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  • Data Management at Scale : Modern Data Architecture with Data Mesh and Data Fabric
    Data Management at Scale : Modern Data Architecture with Data Mesh and Data Fabric

    As data management continues to evolve rapidly, managing all of your data in a central place, such as a data warehouse, is no longer scalable.Today's world is about quickly turning data into value.This requires a paradigm shift in the way we federate responsibilities, manage data, and make it available to others.With this practical book, you'll learn how to design a next-gen data architecture that takes into account the scale you need for your organization. Executives, architects and engineers, analytics teams, and compliance and governance staff will learn how to build a next-gen data landscape.Author Piethein Strengholt provides blueprints, principles, observations, best practices, and patterns to get you up to speed. Examine data management trends, including regulatory requirements, privacy concerns, and new developments such as data mesh and data fabricGo deep into building a modern data architecture, including cloud data landing zones, domain-driven design, data product design, and moreExplore data governance and data security, master data management, self-service data marketplaces, and the importance of metadata

    Price: 59.99 £ | Shipping*: 0.00 £
  • Modern Data Strategy
    Modern Data Strategy

    This book contains practical steps business users can take to implement data management in a number of ways, including data governance, data architecture, master data management, business intelligence, and others.It defines data strategy, and covers chapters that illustrate how to align a data strategy with the business strategy, a discussion on valuing data as an asset, the evolution of data management, and who should oversee a data strategy.This provides the user with a good understanding of what a data strategy is and its limits. Critical to a data strategy is the incorporation of one or more data management domains.Chapters on key data management domains—data governance, data architecture, master data management and analytics, offer the user a practical approach to data management execution within a data strategy.The intent is to enable the user to identify how execution on one or more data management domains can help solve business issues. This book is intended for business users who work with data, who need to manage one or more aspects of the organization’s data, and who want to foster an integrated approach for how enterprise data is managed.This book is also an excellent reference for students studying computer science and business management or simply for someone who has been tasked with starting or improving existing data management.

    Price: 129.99 £ | Shipping*: 0.00 £
  • Data Analytics for IT Networks : Developing Innovative Use Cases
    Data Analytics for IT Networks : Developing Innovative Use Cases

    Use data analytics to drive innovation and value throughout your network infrastructure Network and IT professionals capture immense amounts of data from their networks.Buried in this data are multiple opportunities to solve and avoid problems, strengthen security, and improve network performance.To achieve these goals, IT networking experts need a solid understanding of data science, and data scientists need a firm grasp of modern networking concepts.Data Analytics for IT Networks fills these knowledge gaps, allowing both groups to drive unprecedented value from telemetry, event analytics, network infrastructure metadata, and other network data sources. Drawing on his pioneering experience applying data science to large-scale Cisco networks, John Garrett introduces the specific data science methodologies and algorithms network and IT professionals need, and helps data scientists understand contemporary network technologies, applications, and data sources. After establishing this shared understanding, Garrett shows how to uncover innovative use cases that integrate data science algorithms with network data.He concludes with several hands-on, Python-based case studies reflecting Cisco Customer Experience (CX) engineers’ supporting its largest customers.These are designed to serve as templates for developing custom solutions ranging from advanced troubleshooting to service assurance. Understand the data analytics landscape and its opportunities in Networking See how elements of an analytics solution come together in the practical use cases Explore and access network data sources, and choose the right data for your problem Innovate more successfully by understanding mental models and cognitive biases Walk through common analytics use cases from many industries, and adapt them to your environment Uncover new data science use cases for optimizing large networks Master proven algorithms, models, and methodologies for solving network problems Adapt use cases built with traditional statistical methods Use data science to improve network infrastructure analysisAnalyze control and data planes with greater sophistication Fully leverage your existing Cisco tools to collect, analyze, and visualize data

    Price: 44.99 £ | Shipping*: 0.00 £
  • Innovative Applications of Big Data in the Railway Industry
    Innovative Applications of Big Data in the Railway Industry

    Use of big data has proven to be beneficial within many different industries, especially in the field of engineering; however, infiltration of this type of technology into more traditional heavy industries, such as the railways, has been limited. Innovative Applications of Big Data in the Railway Industry is a pivotal reference source for the latest research findings on the utilization of data sets in the railway industry.Featuring extensive coverage on relevant areas such as driver support systems, railway safety management, and obstacle detection, this publication is an ideal resource for transportation planners, engineers, policymakers, and graduate-level engineering students seeking current research on a specific application of big data and its effects on transportation.

    Price: 256.00 £ | Shipping*: 0.00 £
  • Where can one find stylish, modern, and trendy fashion for plus-size individuals online?

    One can find stylish, modern, and trendy fashion for plus-size individuals online at retailers such as ASOS Curve, Eloquii, and Fashion to Figure. These retailers offer a wide range of trendy clothing options including dresses, tops, bottoms, and outerwear designed specifically for plus-size individuals. Additionally, online marketplaces like Nordstrom and Amazon also offer a variety of stylish and modern plus-size fashion options from a range of different brands.

  • What do you think of the trendy word innovative?

    I think the word "innovative" is often overused and has become somewhat of a buzzword in today's society. While it is important to strive for innovation and creativity in various fields, the term itself can sometimes be vague and lack specificity. It is crucial to truly understand the meaning behind the word and ensure that any claims of being innovative are backed up by tangible results or advancements.

  • What do you think of the trendy term innovative?

    I think the term "innovative" is often overused and has become somewhat of a buzzword in today's business world. While innovation is crucial for progress and success, it's important to not just label something as innovative for the sake of it. True innovation involves thinking outside the box, taking risks, and creating something truly groundbreaking. It's important to distinguish between genuine innovation and simply following a trend.

  • What is currently trendy and modern?

    Currently, minimalist and sustainable fashion is trendy and modern. People are opting for simple, high-quality pieces that are versatile and timeless. In terms of technology, smart home devices and wearable tech are popular choices. Additionally, plant-based diets and eco-friendly practices are modern trends that are gaining popularity.

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  • Modern Data Science with R
    Modern Data Science with R

    From a review of the first edition: "Modern Data Science with R… is rich with examples and is guided by a strong narrative voice.What’s more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics" (The American Statistician). Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems.Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions. The second edition is updated to reflect the growing influence of the tidyverse set of packages.All code in the book has been revised and styled to be more readable and easier to understand.New functionality from packages like sf, purrr, tidymodels, and tidytext is now integrated into the text.All chapters have been revised, and several have been split, re-organized, or re-imagined to meet the shifting landscape of best practice.

    Price: 84.99 £ | Shipping*: 0.00 £
  • Modern Data Visualization with R
    Modern Data Visualization with R

    Modern Data Visualization with R describes the many ways that raw and summary data can be turned into visualizations that convey meaningful insights.It starts with basic graphs such as bar charts, scatter plots, and line charts, but progresses to less well-known visualizations such as tree maps, alluvial plots, radar charts, mosaic plots, effects plots, correlation plots, biplots, and the mapping of geographic data.Both static and interactive graphics are described and the use of color, shape, shading, grouping, annotation, and animations are covered in detail.The book moves from a default look and feel for graphs, to graphs with customized colors, fonts, legends, annotations, and organizational themes. FeaturesContains a wide breadth of graph types including newer and less well-known approachesConnects each graph type to the characteristics of the data and the goals of the analysisMoves the reader from simple graphs describing one variable to building visualizations that describe complex relationships among many variablesProvides newer approaches to creating interactive web graphics via JavaScript librariesDetails how to customize each graph type to meet users’ needs and those of their audiencesGives methods for creating visualizations that are publication ready for print (in color or black and white) and the webSuggests best practicesOffers examples from a wide variety of fieldsThe book is written for those new to data analysis as well as the seasoned data scientist.It can be used for both teaching and research, and will particularly appeal to anyone who needs to describe data visually and wants to find and emulate the most appropriate method quickly.The reader should have some basic coding experience, but expertise in R is not required.Some of the later chapters (e.g., visualizing statistical models) assume exposure to statistical inference at the level of analysis of variance and regression.

    Price: 61.99 £ | Shipping*: 0.00 £
  • Modern Data Architecture on Azure : Design Data-centric Solutions on Microsoft Azure
    Modern Data Architecture on Azure : Design Data-centric Solutions on Microsoft Azure

    This book is an exhaustive guide to designing and implementing data solutions on Azure.It covers the process of managing data from end to end, starting from data collection all the way through transformation, distribution, and consumption. Modern Data Architecture on Azure begins with an introduction to the fundaments of data management, followed by a demonstration of how to build relational and non-relational data solutions on Azure.Here, you will learn data processing for complex analysis and how to work with CSV and JSON files.Moving forward, you will learn the foundational concepts of big data architecture, along with data management patterns and technology options offered by Azure.From there, you’ll be walked through the data architecture process, including data consortium on Azure, enterprise data governance, and much more.The book culminates with a deep dive into data architecture frameworks with data modeling. After reading this book, you will have a thorough understanding of data design and analytics using Azure, allowing you to collect and analyze massive amounts of data to optimize business performance, forecast future results, and more. What Will You LearnUnderstand the fundamentals of data architecture including data management, data handling ethics, data governance, and metadata managementAnalyze and understand business needs to choose the right Azure services and make informed business decisionsUnderstand Azure Cloud Data design patterns for relational and non-relational data, batch real-time processing, and ETL/ELT pipelinesModernize data architecture using Azure to leverage data and AI to enable digital transformation by securing and optimizing overall data lifecycle managementWho Is This Book For:Data solution architects, data engineers, and IT consultants who want to gain a better understanding of modern data architecture design and implementation on Azure.

    Price: 44.99 £ | Shipping*: 0.00 £
  • Delta Lake: The Definitive Guide : Modern Data Lakehouse Architectures with Data Lakes
    Delta Lake: The Definitive Guide : Modern Data Lakehouse Architectures with Data Lakes

    Ready to simplify the process of building data lakehouses and data pipelines at scale?In this practical guide, learn how Delta Lake is helping data engineers, data scientists, and data analysts overcome key data reliability challenges with modern data engineering and management techniques. Authors Denny Lee, Tristen Wentling, Scott Haines, and Prashanth Babu (with contributions from Delta Lake maintainer R.Tyler Croy) share expert insights on all things Delta Lake--including how to run batch and streaming jobs concurrently and accelerate the usability of your data.You'll also uncover how ACID transactions bring reliability to data lakehouses at scale. This book helps you:Understand key data reliability challenges and how Delta Lake solves themExplain the critical role of Delta transaction logs as a single source of truthLearn the Delta Lake ecosystem with technologies like Apache Flink, Kafka, and TrinoArchitect data lakehouses with the medallion architectureOptimize Delta Lake performance with features like deletion vectors and liquid clustering

    Price: 63.99 £ | Shipping*: 0.00 £
  • Can Modern Combat 5 be played with mobile data?

    Yes, Modern Combat 5 can be played with mobile data. The game is designed to be played online, so as long as you have a stable internet connection, you can play it using mobile data. However, keep in mind that playing online games with mobile data may consume a significant amount of data, so it's important to monitor your data usage to avoid exceeding your data plan.

  • Do active mobile data consume data volume?

    Yes, active mobile data does consume data volume. When your mobile data is turned on and you are using apps, browsing the internet, streaming videos, or downloading files, data is being consumed from your data plan. It is important to monitor your data usage to avoid exceeding your data limit and potentially incurring extra charges from your mobile service provider.

  • Do activated mobile data consume data volume?

    Yes, activated mobile data does consume data volume. When mobile data is turned on, it allows your device to connect to the internet using your cellular network, and any data used during this connection will be deducted from your data plan. Activities such as browsing the web, streaming videos, or using apps that require an internet connection will all consume data volume when mobile data is activated. It's important to monitor your data usage to avoid exceeding your plan's limits and incurring additional charges.

  • What are master data and transactional data?

    Master data refers to the core data entities of an organization, such as customer, product, employee, and supplier information. This data is typically static and does not change frequently. Master data is used as a reference point for transactional data. On the other hand, transactional data refers to the detailed records of day-to-day business activities, such as sales orders, purchase orders, invoices, and payments. This data is dynamic and changes frequently as business transactions occur. Transactional data is used to track and record the specific activities and events within an organization.

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