Take a look at our Data Processing books. Shulph carries a great selection of Data Processing books, and we are always adding more.
Explore the entire Hyperledger blockchain family, including frameworks such as Fabric, Sawtooth, Indy, Burrow, and Iroha; and tools such as Composer, Explorer, and Caliper. Key Features Plan, design, and create a full-fledged private decentralized application using Hyperledger services Master the ins and outs of the Hyperledger network using real-world examples Packed with problem-solution-based recipes to tackle pain areas in the blockchain development cycle Book Description Hyperledger is an open-source project and creates private blockchain applications for a range of domains. This book will be your desk reference as you explore common and not-so-common challenges faced while building blockchain networks using Hyperledger services. We'll work through all Hyperledger platform modules to understand their services and features and build end-to-end blockchain applications using various frameworks and tools supported by Hyperledger. This book's independent, recipe-based approach (packed with real-world examples) will familiarize you with the blockchain development cycle. From modeling a business network to integrating with various tools, you will cover it all. We'll cover common and not-so-common challenges faced in the blockchain life cycle. Later, we'll delve into how we can interact with the Hyperledger Fabric blockchain, covering all the principles you need to master, such as chaincode, smart contracts, and much more. We'll also address the scalability and security issues currently faced in blockchain development. By the end of this book, you will be able to implement each recipe to plan, design, and create a full-fledged, private, decentralized application to meet organizational needs. What you will learn Create the most popular permissioned blockchain network with Fabric and Composer Build permissioned and permission-less blockchains using Sawtooth Utilize built-in Iroha asset/account management with role-based permissions Implement and run Ethereum smart contracts with Burrow Get to grips with security and scalability in Hyperledger Explore and view blockchain data using Hyperledger Explorer Produce reports containing performance indicators and benchmarks using Caliper Who this book is for This book is for blockchain developers who want to understand how they can apply Hyperledger services in their day-to-day projects. This book uses a recipe-based approach to help you use Hyperledger to build powerful, decentralized autonomous applications. We assume the reader has a basic knowledge of the Blockchain technology and cryptography concepts
Continuous integration with Jenkins speeds up your projects and saves you time and money Key Features Get a perfect balance of theories and hands-on activities Apply continuous integration and delivery to your workflow Explore concepts such as the plugin ecosystem and adaptive build parameters, among others Book Description Jenkins Fundamentals teaches you everything you need to know about installing, setting up, configuring, and integrating a Jenkins server with your project to speed up the product development life cycle. You will learn how to deploy via Docker and integrate with Git. Next you will move on to understanding bespoke plugins and services to further customize your workflow, and dynamically adjust your build requirements when pushing to production. Once you have grasped the basics, you will explore user and plugin management along with updating and upgrading Jenkins. You will set up freestyle projects and views to manage your projects, followed by configuring parameters for your projects and creating upstream and downstream projects with views to visualize the projects. In addition to this, you will create a secure connection from your master to your build slaves and configure your build tasks to run on the slave. By the end of this book, you will be able to successfully set up a Jenkins server that checks your source code repositories for changes, triggering new builds and unit tests while informing all of the key stakeholders in your organization. What you will learn Set up and deploy a Jenkins server across different platforms via Docker Design development workflows that enable continuous integration and then easily integrate with Jenkins Explore community plugins and use them to extend core Jenkins functionality Set up a freestyle project as well as a view to manage your projects Understand source control and pipelines, and build parameters in the context of Git and Jenkins Configure general-purpose freestyle projects, or use more formal pipeline-driven implementation Explore concepts such as the plugin ecosystem and adaptive build parameters, among others Apply continuous integration and delivery to your workflow Who this book is for Jenkins Fundamentals is for you if you are a software developer, with prior experience in application development, looking to build and transition to a more centrally managed deployment process. This book is ideal if you need a real-world introduction to continuous delivery, with a view to setting up and using Jenkins as a tool for your own software development life cycle.
Learn how to use Power BI to deliver the insights needed to help your enterprise survive and thriveKey FeaturesLearn simple through to advanced Power BI features in a clear, concise way using real-world examplesDevelop powerful analytical models and reports that extract key business insightsPublish, share and collaborate on impressive reports, dashboards, apps, and goalsBook DescriptionTo succeed in today's transforming business world, organizations need business intelligence capabilities to make smarter decisions faster than ever before. This updated second edition of Learn Power BI takes you on a journey of data exploration and discovery, using Microsoft Power BI to ingest, cleanse, and organize data in order to unlock key business insights that can then be shared with others. This newly revised and expanded edition of Learn Power BI covers all of the latest features and interface changes and takes you through the fundamentals of business intelligence projects, how to deploy, adopt, and govern Power BI within your organization, and how to leverage your knowledge in the marketplace and broader ecosystem that is Power BI. As you progress, you will learn how to ingest, cleanse, and transform your data into stunning visualizations, reports, and dashboards that speak to business decision-makers. By the end of this Power BI book, you will be fully prepared to be the data analysis hero of your organization – or even start a new career as a business intelligence professional.What you will learnGet up and running quickly with Power BIUnderstand and plan your business intelligence projectsConnect to and transform data using Power QueryCreate data models optimized for analysis and reportingPerform simple and complex DAX calculations to enhance analysisDiscover business insights and create professional reportsCollaborate via Power BI dashboards, apps, goals, and scorecardsDeploy and govern Power BI, including using deployment pipelinesWho this book is forIf you're an IT manager, data analyst, or BI user new to using Power BI for solving business intelligence problems, this book is for you. You'll also find this book helpful if you want to migrate from other BI tools to create powerful and interactive dashboards. No experience of working with Power BI is expected.
A beginner's guide to analyzing and visualizing your Elasticsearch data using Kibana 7 and Timelion Key Features Gain a fundamental understanding of how Kibana operates within the Elastic Stack Explore your data with Elastic Graph and create rich dashboards in Kibana Learn scalable data visualization techniques in Kibana 7 Book Description Kibana is a window into the Elastic Stack, that enables the visual exploration and real-time analysis of your data in Elasticsearch. This book will help you understand the core concepts of the use of Kibana 7 for rich analytics and data visualization. If you're new to the tool or want to get to grips with the latest features introduced in Kibana 7, this book is the perfect beginner's guide. You'll learn how to set up and configure the Elastic Stack and understand where Kibana sits within the architecture. As you advance, you'll learn how to ingest data from different sources using Beats or Logstash into Elasticsearch, followed by exploring and visualizing data in Kibana. Whether working with time series data to create complex graphs using Timelion or embedding visualizations created in Kibana into your web applications, this book covers it all. It also covers topics that every Elastic developer needs to be aware of, such as installing and configuring Application Performance Monitoring (APM) servers and agents. Finally, you'll also learn how to create effective machine learning jobs in Kibana to find anomalies in your data. By the end of this book, you'll have a solid understanding of Kibana, and be able to create your own visual analytics solutions from scratch. What you will learn Explore the data-driven architecture of the Elastic Stack Install and set up Kibana 7 and other Elastic Stack components Use Beats and Logstash to get input from different data sources Create different visualizations using Kibana Build enterprise-grade Elastic dashboards from scratch Use Timelion to play with time series data Install and configure APM servers and APM agents Work with Dev Tools, Spaces, Graph, and other important tools Who this book is for If you're an aspiring Elastic developer or data analysts, this book is for you. You'll also find it useful if you want to get up to speed with the new features of Kibana 7 and perform data visualization on enterprise data. No prior knowledge of Kibana is expected, but some experience with Elasticsearch will be helpful.
Combine advanced analytics including Machine Learning, Deep Learning Neural Networks and Natural Language Processing with modern scalable technologies including Apache Spark to derive actionable insights from Big Data in real-time Key Features Make a hands-on start in the fields of Big Data, Distributed Technologies and Machine Learning Learn how to design, develop and interpret the results of common Machine Learning algorithms Uncover hidden patterns in your data in order to derive real actionable insights and business value Book Description Every person and every organization in the world manages data, whether they realize it or not. Data is used to describe the world around us and can be used for almost any purpose, from analyzing consumer habits to fighting disease and serious organized crime. Ultimately, we manage data in order to derive value from it, and many organizations around the world have traditionally invested in technology to help process their data faster and more efficiently. But we now live in an interconnected world driven by mass data creation and consumption where data is no longer rows and columns restricted to a spreadsheet, but an organic and evolving asset in its own right. With this realization comes major challenges for organizations: how do we manage the sheer size of data being created every second (think not only spreadsheets and databases, but also social media posts, images, videos, music, blogs and so on)? And once we can manage all of this data, how do we derive real value from it? The focus of Machine Learning with Apache Spark is to help us answer these questions in a hands-on manner. We introduce the latest scalable technologies to help us manage and process big data. We then introduce advanced analytical algorithms applied to real-world use cases in order to uncover patterns, derive actionable insights, and learn from this big data. What you will learn Understand how Spark fits in the context of the big data ecosystem Understand how to deploy and configure a local development environment using Apache Spark Understand how to design supervised and unsupervised learning models Build models to perform NLP, deep learning, and cognitive services using Spark ML libraries Design real-time machine learning pipelines in Apache Spark Become familiar with advanced techniques for processing a large volume of data by applying machine learning algorithms Who this book is for This book is aimed at Business Analysts, Data Analysts and Data Scientists who wish to make a hands-on start in order to take advantage of modern Big Data technologies combined with Advanced Analytics.
Learn how to use R to apply powerful machine learning methods and gain insight into real-world applications using clustering, logistic regressions, random forests, support vector machine, and more. Key Features Use R 3.5 to implement real-world examples in machine learning Implement key machine learning algorithms to understand the working mechanism of smart models Create end-to-end machine learning pipelines using modern libraries from the R ecosystem Book Description Machine Learning with R Quick Start Guide takes you on a data-driven journey that starts with the very basics of R and machine learning. It gradually builds upon core concepts so you can handle the varied complexities of data and understand each stage of the machine learning pipeline. From data collection to implementing Natural Language Processing (NLP), this book covers it all. You will implement key machine learning algorithms to understand how they are used to build smart models. You will cover tasks such as clustering, logistic regressions, random forests, support vector machines, and more. Furthermore, you will also look at more advanced aspects such as training neural networks and topic modeling. By the end of the book, you will be able to apply the concepts of machine learning, deal with data-related problems, and solve them using the powerful yet simple language that is R. What you will learn Introduce yourself to the basics of machine learning with R 3.5 Get to grips with R techniques for cleaning and preparing your data for analysis and visualize your results Learn to build predictive models with the help of various machine learning techniques Use R to visualize data spread across multiple dimensions and extract useful features Use interactive data analysis with R to get insights into data Implement supervised and unsupervised learning, and NLP using R libraries Who this book is for This book is for graduate students, aspiring data scientists, and data analysts who wish to enter the field of machine learning and are looking to implement machine learning techniques and methodologies from scratch using R 3.5. A working knowledge of the R programming language is expected.
Build, manage, and configure high-performing, reliable NoSQL database for your applications with Cassandra Key Features Write programs more efficiently using Cassandra's features with the help of examples Configure Cassandra and fine-tune its parameters depending on your needs Integrate Cassandra database with Apache Spark and build strong data analytics pipeline Book Description With ever-increasing rates of data creation, the demand for storing data fast and reliably becomes a need. Apache Cassandra is the perfect choice for building fault-tolerant and scalable databases. Mastering Apache Cassandra 3.x teaches you how to build and architect your clusters, configure and work with your nodes, and program in a high-throughput environment, helping you understand the power of Cassandra as per the new features. Once you've covered a brief recap of the basics, you'll move on to deploying and monitoring a production setup and optimizing and integrating it with other software. You'll work with the advanced features of CQL and the new storage engine in order to understand how they function on the server-side. You'll explore the integration and interaction of Cassandra components, followed by discovering features such as token allocation algorithm, CQL3, vnodes, lightweight transactions, and data modelling in detail. Last but not least you will get to grips with Apache Spark. By the end of this book, you'll be able to analyse big data, and build and manage high-performance databases for your application. What you will learn Write programs more efficiently using Cassandra's features more efficiently Exploit the given infrastructure, improve performance, and tweak the Java Virtual Machine (JVM) Use CQL3 in your application in order to simplify working with Cassandra Configure Cassandra and fine-tune its parameters depending on your needs Set up a cluster and learn how to scale it Monitor a Cassandra cluster in different ways Use Apache Spark and other big data processing tools Who this book is for Mastering Apache Cassandra 3.x is for you if you are a big data administrator, database administrator, architect, or developer who wants to build a high-performing, scalable, and fault-tolerant database. Prior knowledge of core concepts of databases is required.
Get to grips with Kibana and its advanced functions to create interactive visualizations and dashboards Key Features Explore visualizations and perform histograms, stats, and map analytics Unleash X-Pack and Timelion, and learn alerting, monitoring, and reporting features Manage dashboards with Beats and create machine learning jobs for faster analytics Book Description Kibana is one of the popular tools among data enthusiasts for slicing and dicing large datasets and uncovering Business Intelligence (BI) with the help of its rich and powerful visualizations. To begin with, Mastering Kibana 6.x quickly introduces you to the features of Kibana 6.x, before teaching you how to create smart dashboards in no time. You will explore metric analytics and graph exploration, followed by understanding how to quickly customize Kibana dashboards. In addition to this, you will learn advanced analytics such as maps, hits, and list analytics. All this will help you enhance your skills in running and comparing multiple queries and filters, influencing your data visualization skills at scale. With Kibana's Timelion feature, you can analyze time series data with histograms and stats analytics. By the end of this book, you will have created a speedy machine learning job using X-Pack capabilities. What you will learn Create unique dashboards with various intuitive data visualizations Visualize Timelion expressions with added histograms and stats analytics Integrate X-Pack with your Elastic Stack in simple steps Extract data from Elasticsearch for advanced analysis and anomaly detection using dashboards Build dashboards from web applications for application logs Create monitoring and alerting dashboards using Beats Who this book is for Mastering Kibana 6.x is for you if you are a big data engineer, DevOps engineer, or data scientist aspiring to go beyond data visualization at scale and gain maximum insights from their large datasets. Basic knowledge of Elasticstack will be an added advantage, although not mandatory.
Understand and build beautiful and advanced plots with Matplotlib and Python Key Features Practical guide with hands-on examples to design interactive plots Advanced techniques to constructing complex plots Explore 3D plotting and visualization using Jupyter Notebook Book Description In this book, you'll get hands-on with customizing your data plots with the help of Matplotlib. You'll start with customizing plots, making a handful of special-purpose plots, and building 3D plots. You'll explore non-trivial layouts, Pylab customization, and more about tile configuration. You'll be able to add text, put lines in plots, and also handle polygons, shapes, and annotations. Non-Cartesian and vector plots are exciting to construct, and you'll explore them further in this book. You'll delve into niche plots and visualize ordinal and tabular data. In this book, you'll be exploring 3D plotting, one of the best features when it comes to 3D data visualization, along with Jupyter Notebook, widgets, and creating movies for enhanced data representation. Geospatial plotting will also be explored. Finally, you'll learn how to create interactive plots with the help of Jupyter. Learn expert techniques for effective data visualization using Matplotlib 3 and Python with our latest offering -- Matplotlib 3.0 Cookbook What you will learn Deal with non-trivial and unusual plots Understanding Basemap methods Customize and represent data in 3D Construct Non-Cartesian and vector plots Design interactive plots using Jupyter Notebook Make movies for enhanced data representation Who this book is for This book is aimed at individuals who want to explore data visualization techniques. A basic knowledge of Matplotlib and Python is required.
Design, develop, and master efficient Power BI solutions for impactful business insights Key Features Get to grips with the fundamentals of Microsoft Power BI Combine data from multiple sources, create visuals, and publish reports across platforms Understand Power BI concepts with real-world use cases Book Description Microsoft Power BI Complete Reference Guide gets you started with business intelligence by showing you how to install the Power BI toolset, design effective data models, and build basic dashboards and visualizations that make your data come to life. In this Learning Path, you will learn to create powerful interactive reports by visualizing your data and learn visualization styles, tips and tricks to bring your data to life. You will be able to administer your organization's Power BI environment to create and share dashboards. You will also be able to streamline deployment by implementing security and regular data refreshes. Next, you will delve deeper into the nuances of Power BI and handling projects. You will get acquainted with planning a Power BI project, development, and distribution of content, and deployment. You will learn to connect and extract data from various sources to create robust datasets, reports, and dashboards. Additionally, you will learn how to format reports and apply custom visuals, animation and analytics to further refine your data. By the end of this Learning Path, you will learn to implement the various Power BI tools such as on-premises gateway together along with staging and securely distributing content via apps. This Learning Path includes content from the following Packt products: Microsoft Power BI Quick Start Guide by Devin Knight et al. Mastering Microsoft Power BI by Brett Powell What you will learn Connect to data sources using both import and DirectQuery options Leverage built-in and custom visuals to design effective reports Administer a Power BI cloud tenant for your organization Deploy your Power BI Desktop files into the Power BI Report Server Build efficient data retrieval and transformation processes Who this book is for Microsoft Power BI Complete Reference Guide is for those who want to learn and use the Power BI features to extract maximum information and make intelligent decisions that boost their business. If you have a basic understanding of BI concepts and want to learn how to apply them using Microsoft Power BI, then Learning Path is for you. It consists of real-world examples on Power BI and goes deep into the technical issues, covers additional protocols, and much more.