scalable, efficient, and resilient applications. As organizations move their infrastructures to the cloud, the demand for professionals who can design, manage, and optimize data pipelines has surged. "Data Engineering for Cloud Applications: Leveraging Full-Stack Skills for Scalable Solutions" aims to bridge the gap between traditional data engineering practices and the modern demands of cloud-native environments. This book is written for developers, engineers, and architects who want to harness the power of cloud platforms while leveraging their full-stack skills to create scalable, high-performance applications. The integration of cloud technologies such as AWS, Azure, and Google Cloud with data engineering practices enables organizations to manage vast amounts of data effectively, streamline their workflows, and enhance decision-making capabilities. Through practical insights, hands-on examples, and industry best practices, this book guides you through the entire data engineering lifecycle in the cloud, from ingestion to processing and storage. Emphasis is placed on optimizing data flows, reducing latency, and maintaining data integrity across distributed systems. Whether you're working with relational databases, NoSQL systems, or big data solutions, this book offers the tools and techniques necessary to build applications that scale with your business needs. Moreover, this book highlights the synergy between cloud architecture and full-stack development, demonstrating how data engineers can collaborate with front-end and back-end developers to create end-to-end solutions. By the end, you will have a deep understanding of cloud data engineering, allowing you to design robust, scalable solutions that meet the demands of modern businesses in an increasingly data-driven world. Thank you for embarking on this journey with us. Authors



Mastering Data Engineering And Analytics With Databricks


Mastering Data Engineering And Analytics With Databricks
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Author : Manoj Kumar
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2024-09-30

Mastering Data Engineering And Analytics With Databricks written by Manoj Kumar and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-30 with Computers categories.


TAGLINE Master Databricks to Transform Data into Strategic Insights for Tomorrow’s Business Challenges KEY FEATURES ● Combines theory with practical steps to master Databricks, Delta Lake, and MLflow. ● Real-world examples from FMCG and CPG sectors demonstrate Databricks in action. ● Covers real-time data processing, ML integration, and CI/CD for scalable pipelines. ● Offers proven strategies to optimize workflows and avoid common pitfalls. DESCRIPTION In today’s data-driven world, mastering data engineering is crucial for driving innovation and delivering real business impact. Databricks is one of the most powerful platforms which unifies data, analytics and AI requirements of numerous organizations worldwide. Mastering Data Engineering and Analytics with Databricks goes beyond the basics, offering a hands-on, practical approach tailored for professionals eager to excel in the evolving landscape of data engineering and analytics. This book uniquely blends foundational knowledge with advanced applications, equipping readers with the expertise to build, optimize, and scale data pipelines that meet real-world business needs. With a focus on actionable learning, it delves into complex workflows, including real-time data processing, advanced optimization with Delta Lake, and seamless ML integration with MLflow—skills critical for today’s data professionals. Drawing from real-world case studies in FMCG and CPG industries, this book not only teaches you how to implement Databricks solutions but also provides strategic insights into tackling industry-specific challenges. From setting up your environment to deploying CI/CD pipelines, you'll gain a competitive edge by mastering techniques that are directly applicable to your organization’s data strategy. By the end, you’ll not just understand Databricks—you’ll command it, positioning yourself as a leader in the data engineering space. WHAT WILL YOU LEARN ● Design and implement scalable, high-performance data pipelines using Databricks for various business use cases. ● Optimize query performance and efficiently manage cloud resources for cost-effective data processing. ● Seamlessly integrate machine learning models into your data engineering workflows for smarter automation. ● Build and deploy real-time data processing solutions for timely and actionable insights. ● Develop reliable and fault-tolerant Delta Lake architectures to support efficient data lakes at scale. WHO IS THIS BOOK FOR? This book is designed for data engineering students, aspiring data engineers, experienced data professionals, cloud data architects, data scientists and analysts looking to expand their skill sets, as well as IT managers seeking to master data engineering and analytics with Databricks. A basic understanding of data engineering concepts, familiarity with data analytics, and some experience with cloud computing or programming languages such as Python or SQL will help readers fully benefit from the book’s content. TABLE OF CONTENTS SECTION 1 1. Introducing Data Engineering with Databricks 2. Setting Up a Databricks Environment for Data Engineering 3. Working with Databricks Utilities and Clusters SECTION 2 4. Extracting and Loading Data Using Databricks 5. Transforming Data with Databricks 6. Handling Streaming Data with Databricks 7. Creating Delta Live Tables 8. Data Partitioning and Shuffling 9. Performance Tuning and Best Practices 10. Workflow Management 11. Databricks SQL Warehouse 12. Data Storage and Unity Catalog 13. Monitoring Databricks Clusters and Jobs 14. Production Deployment Strategies 15. Maintaining Data Pipelines in Production 16. Managing Data Security and Governance 17. Real-World Data Engineering Use Cases with Databricks 18. AI and ML Essentials 19. Integrating Databricks with External Tools Index



Data Engineering With Dbt


Data Engineering With Dbt
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Author : Roberto Zagni
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-06-30

Data Engineering With Dbt written by Roberto Zagni 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 2023-06-30 with Computers categories.


Use easy-to-apply patterns in SQL and Python to adopt modern analytics engineering to build agile platforms with dbt that are well-tested and simple to extend and run Purchase of the print or Kindle book includes a free PDF eBook Key Features Build a solid dbt base and learn data modeling and the modern data stack to become an analytics engineer Build automated and reliable pipelines to deploy, test, run, and monitor ELTs with dbt Cloud Guided dbt + Snowflake project to build a pattern-based architecture that delivers reliable datasets Book Descriptiondbt Cloud helps professional analytics engineers automate the application of powerful and proven patterns to transform data from ingestion to delivery, enabling real DataOps. This book begins by introducing you to dbt and its role in the data stack, along with how it uses simple SQL to build your data platform, helping you and your team work better together. You’ll find out how to leverage data modeling, data quality, master data management, and more to build a simple-to-understand and future-proof solution. As you advance, you’ll explore the modern data stack, understand how data-related careers are changing, and see how dbt enables this transition into the emerging role of an analytics engineer. The chapters help you build a sample project using the free version of dbt Cloud, Snowflake, and GitHub to create a professional DevOps setup with continuous integration, automated deployment, ELT run, scheduling, and monitoring, solving practical cases you encounter in your daily work. By the end of this dbt book, you’ll be able to build an end-to-end pragmatic data platform by ingesting data exported from your source systems, coding the needed transformations, including master data and the desired business rules, and building well-formed dimensional models or wide tables that’ll enable you to build reports with the BI tool of your choice.What you will learn Create a dbt Cloud account and understand the ELT workflow Combine Snowflake and dbt for building modern data engineering pipelines Use SQL to transform raw data into usable data, and test its accuracy Write dbt macros and use Jinja to apply software engineering principles Test data and transformations to ensure reliability and data quality Build a lightweight pragmatic data platform using proven patterns Write easy-to-maintain idempotent code using dbt materialization Who this book is for This book is for data engineers, analytics engineers, BI professionals, and data analysts who want to learn how to build simple, futureproof, and maintainable data platforms in an agile way. Project managers, data team managers, and decision makers looking to understand the importance of building a data platform and foster a culture of high-performing data teams will also find this book useful. Basic knowledge of SQL and data modeling will help you get the most out of the many layers of this book. The book also includes primers on many data-related subjects to help juniors get started.



Data Driven Decision Making For Business


Data Driven Decision Making For Business
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Author : Claus Grand Bang
language : en
Publisher: Taylor & Francis
Release Date : 2024-08-22

Data Driven Decision Making For Business written by Claus Grand Bang and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-22 with Business & Economics categories.


Research shows that companies that employ data-driven decision-making are more productive, have a higher market value, and deliver higher returns for their shareholders. In this book, the reader will discover the history, theory, and practice of data-driven decision-making, learning how organizations and individual managers alike can utilize its methods to avoid cognitive biases and improve confidence in their decisions. It argues that value does not come from data, but from acting on data. Throughout the book, the reader will examine how to convert data to value through data-driven decision-making, as well as how to create a strong foundation for such decision-making within organizations. Covering topics such as strategy, culture, analysis, and ethics, the text uses a collection of diverse and up-to-date case studies to convey insights which can be developed into future action. Simultaneously, the text works to bridge the gap between data specialists and businesspeople. Clear learning outcomes and chapter summaries ensure that key points are highlighted, enabling lecturers to easily align the text to their curriculums. Data-Driven Decision-Making for Business provides important reading for undergraduate and postgraduate students of business and data analytics programs, as well as wider MBA classes. Chapters can also be used on a standalone basis, turning the book into a key reference work for students graduating into practitioners. The book is supported by online resources, including PowerPoint slides for each chapter.



Ultimate Qlik Cloud Data Analytics And Data Integration


Ultimate Qlik Cloud Data Analytics And Data Integration
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Author : Orange Editorial Board
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2025-07-25

Ultimate Qlik Cloud Data Analytics And Data Integration written by Orange Editorial Board and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-25 with Computers categories.


TAGLINE Master Qlik Cloud to Integrate Data and Drive Real-Time Insights. KEY FEATURES ● End-to-End Qlik Cloud Coverage from Basics to Automation. ● Real-Time Data Integration with QCDI & CDC Techniques. ● AI-Powered Insights Using AutoML and Insight Advisor. ● Hands-On Visualizations, Scripting, and Application Design. DESCRIPTION In today’s data-driven world, organizations need smarter tools to turn raw data into actionable insights—Qlik Cloud is one of the most powerful platforms to do just that. It enables users to unify data, visualize trends, and make faster, informed decisions. Ultimate Qlik Cloud Data Analytics and Data Integration is your comprehensive guide to mastering the full Qlik Cloud ecosystem. The journey begins with a walkthrough of the platform's foundational features, including its intuitive interface, scalable architecture, and cloud-native capabilities. You’ll learn how to build your first application using Data Manager, seamlessly connecting and loading data from a variety of sources. As your skills grow, the book delves into data scripting, modeling, and set analysis—giving you the tools to shape your data and create meaningful relationships. Visualizations come next, where you’ll design compelling, interactive dashboards that uncover hidden patterns and drive user engagement. Beyond visualization, the book explores Qlik Cloud’s advanced analytics offerings, including Insight Advisor, AutoML, and AI-assisted recommendations that accelerate decision-making. You'll also master the backend power of the platform, diving deep into real-time data integration, Change Data Capture (CDC), Application Automation, and data lineage tracking—all crucial for building enterprise-ready solutions. With a focus on real-world implementation, governance, and performance, this book prepares analysts, developers, and business users alike to unlock the full potential of Qlik Cloud—from data ingestion to decision-making. Dive in and become a Qlik Cloud expert to integrate smarter, analyze deeper, and lead with data. WHAT WILL YOU LEARN ● Build apps using Qlik Cloud Data Manager and scripting. ● Create advanced visualizations and master set analysis logic. ● Integrate real-time data streams using QCDI and CDC. ● Automate workflows with Application Automation and Insight Advisor. ● Leverage AutoML for predictive analytics and business insights. ● Manage data lineage, governance, and glossary for compliance. WHO IS THIS BOOK FOR? This book is ideal for data analysts, BI developers, and business users looking to build or enhance their data visualization and integration skills using Qlik Cloud. Whether you're new to Qlik or transitioning from other tools, no prior experience with Qlik Sense is required, just a basic understanding of data concepts. TABLE OF CONTENTS 1. Getting Started With Qlik Cloud 2. Building Your First Application 3. Using Scripts 4. Set Analysis 5. Embedding and Extending 6. Navigating The Data Landscape 7. Advanced Analytics - AutoML 8. Application Automation 9. Insight Advisor 10. Reporting Service 11. Direct Access Gateway 12. Getting to Know Qlik Talend Data Integration 13. CDC and Landing Data in Real Time 14. Transforming Data 15. Data Marts Index



The Definitive Guide To Data Integration


The Definitive Guide To Data Integration
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Author : Pierre-Yves BONNEFOY
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-03-29

The Definitive Guide To Data Integration written by Pierre-Yves BONNEFOY 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 2024-03-29 with Computers categories.


Learn the essentials of data integration with this comprehensive guide, covering everything from sources to solutions, and discover the key to making the most of your data stack Key Features Learn how to leverage modern data stack tools and technologies for effective data integration Design and implement data integration solutions with practical advice and best practices Focus on modern technologies such as cloud-based architectures, real-time data processing, and open-source tools and technologies Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe Definitive Guide to Data Integration is an indispensable resource for navigating the complexities of modern data integration. Focusing on the latest tools, techniques, and best practices, this guide helps you master data integration and unleash the full potential of your data. This comprehensive guide begins by examining the challenges and key concepts of data integration, such as managing huge volumes of data and dealing with the different data types. You’ll gain a deep understanding of the modern data stack and its architecture, as well as the pivotal role of open-source technologies in shaping the data landscape. Delving into the layers of the modern data stack, you’ll cover data sources, types, storage, integration techniques, transformation, and processing. The book also offers insights into data exposition and APIs, ingestion and storage strategies, data preparation and analysis, workflow management, monitoring, data quality, and governance. Packed with practical use cases, real-world examples, and a glimpse into the future of data integration, The Definitive Guide to Data Integration is an essential resource for data eclectics. By the end of this book, you’ll have the gained the knowledge and skills needed to optimize your data usage and excel in the ever-evolving world of data.What you will learn Discover the evolving architecture and technologies shaping data integration Process large data volumes efficiently with data warehousing Tackle the complexities of integrating large datasets from diverse sources Harness the power of data warehousing for efficient data storage and processing Design and optimize effective data integration solutions Explore data governance principles and compliance requirements Who this book is for This book is perfect for data engineers, data architects, data analysts, and IT professionals looking to gain a comprehensive understanding of data integration in the modern era. Whether you’re a beginner or an experienced professional enhancing your knowledge of the modern data stack, this definitive guide will help you navigate the data integration landscape.



Fundamentals Of Data Engineering


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