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Data That Drives Engineering Bi And Etl For Business Transformation


Data That Drives Engineering Bi And Etl For Business Transformation
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Data That Drives Engineering Bi And Etl For Business Transformation


Data That Drives Engineering Bi And Etl For Business Transformation
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Author : Dhaval Patolia
language : en
Publisher: Xoffencer International Book Publication House
Release Date : 2025-05-23

Data That Drives Engineering Bi And Etl For Business Transformation written by Dhaval Patolia and has been published by Xoffencer International Book Publication House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-23 with Computers categories.


Business Intelligence (BI) and Extract, Transform, and Load (ETL) procedures are becoming more important to organisations in today's data- driven economy. These processes are used to drive strategic decision-making and obtain a competitive edge. Within the context of facilitating business transformation, this chapter offers an examination of the crucial role that developing effective BI and ETL frameworks plays. Business intelligence systems are able to transform raw data into actionable insights that can be used to improve operational efficiency, customer engagement, and innovation. This is accomplished via the systematic collection, processing, and analysis of massive amounts of heterogeneous data and information. An emphasis is placed in the research on the architectural design of ETL pipelines that are scalable, adaptable, and real-time. These pipelines should guarantee that data is of high quality, consistent, and timely. It analyses contemporary data engineering approaches such as API integration, Change Data Capture (CDC), and stream processing, all of which make it possible to consume and convert data from a variety of sources in a seamless manner. In addition to this, the study emphasises the use of sophisticated analytics and visualisation technologies that provide stakeholders at all levels of the organisation additional leverage. This chapter explains, through the use of case studies and best practices, how well-engineered business intelligence (BI) and enterprise transaction flow (ETL) systems not only increase the accuracy of reporting and forecasting, but also allow proactive business plans, agile reactions to changes in the market, and continuous development. The results highlight how important it is to achieve alignment between data engineering and business objectives, governance regulations, and new technologies like as machine learning and cloud computing. The purpose of this work is to provide a thorough guide for data engineers, business analysts, and decision-makers who are interested in maximising the potential of their data assets in order to achieve real business change.



Optimizing Data Pipelines With Azure Advanced Etl And Analytics Solutions For Modern Enterprises


Optimizing Data Pipelines With Azure Advanced Etl And Analytics Solutions For Modern Enterprises
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Author : Dinesh Nayak Banoth  Afroz Shaik  Prof. Sandeep Kumar
language : en
Publisher: DeepMisti Publication
Release Date : 2025-01-01

Optimizing Data Pipelines With Azure Advanced Etl And Analytics Solutions For Modern Enterprises written by Dinesh Nayak Banoth  Afroz Shaik  Prof. Sandeep Kumar and has been published by DeepMisti Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-01 with Computers categories.


In today’s fast-paced digital landscape, data has become one of the most valuable assets for organizations striving to gain a competitive edge. However, managing, processing, and extracting actionable insights from vast volumes of data has become increasingly complex. Traditional methods are no longer sufficient to handle the demands of modern enterprise systems, which require high-performance, scalable, and reliable data solutions. This book, Optimizing Data Pipelines with Azure: Advanced ETL and Analytics Solutions for Modern Enterprises, explores the intricacies of designing and optimizing data pipelines using Microsoft Azure’s powerful cloud ecosystem. Azure has emerged as a leader in providing scalable, flexible, and secure cloud solutions that help businesses streamline their data processing workflows, enhance analytics capabilities, and make data-driven decisions at scale. This book is designed to serve both as a comprehensive guide and a practical reference for professionals looking to leverage Azure’s advanced data engineering tools and technologies. Whether you are a data engineer, architect, or business intelligence professional, you will find practical insights and detailed instructions on how to implement end-to-end data pipelines on Azure. Throughout this book, we delve into key concepts such as Extract, Transform, Load (ETL) processes, data integration, real-time analytics, and the optimization of data workflows using Azure Synapse Analytics, Azure Data Factory, Azure Databricks, and other leading Azure services. We will walk you through how to design flexible, reliable, and highly performant data pipelines tailored to the specific needs of modern enterprises. By the end of this book, you will have a clear understanding of how to efficiently manage large-scale data flows, optimize ETL processes, and implement robust analytics solutions on Azure to unlock valuable insights. Whether you're tackling data ingestion, processing, storage, or analytics, this book will equip you with the tools and strategies to succeed in the ever-evolving world of data engineering and analytics. I hope this book inspires and empowers you to transform how your organization handles its data and drives future success through advanced data pipeline optimization techniques. — Author



Data Engineering And Business Intelligence For Scalable Solutions


Data Engineering And Business Intelligence For Scalable Solutions
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Author : RAVI KIRAN PAGIDI PROF.(DR.) VISHWADEEPAK SINGH BAGHELA
language : en
Publisher: DeepMisti Publication
Release Date : 2024-12-22

Data Engineering And Business Intelligence For Scalable Solutions written by RAVI KIRAN PAGIDI PROF.(DR.) VISHWADEEPAK SINGH BAGHELA and has been published by DeepMisti Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-22 with Computers categories.


In the dynamic realm of data engineering and business intelligence, scalability is no longer a luxury but a necessity for organizations aiming to thrive in today’s data-driven world. This book, Data Engineering and Business Intelligence for Scalable Systems, is crafted to address the challenges and opportunities involved in designing, implementing, and managing scalable solutions that transform raw data into actionable insights. Our mission is to provide a comprehensive resource that bridges the gap between foundational principles and cutting-edge strategies, equipping readers with the knowledge to excel in this fast-evolving field. This book delves deeply into the methodologies, tools, and frameworks that underpin successful data engineering and business intelligence practices for scalable systems. From conceptualizing robust data pipelines to leveraging advanced analytics for decision-making, the content spans a wide range of topics tailored to meet the needs of students, data engineers, BI professionals, and organizational leaders. Through a balanced approach, we integrate theory with practical applications, offering readers actionable insights to tackle real-world challenges in data scalability and intelligence. The chapters are meticulously structured to provide both depth and breadth, covering topics such as data architecture design, ETL processes, cloud-based data warehousing, and real-time analytics. Furthermore, we explore the integration of machine learning into BI systems, the use of automation in data workflows, and the role of predictive modeling in crafting forward-looking business strategies. Special emphasis is placed on scalability, ensuring that the solutions discussed are adaptable to growing data volumes and evolving enterprise demands. We hope this book serves as a trusted guide for those aspiring to master the art and science of data engineering and business intelligence for scalable systems. May it inspire innovation, foster growth, and empower readers to design systems that stand at the forefront of technological and business advancements. Thank you for joining us on this transformative journey. Authors



Security Engineering For Embedded And Cyber Physical Systems


Security Engineering For Embedded And Cyber Physical Systems
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Author : Saad Motahhir
language : en
Publisher: CRC Press
Release Date : 2022-08-31

Security Engineering For Embedded And Cyber Physical Systems written by Saad Motahhir and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-31 with Computers categories.


Digital transformation, also known as Industry 4.0, Smart Industry, and Smart Manufacturing, is at the top of leaders’ agendas. Such a transformation stimulates innovation in new products and services, the digital transformation of processes, and the creation of new business models and ecosystems. In the world of manufacturing, Industry 4.0 is based on various technological advances, among which we can mainly cite CPS (cyber-physical systems), IoT (Internet of Things), and IoS (internet of services). While engaging, this fourth wave also brings significant challenges for manufacturers. Business operations and the supply chain are becoming more vulnerable to cyber threats. Security Engineering for Embedded and Cyber-Physical Systems is an invaluable resource to discover cybersecurity and privacy techniques for embedded and cyber-physical systems. This book presents the latest studies and research results on all aspects of security engineering for embedded and cyber-physical systems. It also provides a premier interdisciplinary reference for researchers, practitioners, and educators to discover the most recent innovations, trends, concerns, and practical challenges encountered and solutions adopted in security engineering for embedded and cyber-physical systems. The book offers comprehensive coverage of the essential topics, including the following: Embedded and cyber-physical systems threats and vulnerabilities Security engineering techniques for embedded and cyber-physical systems Security engineering for embedded and cyber-physical systems and potential future-use cases Artificial intelligence techniques for cybersecurity and privacy Security engineering for Internet of Things Blockchain for cybersecurity in embedded and cyber-physical systems This book comprises a number of state-of-the-art contributions from both scientists and practitioners working in security engineering for embedded and cyber-physical systems. It aspires to provide a relevant reference for students, researchers, engineers, and professionals working in this area or those interested in grasping its diverse facets and exploring the latest advances and future trends related to security engineering for embedded and cyber-physical systems.



Advances In Enterprise Engineering Xvii


Advances In Enterprise Engineering Xvii
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Author : Monika Malinova Mandelburger
language : en
Publisher: Springer Nature
Release Date : 2024-05-02

Advances In Enterprise Engineering Xvii written by Monika Malinova Mandelburger and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-02 with Computers categories.


This book constitutes the refereed proceedings of the 13th Enterprise Design and Engineering Working Conference on Advances in Enterprise Engineering XVII, EDEWC 2023, held in Vienna, Austria, during November 27–28, 2023. Enterprise design and engineering aims to take an integrative and engineering-oriented perspective to enterprise development management. As such, it considers enterprises as purposefully designed systems where all relevant aspects should be designed in coherence. The new scope of EDEWC reflects the rapid increase in digitization of enterprises in the last decade. This has resulted in a substantial change in the nature and structure of enterprises, which was the main focus of EDEWC 2023. The 5 full papers and 2 short papers included in this book were carefully reviewed and selected from 15 submissions.



Data Analytics And Digital Transformation


Data Analytics And Digital Transformation
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Author : Erik Beulen
language : en
Publisher: Taylor & Francis
Release Date : 2023-12-01

Data Analytics And Digital Transformation written by Erik Beulen and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-01 with Business & Economics categories.


Understanding the significance of data analytics is paramount for digital transformation but in many organizations they are separate units without fully aligned goals. As organizations are applying digital transformations to be adaptive and agile in a competitive environment, data analytics can play a critical role in their success. This book explores the crossroads between them and how to leverage their connection for improved business outcomes. The need to collaborate and share data is becoming an integral part of digital transformation. This not only creates new opportunities but also requires well-considered and continuously assessed decision-making as competitiveness is at stake. This book details approaches, concepts, and frameworks, as well as actionable insights and good practices, including combined data management and agile concepts. Critical issues are discussed such as data quality and data governance, as well as compliance, privacy, and ethics. It also offers insights into how both private and public organizations can innovate and keep up with growing data volumes and increasing technological developments in the short, mid, and long term. This book will be of direct appeal to global researchers and students across a range of business disciplines, including technology and innovation management, organizational studies, and strategic management. It is also relevant for policy makers, regulators, and executives of private and public organizations looking to implement successful transformation policies.



Simplifying Data Engineering And Analytics With Delta


Simplifying Data Engineering And Analytics With Delta
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Author : Anindita Mahapatra
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-07-29

Simplifying Data Engineering And Analytics With Delta written by Anindita Mahapatra 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 2022-07-29 with Computers categories.


Explore how Delta brings reliability, performance, and governance to your data lake and all the AI and BI use cases built on top of it Key Features • Learn Delta’s core concepts and features as well as what makes it a perfect match for data engineering and analysis • Solve business challenges of different industry verticals using a scenario-based approach • Make optimal choices by understanding the various tradeoffs provided by Delta Book Description Delta helps you generate reliable insights at scale and simplifies architecture around data pipelines, allowing you to focus primarily on refining the use cases being worked on. This is especially important when you consider that existing architecture is frequently reused for new use cases. In this book, you'll learn about the principles of distributed computing, data modeling techniques, and big data design patterns and templates that help solve end-to-end data flow problems for common scenarios and are reusable across use cases and industry verticals. You'll also learn how to recover from errors and the best practices around handling structured, semi-structured, and unstructured data using Delta. After that, you'll get to grips with features such as ACID transactions on big data, disciplined schema evolution, time travel to help rewind a dataset to a different time or version, and unified batch and streaming capabilities that will help you build agile and robust data products. By the end of this Delta book, you'll be able to use Delta as the foundational block for creating analytics-ready data that fuels all AI/BI use cases. What you will learn • Explore the key challenges of traditional data lakes • Appreciate the unique features of Delta that come out of the box • Address reliability, performance, and governance concerns using Delta • Analyze the open data format for an extensible and pluggable architecture • Handle multiple use cases to support BI, AI, streaming, and data discovery • Discover how common data and machine learning design patterns are executed on Delta • Build and deploy data and machine learning pipelines at scale using Delta Who this book is for Data engineers, data scientists, ML practitioners, BI analysts, or anyone in the data domain working with big data will be able to put their knowledge to work with this practical guide to executing pipelines and supporting diverse use cases using the Delta protocol. Basic knowledge of SQL, Python programming, and Spark is required to get the most out of this book.



Software Engineering Methods In Intelligent Algorithms


Software Engineering Methods In Intelligent Algorithms
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Author : Radek Silhavy
language : en
Publisher: Springer
Release Date : 2019-05-07

Software Engineering Methods In Intelligent Algorithms written by Radek Silhavy and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-07 with Computers categories.


This book presents software engineering methods in the context of the intelligent systems. It discusses real-world problems and exploratory research describing novel approaches and applications of software engineering, software design and algorithms. The book constitutes the refereed proceedings of the Software Engineering Methods in Intelligent Algorithms Section of the 8th Computer Science On-line Conference 2019 (CSOC 2019), held on-line in April 2019.



Ultimate Apache Superset For Data Visualization And Analytics


Ultimate Apache Superset For Data Visualization And Analytics
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Author : Bragadeesh Sundararajan
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2025-04-07

Ultimate Apache Superset For Data Visualization And Analytics written by Bragadeesh Sundararajan 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 2025-04-07 with Computers categories.


TAGLINE Apache Superset to Master Data Visualization and Build High-Impact BI Solutions KEY FEATURES ● Learn to install, configure, and use Superset to create visualizations and build interactive dashboards. ● Apply your learning to real-world data scenarios and business use cases, ensuring you can immediately apply these skills in your role. ● Customize Superset with custom visualizations, integrate it with modern data pipelines, and learn how to deploy it in production environments. DESCRIPTION Apache Superset is a powerful open-source data visualization and business intelligence platform that enables professionals to create interactive dashboards effortlessly. With its user-friendly interface and broad compatibility with various data sources, Superset helps users uncover insights and make informed, data-driven decisions in real time. Ultimate Apache Superset for Data Visualization and Analytics offers a structured, hands-on approach to mastering Apache Superset. It begins with installation and configuration, guiding you through building your first visualization and dashboard. As you progress, you’ll explore advanced features such as SQL Lab, custom visualizations, and security management. The book also covers optimizing dashboards, integrating Superset with data pipelines, and deploying it in production environments. Each chapter includes practical examples, best practices, and real-world use cases to reinforce learning. By the end, you’ll have the expertise to build high-impact, interactive dashboards and confidently deploy Apache Superset in production. Whether you're a data analyst, engineer, or business professional, this book equips you with the skills to scale and customize Superset for your organization’s needs. Don't get left behind—unlock the full potential of Apache Superset and take your data visualization to the next level! WHAT WILL YOU LEARN ● Set up and configure Apache Superset for data visualization and BI. ● Design interactive dashboards and compelling data visualizations effortlessly. ● Use SQL Lab to query and explore datasets with precision. ● Develop custom visualizations and extend Superset with plugins. ● Implement role-based access control (RBAC) for secure data governance. ● Deploy, scale, and optimize Superset for enterprise-ready BI solutions. WHO IS THIS BOOK FOR? This book is tailored for Data Analysts, Data Engineers, Business Intelligence Specialists, Data Scientists, IT Professionals, and Business Managers looking to harness Apache Superset for data visualization and BI. A basic understanding of SQL and data analytics will help readers get the most out of this guide. TABLE OF CONTENTS 1. Introduction to Apache Superset 2. Installing and Configuring Apache Superset 3. Getting Started with Data Visualization 4. Data Exploration and SQL Lab 5. Custom Visualizations and Plugins 6. Security and Access Control 7. Building and Optimizing Dashboards 8. Integrating Superset into Data Pipelines 9. Exploratory Data Analysis and Hypothesis Testing 10. Scaling and Deploying Superset in Production 11. Superset for Business Reporting 12. Self-Service BI with Superset 13. Emerging Trends and Innovations in Data Visualization Index



Data Engineering On The Cloud A Practical Guide 2025


Data Engineering On The Cloud A Practical Guide 2025
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Author : Raghu Gopa, Dr. Arpita Roy
language : en
Publisher: YASHITA PRAKASHAN PRIVATE LIMITED
Release Date :

Data Engineering On The Cloud A Practical Guide 2025 written by Raghu Gopa, Dr. Arpita Roy and has been published by YASHITA PRAKASHAN PRIVATE LIMITED this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.


PREFACE The digital transformation of businesses and the exponential growth of data have created a fundamental shift in how organizations approach data management, analytics, and decision-making. As cloud technologies continue to evolve, cloud-based data engineering has become central to the success of modern data-driven enterprises. “Data Engineering on the Cloud: A Practical Guide” aims to equip data professionals, engineers, and organizations with the knowledge and practical tools needed to build and manage scalable, secure, and efficient data engineering pipelines in cloud environments. This book is designed to bridge the gap between the theoretical foundations of data engineering and the practical realities of working with cloud-based data platforms. Cloud computing has revolutionized data storage, processing, and analytics by offering unparalleled scalability, flexibility, and cost efficiency. However, with these opportunities come new challenges, including selecting the right tools, architectures, and strategies to ensure seamless data integration, transformation, and delivery. As businesses increasingly migrate their data to the cloud, it is essential for data engineers to understand how to leverage the capabilities of the cloud to build robust data pipelines that can handle large, complex datasets in real-time. Throughout this guide, we will explore the various facets of cloud-based data engineering, from understanding cloud storage and computing services to implementing data integration techniques, managing data quality, and optimizing performance. Whether you are building data pipelines from scratch, migrating on-premises systems to the cloud, or enhancing existing data workflows, this book will provide actionable insights and step-by-step guidance on best practices, tools, and frameworks commonly used in cloud data engineering. Key topics covered in this book include: · The fundamentals of cloud architecture and the role of cloud providers (such as AWS, Google Cloud, and Microsoft Azure) in data engineering workflows. · Designing scalable and efficient data pipelines using cloud-based tools and services. · Integrating diverse data sources, including structured, semi-structured, and unstructured data, for seamless processing and analysis. · Data transformation techniques, including ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform), in cloud environments. · Ensuring data quality, governance, and security when working with cloud data platforms. · Optimizing performance for data storage, processing, and analytics to handle growing data volumes and complexity. This book is aimed at professionals who are already familiar with data engineering concepts and are looking to apply those concepts within cloud environments. It is also suitable for organizations that are in the process of migrating to cloud-based data platforms and wish to understand the nuances and best practices for cloud data engineering. In addition to theoretical knowledge, this guide emphasizes hands-on approaches, providing practical examples, code snippets, and real-world case studies to demonstrate the effective implementation of cloud-based data engineering solutions. We will explore how to utilize cloud-native services to streamline workflows, improve automation, and reduce manual interventions in data pipelines. Throughout the book, you will gain insights into the evolving tools and technologies that make data engineering more agile, reliable, and efficient. The role of data engineering is growing ever more important in enabling businesses to unlock the value of their data. By the end of this book, you will have a comprehensive understanding of how to leverage cloud technologies to build high-performance, scalable data engineering solutions that are aligned with the needs of modern data-driven organizations. We hope this guide helps you to navigate the complexities of cloud data engineering and helps you unlock new possibilities for your data initiatives. Welcome to “Data Engineering on the Cloud: A Practical Guide.” Let’s embark on this journey to harness the full potential of cloud technologies in the world of data engineering. Authors