Dataops
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Practical Dataops
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Author : Harvinder Atwal
language : en
Publisher: Apress
Release Date : 2019-12-09
Practical Dataops written by Harvinder Atwal and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-09 with Computers categories.
Gain a practical introduction to DataOps, a new discipline for delivering data science at scale inspired by practices at companies such as Facebook, Uber, LinkedIn, Twitter, and eBay. Organizations need more than the latest AI algorithms, hottest tools, and best people to turn data into insight-driven action and useful analytical data products. Processes and thinking employed to manage and use data in the 20th century are a bottleneck for working effectively with the variety of data and advanced analytical use cases that organizations have today. This book provides the approach and methods to ensure continuous rapid use of data to create analytical data products and steer decision making. Practical DataOps shows you how to optimize the data supply chain from diverse raw data sources to the final data product, whether the goal is a machine learning model or other data-orientated output. The book provides an approach to eliminate wasted effort and improve collaboration between data producers, data consumers, and the rest of the organization through the adoption of lean thinking and agile software development principles. This book helps you to improve the speed and accuracy of analytical application development through data management and DevOps practices that securely expand data access, and rapidly increase the number of reproducible data products through automation, testing, and integration. The book also shows how to collect feedback and monitor performance to manage and continuously improve your processes and output. What You Will Learn Develop a data strategy for your organization to help it reach its long-term goals Recognize and eliminate barriers to delivering data to users at scale Work on the right things for the right stakeholders through agile collaboration Create trust in data via rigorous testing and effective data management Build a culture of learning and continuous improvement through monitoring deployments and measuring outcomes Create cross-functional self-organizing teams focused on goals not reporting lines Build robust, trustworthy, data pipelines in support of AI, machine learning, and other analytical data products Who This Book Is For Data science and advanced analytics experts, CIOs, CDOs (chief data officers), chief analytics officers, business analysts, business team leaders, and IT professionals (data engineers, developers, architects, and DBAs) supporting data teams who want to dramatically increase the value their organization derives from data. The book is ideal for data professionals who want to overcome challenges of long delivery time, poor data quality, high maintenance costs, and scaling difficulties in getting data science output and machine learning into customer-facing production.
Dataops For Business
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Author : Diego Rodrigues
language : en
Publisher: StudioD21
Release Date : 2025-02-10
Dataops For Business written by Diego Rodrigues and has been published by StudioD21 this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-10 with Business & Economics categories.
DataOps for Business: Transform Data into Insights with Agility is an essential guide for professionals and companies looking to optimize data flows, increase operational efficiency, and drive innovation through DataOps. This book presents the key principles, tools, and strategies to effectively implement DataOps, ensuring greater automation, governance, and collaboration in data processes. Written by Diego Rodrigues, a best-selling author with over 180 titles published in six languages, this book combines theory and practice to empower you to transform the way data is collected, processed, and analyzed. Throughout the chapters, you will learn how to structure agile data pipelines, integrate DataOps with emerging technologies, implement continuous automation, and enhance data security and quality. Additionally, the book explores success stories and future trends, preparing you to apply DataOps in a strategic and scalable way. With practical examples and in-depth insights, DataOps for Business is more than just a technical manual—it is an indispensable resource for those seeking excellence in data management and utilization. Get ready to transform your approach and extract real value from data with agility and intelligence! TAGS: Python Java Linux Kali HTML ASP.NET Ada Assembly BASIC Borland Delphi C C# C++ CSS Cobol Compilers DHTML Fortran General JavaScript LISP PHP Pascal Perl Prolog RPG Ruby SQL Swift UML Elixir Haskell VBScript Visual Basic XHTML XML XSL Django Flask Ruby on Rails Angular React Vue.js Node.js Laravel Spring Hibernate .NET Core Express.js TensorFlow PyTorch Jupyter Notebook Keras Bootstrap Foundation jQuery SASS LESS Scala Groovy MATLAB R Objective-C Rust Go Kotlin TypeScript Dart SwiftUI Xamarin React Native NumPy Pandas SciPy Matplotlib Seaborn D3.js OpenCV NLTK PySpark BeautifulSoup Scikit-learn XGBoost CatBoost LightGBM FastAPI Redis RabbitMQ Kubernetes Docker Jenkins Terraform Ansible Vagrant GitHub GitLab CircleCI Regression Logistic Regression Decision Trees Random Forests AI ML K-Means Clustering Support Vector Machines Gradient Boosting Neural Networks LSTMs CNNs GANs ANDROID IOS MACOS WINDOWS Nmap Metasploit Framework Wireshark Aircrack-ng John the Ripper Burp Suite SQLmap Maltego Autopsy Volatility IDA Pro OllyDbg YARA Snort ClamAV Netcat Tcpdump Foremost Cuckoo Sandbox Fierce HTTrack Kismet Hydra Nikto OpenVAS Nessus ZAP Radare2 Binwalk GDB OWASP Amass Dnsenum Dirbuster Wpscan Responder Setoolkit Searchsploit Recon-ng BeEF AWS Google Cloud IBM Azure Databricks Nvidia Meta Power BI IoT CI/CD Hadoop Spark Dask SQLAlchemy Web Scraping MySQL Big Data Science OpenAI ChatGPT Handler RunOnUiThread() Qiskit Q# Cassandra Bigtable VIRUS MALWARE Information Pen Test Cybersecurity Linux Distributions Ethical Hacking Vulnerability Analysis System Exploration Wireless Attacks Web Application Security Malware Analysis Social Engineering Social Engineering Toolkit SET Computer Science IT Professionals Careers Expertise Library Training Operating Systems Security Testing Penetration Test Cycle Mobile Techniques Industry Global Trends Tools Framework Network Security Courses Tutorials Challenges Landscape Cloud Threats Compliance Research Technology Flutter Ionic Web Views Capacitor APIs REST GraphQL Firebase Redux Provider Bitrise Actions Material Design Cupertino Fastlane Appium Selenium Jest Visual Studio AR VR sql deepseek mysql startup digital marketing
The Dataops Revolution
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Author : Simon Trewin
language : en
Publisher: CRC Press
Release Date : 2021-08-05
The Dataops Revolution written by Simon Trewin and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-05 with Computers categories.
DataOps is a new way of delivering data and analytics that is proven to get results. It enables IT and users to collaborate in the delivery of solutions that help organisations to embrace a data-driven culture. The DataOps Revolution: Delivering the Data-Driven Enterprise is a narrative about real world issues involved in using DataOps to make data-driven decisions in modern organisations. The book is built around real delivery examples based on the author’s own experience and lays out principles and a methodology for business success using DataOps. Presenting practical design patterns and DataOps approaches, the book shows how DataOps projects are run and presents the benefits of using DataOps to implement data solutions. Best practices are introduced in this book through the telling of a story, which relates how a lead manager must find a way through complexity to turn an organisation around. This narrative vividly illustrates DataOps in action, enabling readers to incorporate best practices into everyday projects. The book tells the story of an embattled CIO who turns to a new and untested project manager charged with a wide remit to roll out DataOps techniques to an entire organisation. It illustrates a different approach to addressing the challenges in bridging the gap between IT and the business. The approach presented in this story lines up to the six IMPACT pillars of the DataOps model that Kinaesis (www.kinaesis.com) has been using through its consultants to deliver successful projects and turn around failing deliveries. The pillars help to organise thinking and structure an approach to project delivery. The pillars are broken down and translated into steps that can be applied to real-world projects that can deliver satisfaction and fulfillment to customers and project team members.
Winning With Dataops Harnessing Efficiency In The Enterprise
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Author : Prabhu Krishnaswamy
language : en
Publisher: Libertatem Media Private Limited
Release Date : 2023-08-18
Winning With Dataops Harnessing Efficiency In The Enterprise written by Prabhu Krishnaswamy and has been published by Libertatem Media Private Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-18 with Business & Economics categories.
In the fast-paced world of data-driven decision-making, DataOps has emerged as a transformative framework for organizations aiming to optimize their data ecosystems. Winning with DataOps: Harnessing Efficiency in the Enterprise is a definitive guide for senior executives, IT professionals, and data engineers striving to build agile, scalable, and secure data workflows that align with business goals. This book unpacks the core principles of DataOps, providing insights into its role in bridging the gap between legacy systems and cutting-edge technologies. From data pipeline automation and orchestration to governance and real-time security, the book offers actionable strategies for managing complex, large-scale data ecosystems. It also highlights the importance of aligning DataOps practices with organizational objectives to ensure that data-driven initiatives deliver measurable business value. Readers will explore practical methodologies for implementing robust data governance frameworks, ensuring compliance with global regulations, and leveraging tools like Apache Airflow, Kafka, and Collibra for pipeline optimization and lineage tracking. Case studies and industry examples illustrate the transformative power of DataOps in industries like healthcare, finance, and e-commerce, showcasing its potential to enhance efficiency, reliability, and innovation. Whether you ’ re integrating legacy systems with modern architectures, deploying real-time processing strategies, or navigating multi-cloud environments, Winning with DataOps equips you with the knowledge to harness the full potential of your data assets. This book is your roadmap to operational excellence and strategic advantage in the evolving digital landscape.
Information Systems For Intelligent Systems
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Author : Andres Iglesias
language : en
Publisher: Springer Nature
Release Date : 2025-05-30
Information Systems For Intelligent Systems written by Andres Iglesias and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-30 with Computers categories.
This book includes selected papers presented at World Conference on Information Systems for Business Management (ISBM 2024), held in Bangkok, Thailand, during September 12–13, 2024. It covers up-to-date cutting-edge research on data science, information systems, infrastructure and computational systems, engineering systems, business information systems, and smart secure systems.
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 will learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available in 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 will understand how to apply the concepts of data generation, ingestion, orchestration, transformation, storage, governance, and deployment that are critical in any data environment regardless of the underlying technology. This book will help you: Assess data engineering problems using an end-to-end data 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." - from Publisher.
Data Governance Devsecops And Advancements In Modern Software
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Author : Elbaghazaoui, Bahaa Eddine
language : en
Publisher: IGI Global
Release Date : 2025-04-24
Data Governance Devsecops And Advancements In Modern Software written by Elbaghazaoui, Bahaa Eddine and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-24 with Computers categories.
In today’s digital landscape, data governance, DevSecOps, and advancements in modern software development have become critical in secure and efficient technology ecosystems. As organizations rely on large amounts of data and sophisticated software systems to drive innovation and business success, the need for improved frameworks to manage, protect, and optimize this data increases. Data governance ensures data is accurate, secure, and compliant with regulations, while DevSecOps, an integrated approach to development, security, and operations, empowers teams to build, test, and utilize software with security embedded through its lifecycle. Along with the latest advancements in modern software technologies, these concepts form the foundation for building resilient, secure, and scalable applications. The intersection of these practices shapes the future of how software is developed, deployed, and governed, and further research may provide both opportunities and challenges for connection. Data Governance, DevSecOps, and Advancements in Modern Software explores the integration of key technologies and methodologies that define the modern digital landscape, with a focus on DataOps, DevSecOps, data governance, and software architecture. It provides a comprehensive guide to managing data workflows and enhancing operational efficiency while embedding security at every stage of the development lifecycle. This book covers topics such as data science, artificial intelligence, and resilient systems, and is a useful resource for data scientists, engineers, software developers, business owners, researchers, and academicians.
Principles Of Data Fabric
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Author : Sonia Mezzetta
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-04-06
Principles Of Data Fabric written by Sonia Mezzetta 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 2023-04-06 with Computers categories.
Apply Data Fabric solutions to automate Data Integration, Data Sharing, and Data Protection across disparate data sources using different data management styles. Purchase of the print or Kindle book includes a free PDF eBook Key Features Learn to design Data Fabric architecture effectively with your choice of tool Build and use a Data Fabric solution using DataOps and Data Mesh frameworks Find out how to build Data Integration, Data Governance, and Self-Service analytics architecture Book Description Data can be found everywhere, from cloud environments and relational and non-relational databases to data lakes, data warehouses, and data lakehouses. Data management practices can be standardized across the cloud, on-premises, and edge devices with Data Fabric, a powerful architecture that creates a unified view of data. This book will enable you to design a Data Fabric solution by addressing all the key aspects that need to be considered. The book begins by introducing you to Data Fabric architecture, why you need them, and how they relate to other strategic data management frameworks. You'll then quickly progress to grasping the principles of DataOps, an operational model for Data Fabric architecture. The next set of chapters will show you how to combine Data Fabric with DataOps and Data Mesh and how they work together by making the most out of it. After that, you'll discover how to design Data Integration, Data Governance, and Self-Service analytics architecture. The book ends with technical architecture to implement distributed data management and regulatory compliance, followed by industry best practices and principles. By the end of this data book, you will have a clear understanding of what Data Fabric is and what the architecture looks like, along with the level of effort that goes into designing a Data Fabric solution. What you will learn Understand the core components of Data Fabric solutions Combine Data Fabric with Data Mesh and DataOps frameworks Implement distributed data management and regulatory compliance using Data Fabric Manage and enforce Data Governance with active metadata using Data Fabric Explore industry best practices for effectively implementing a Data Fabric solution Who this book is for If you are a data engineer, data architect, or business analyst who wants to learn all about implementing Data Fabric architecture, then this is the book for you. This book will also benefit senior data professionals such as chief data officers looking to integrate Data Fabric architecture into the broader ecosystem.
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.
Data Engineering With Aws
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Author : Gareth Eagar
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-10-31
Data Engineering With Aws written by Gareth Eagar 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 2023-10-31 with Computers categories.
Looking to revolutionize your data transformation game with AWS? Look no further! From strong foundations to hands-on building of data engineering pipelines, our expert-led manual has got you covered. Key Features Delve into robust AWS tools for ingesting, transforming, and consuming data, and for orchestrating pipelines Stay up to date with a comprehensive revised chapter on Data Governance Build modern data platforms with a new section covering transactional data lakes and data mesh Book DescriptionThis book, authored by a seasoned Senior Data Architect with 25 years of experience, aims to help you achieve proficiency in using the AWS ecosystem for data engineering. This revised edition provides updates in every chapter to cover the latest AWS services and features, takes a refreshed look at data governance, and includes a brand-new section on building modern data platforms which covers; implementing a data mesh approach, open-table formats (such as Apache Iceberg), and using DataOps for automation and observability. You'll begin by reviewing the key concepts and essential AWS tools in a data engineer's toolkit and getting acquainted with modern data management approaches. You'll then architect a data pipeline, review raw data sources, transform the data, and learn how that transformed data is used by various data consumers. You’ll learn how to ensure strong data governance, and about populating data marts and data warehouses along with how a data lakehouse fits into the picture. After that, you'll be introduced to AWS tools for analyzing data, including those for ad-hoc SQL queries and creating visualizations. Then, you'll explore how the power of machine learning and artificial intelligence can be used to draw new insights from data. In the final chapters, you'll discover transactional data lakes, data meshes, and how to build a cutting-edge data platform on AWS. By the end of this AWS book, you'll be able to execute data engineering tasks and implement a data pipeline on AWS like a pro!What you will learn Seamlessly ingest streaming data with Amazon Kinesis Data Firehose Optimize, denormalize, and join datasets with AWS Glue Studio Use Amazon S3 events to trigger a Lambda process to transform a file Load data into a Redshift data warehouse and run queries with ease Visualize and explore data using Amazon QuickSight Extract sentiment data from a dataset using Amazon Comprehend Build transactional data lakes using Apache Iceberg with Amazon Athena Learn how a data mesh approach can be implemented on AWS Who this book is forThis book is for data engineers, data analysts, and data architects who are new to AWS and looking to extend their skills to the AWS cloud. Anyone new to data engineering who wants to learn about the foundational concepts, while gaining practical experience with common data engineering services on AWS, will also find this book useful. A basic understanding of big data-related topics and Python coding will help you get the most out of this book, but it’s not a prerequisite. Familiarity with the AWS console and core services will also help you follow along.