Analiza danych
Analiza danych jest ekscytującą dyscypliną, która umożliwia zrozumienie pewnych zjawisk, uzyskanie wglądu i wiedzy na podstawie surowych danych. Pojęcie to oznacza dokładnie przetwarzanie danych za pomocą technik matematycznych i statystycznych w celu uzyskania cennych wniosków, podjęcia ważnych decyzji i opracowania przydatnych produktów. Termin ten wywodzi się od angielskiego data science, często traktowanego jako synonim takich terminów, jak analityka biznesowa, badania operacyjne, business intelligence, wywiad konkurencyjny, analiza i modelowanie danych, a także pozyskiwanie wiedzy. Dzięki takim technologiom, jak języki Python czy R, platformy Hadoop i Spark masz szansę wyciągnąć maksimum wniosków, dostrzec szanse na rozwój swojej organizacji albo przewidzieć i zapobiec zagrożeniom.
Blockchain Quick Reference. A guide to exploring decentralized blockchain application development
Brenn Hill, Samanyu Chopra, Paul Valencourt
Blockchain Quick Reference takes you through the electrifying world of blockchain technology and is designed for those who want to polish their existing knowledge regarding the various pillars of the blockchain ecosystem.This book is your go-to guide, teaching you how to apply principles and ideas for making your life and business better. You will cover the architecture, Initial Coin Offerings (ICOs), tokens, smart contracts, and terminologies of the blockchain technology, before studying how they work. All you need is a curious mind to get started with blockchain technology. Once you have grasped the basics, you will explore components of Ethereum, such as ether tokens, transactions, and smart contracts, in order to build simple Dapps. You will then move on to learning why Solidity is used specifically for Ethereum-based projects, followed by exploring different types of blockchain with easy-to-follow examples. All this will help you tackle challenges and problems. By the end of this book, you will not only have solved current and future problems relating to blockchain technology but will also be able to build efficient decentralized applications.
Xun (Brian) Wu, Weimin Sun
Blockchain is a technology that powers the development of decentralized applications.This technology allows the construction of a network with no single control that enables participants to make contributions to and receive benefits from the network directly.This book will give you a thorough overview of blockchain and explain how a blockchain works.You will begin by going through various blockchain consensus mechanisms and cryptographic hash functions. You will then learn the fundamentals of programming in Solidity – the defacto language for developing decentralize, applications in Ethereum. After that, you will set up an Ethereum development environment and develop, package, build, and test campaign-decentralized applications.The book also shows you how to set up Hyperledger composer tools, analyze business scenarios, design business models, and write a chain code. Finally, you will get a glimpse of how blockchain is actually used in different real-world domains. By the end of this guide, you will be comfortable working with basic blockchain frameworks, and develop secure, decentralized applications in a hassle-free manner.
Building Analytics Teams. Harnessing analytics and artificial intelligence for business improvement
John K. Thompson
In Building Analytics Teams, John K. Thompson, with his 30+ years of experience and expertise, illustrates the fundamental concepts of building and managing a high-performance analytics team, including what to do, who to hire, projects to undertake, and what to avoid in the journey of building an analytically sound team. The core processes in creating an effective analytics team and the importance of the business decision-making life cycle are explored to help achieve initial and sustainable success.The book demonstrates the various traits of a successful and high-performing analytics team and then delineates the path to achieve this with insights on the mindset, advanced analytics models, and predictions based on data analytics. It also emphasizes the significance of the macro and micro processes required to evolve in response to rapidly changing business needs.The book dives into the methods and practices of managing, developing, and leading an analytics team. Once you've brought the team up to speed, the book explains how to govern executive expectations and select winning projects.By the end of this book, you will have acquired the knowledge to create an effective business analytics team and develop a production environment that delivers ongoing operational improvements for your organization.
Narayan Prusty
Blockchain is a decentralized ledger that maintains a continuously growing list of data records that are secured from tampering and revision. Every user is allowed to connectto the network, send new transactions to it, verify transactions, and create new blocks,making it permission-less.This book will teach you what blockchain is, how it maintains data integrity, and how to create real-world blockchain projects using Ethereum. With interesting real-worldprojects, you will learn how to write smart contracts which run exactly as programmedwithout any chance of fraud, censorship, or third-party interference, and build end-to-eapplications for blockchain.You will learn about concepts such as cryptography in cryptocurrencies, ether security, mining, smart contracts, solidity, and more. You will also learn about web sockets, various API services for Ethereum, and much more.The blockchain is the main technical innovation of bitcoin, where it serves as the public ledger for bitcoin transactions.
François Voron
FastAPI is a web framework for building APIs with Python 3.6 and its later versions based on standard Python-type hints. With this book, you’ll be able to create fast and reliable data science API backends using practical examples.This book starts with the basics of the FastAPI framework and associated modern Python programming language concepts. You'll be taken through all the aspects of the framework, including its powerful dependency injection system and how you can use it to communicate with databases, implement authentication and integrate machine learning models. Later, you’ll cover best practices relating to testing and deployment to run a high-quality and robust application. You’ll also be introduced to the extensive ecosystem of Python data science packages. As you progress, you’ll learn how to build data science applications in Python using FastAPI. The book also demonstrates how to develop fast and efficient machine learning prediction backends and test them to achieve the best performance. Finally, you’ll see how to implement a real-time face detection system using WebSockets and a web browser as a client.By the end of this FastAPI book, you’ll have not only learned how to implement Python in data science projects but also how to maintain and design them to meet high programming standards with the help of FastAPI.
Chanchal Singh, Manisha Sethi, Manish Kumar, Anshul...
Apache Kafka is a popular distributed streaming platform that acts as a messaging queue or an enterprise messaging system. It lets you publish and subscribe to a stream of records, and process them in a fault-tolerant way as they occur.This book is a comprehensive guide to designing and architecting enterprise-grade streaming applications using Apache Kafka and other big data tools. It includes best practices for building such applications, and tackles some common challenges such as how to use Kafka efficiently and handle high data volumes with ease. This book first takes you through understanding the type messaging system and then provides a thorough introduction to Apache Kafka and its internal details. The second part of the book takes you through designing streaming application using various frameworks and tools such as Apache Spark, Apache Storm, and more. Once you grasp the basics, we will take you through more advanced concepts in Apache Kafka such as capacity planning and security.By the end of this book, you will have all the information you need to be comfortable with using Apache Kafka, and to design efficient streaming data applications with it.
Rising Odegua, Stephen Oni
Most data analysts use Python and pandas for data processing for the convenience and performance these libraries provide. However, JavaScript developers have always wanted to use machine learning in the browser as well. This book focuses on how Danfo.js brings data processing, analysis, and ML tools to JavaScript developers and how to make the most of this library to build data-driven applications.Starting with an overview of modern JavaScript, you’ll cover data analysis and transformation with Danfo.js and Dnotebook. The book then shows you how to load different datasets, combine and analyze them by performing operations such as handling missing values and string manipulations. You’ll also get to grips with data plotting, visualization, aggregation, and group operations by combining Danfo.js with Plotly. As you advance, you’ll create a no-code data analysis and handling system and create-react-app, react-table, react-chart, Draggable.js, and tailwindcss, and understand how to use TensorFlow.js and Danfo.js to build a recommendation system. Finally, you’ll build a Twitter analytics dashboard powered by Danfo.js, Next.js, node-nlp, and Twit.js.By the end of this app development book, you’ll be able to build and embed data analytics, visualization, and ML capabilities into any JavaScript app in server-side Node.js or the browser.
Brij Kishore Pandey, Emily Ro Schoof
Modern extract, transform, and load (ETL) pipelines for data engineering have favored the Python language for its broad range of uses and a large assortment of tools, applications, and open source components. With its simplicity and extensive library support, Python has emerged as the undisputed choice for data processing.In this book, you’ll walk through the end-to-end process of ETL data pipeline development, starting with an introduction to the fundamentals of data pipelines and establishing a Python development environment to create pipelines. Once you've explored the ETL pipeline design principles and ET development process, you'll be equipped to design custom ETL pipelines. Next, you'll get to grips with the steps in the ETL process, which involves extracting valuable data; performing transformations, through cleaning, manipulation, and ensuring data integrity; and ultimately loading the processed data into storage systems. You’ll also review several ETL modules in Python, comparing their pros and cons when building data pipelines and leveraging cloud tools, such as AWS, to create scalable data pipelines. Lastly, you’ll learn about the concept of test-driven development for ETL pipelines to ensure safe deployments.By the end of this book, you’ll have worked on several hands-on examples to create high-performance ETL pipelines to develop robust, scalable, and resilient environments using Python.
Michael Olafusi, Olanrewaju Oyinbooke
M365 Excel is a modern Excel version that is constantly updated with features that make creating and automating analyses, reports, and dashboards very easy compared with older Excel versions. This book will help you leverage its full capabilities, beginning with a quick overview of what dashboards are and how they are different from other types of reports. Then, you’ll familiarize yourself with the different standard dashboards currently available and what they are meant to accomplish for organizations. As you progress, you’ll get to grips with the use of new powerful tools such as Power Query and dynamic array formulae in the automation of analysis, gaining insights into the right approach to take in building effective dashboards. You’ll equip yourself with not only all the essential formulae, charts, and non-chart visuals but also learn how to set up your dashboard perfectly. Along the way, you’ll build a couple of awesome dashboards from scratch to utilize your newfound knowledge.By the end of this book, you will be able to carry out an impressive and robust level of analysis on business data that may come from multiple sources or files, using better processes, formulae, and best practices in M365 to create insightful dashboards faster.
Willi Richert , Luis Pedro Coelho
Machine learning, the field of building systems that learn from data, is exploding on the Web and elsewhere. Python is a wonderful language in which to develop machine learning applications. As a dynamic language, it allows for fast exploration and experimentation and an increasing number of machine learning libraries are developed for Python.Building Machine Learning system with Python shows you exactly how to find patterns through raw data. The book starts by brushing up on your Python ML knowledge and introducing libraries, and then moves on to more serious projects on datasets, Modelling, Recommendations, improving recommendations through examples and sailing through sound and image processing in detail. Using open-source tools and libraries, readers will learn how to apply methods to text, images, and sounds. You will also learn how to evaluate, compare, and choose machine learning techniques. Written for Python programmers, Building Machine Learning Systems with Python teaches you how to use open-source libraries to solve real problems with machine learning. The book is based on real-world examples that the user can build on.Readers will learn how to write programs that classify the quality of StackOverflow answers or whether a music file is Jazz or Metal. They will learn regression, which is demonstrated on how to recommend movies to users. Advanced topics such as topic modeling (finding a text's most important topics), basket analysis, and cloud computing are covered as well as many other interesting aspects.Building Machine Learning Systems with Python will give you the tools and understanding required to build your own systems, which are tailored to solve your problems.
Mark Lewin, Eric Pimpler
The ArcGIS API for JavaScript enables you to quickly build web and mobile mapping applications that include sophisticated GIS capabilities, yet are easy and intuitive for the user.Aimed at both new and experienced web developers, this practical guide gives you everything you need to get started with the API. After a brief introduction to HTML/CSS/JavaScript, you'll embed maps in a web page, add the tiled, dynamic, and streaming data layers that your users will interact with, and mark up the map with graphics. You will learn how to quickly incorporate a broad range of useful user interface elements and GIS functionality to your application with minimal effort using prebuilt widgets. As the book progresses, you will discover and use the task framework to query layers with spatial and attribute criteria, search for and identify features on the map, geocode addresses, perform network analysis and routing, and add custom geoprocessing operations. Along the way, we cover exciting new features such as the client-side geometry engine, learn how to integrate content from ArcGIS.com, and use your new skills to build mobile web mapping applications.We conclude with a look at version 4 of the ArcGIS API for JavaScript (which is being developed in parallel with version 3.x) and what it means for you as a developer.
Davide Moraschi
Business intelligence is becoming more important by the day, with cloud offerings and mobile devices gaining wider acceptance and achieving better market penetration. MicroStrategy Reporting Suite is a complete business intelligence platform that covers all the data analysis needs of an enterprise. Scorecards, dashboards, and reports can be explored and delivered on desktop, the Web, mobile devices, and the Cloud. With the latest Visual Insight tool, MicroStrategy brings the power of BI to the business users, allowing them to discover information without the help of IT personnel.Business Intelligence with MicroStrategy Cookbook covers the full cycle of a BI project with the MicroStrategy platform, from setting up the software to using dashboards in the cloud and on mobile devices. This book uses step-by-step instructions to teach you everything from the very basics to the more advanced topics. We will start by downloading and installing the software and a well-known sample SQL Server database. Then, one brick at a time, we will construct a fully-featured BI solution with a web interface, mobile reporting, and agile analytics.The chapters are ordered by increasing difficulty, and each one builds on top of the preceding chapter so that the learning process is progressive. The examples given in this book are practical, and you will be able to see the immediate result of your efforts. We will first cover setting up the platform, including the creation of the metadata and the different objects that are part of a BI project: tables, attributes, and metrics. Then, we take a look at how to create and analyze reports, charts, documents, and dashboards, as well as how to manipulate data with the desktop application, the web Interface, and an iPad device.The last part of the book is dedicated to advanced topics like the new agile analytics technology from MicroStrategy, where we cover both Visual Insight and MicroStrategy Cloud Express. Whether you are a database developer, data analyst, or a business user, Business Intelligence with MicroStrategy Cookbook will get you up to speed with one of the most powerful BI platforms on the market with the smallest possible investment of time and money.
David Mertz
Data cleaning is the all-important first step to successful data science, data analysis, and machine learning. If you work with any kind of data, this book is your go-to resource, arming you with the insights and heuristics experienced data scientists had to learn the hard way.In a light-hearted and engaging exploration of different tools, techniques, and datasets real and fictitious, Python veteran David Mertz teaches you the ins and outs of data preparation and the essential questions you should be asking of every piece of data you work with.Using a mixture of Python, R, and common command-line tools, Cleaning Data for Effective Data Science follows the data cleaning pipeline from start to end, focusing on helping you understand the principles underlying each step of the process. You'll look at data ingestion of a vast range of tabular, hierarchical, and other data formats, impute missing values, detect unreliable data and statistical anomalies, and generate synthetic features. The long-form exercises at the end of each chapter let you get hands-on with the skills you've acquired along the way, also providing a valuable resource for academic courses.
MrExcel's Holy Macro! Books, Oz du Soleil
This book provides a step-by-step guide to using Power Query in Excel for efficient data cleaning and transformation. Starting with an introduction to its capabilities, it explains how to import data, handle missing values, and parse text fields with ease.Advanced techniques such as merging datasets, appending data, and performing joins are explored in detail. The book also covers grouping data, creating conditional and custom columns, and reshaping data through unpivoting for analysis. Each concept is illustrated with practical examples for clarity.By the end of the book, readers will be equipped with the skills to automate repetitive tasks and streamline workflows. Whether dealing with messy data or preparing datasets for analysis, this guide ensures you can confidently tackle any Excel data transformation challenge.
Eric Richard Rochester
This book is for those with a basic knowledge of Clojure, who are looking to push the language to excel with data analysis.
Clojure for Data Science. Statistics, big data, and machine learning for Clojure programmers
Henry Garner
The term “data science” has been widely used to define this new profession that is expected to interpret vast datasets and translate them to improved decision-making and performance. Clojure is a powerful language that combines the interactivity of a scripting language with the speed of a compiled language. Together with its rich ecosystem of native libraries and an extremely simple and consistent functional approach to data manipulation, which maps closely to mathematical formula, it is an ideal, practical, and flexible language to meet a data scientist’s diverse needs.Taking you on a journey from simple summary statistics to sophisticated machine learning algorithms, this book shows how the Clojure programming language can be used to derive insights from data. Data scientists often forge a novel path, and you’ll see how to make use of Clojure’s Java interoperability capabilities to access libraries such as Mahout and Mllib for which Clojure wrappers don’t yet exist. Even seasoned Clojure developers will develop a deeper appreciation for their language’s flexibility!You’ll learn how to apply statistical thinking to your own data and use Clojure to explore, analyze, and visualize it in a technically and statistically robust way. You can also use Incanter for local data processing and ClojureScript to present interactive visualisations and understand how distributed platforms such as Hadoop sand Spark’s MapReduce and GraphX’s BSP solve the challenges of data analysis at scale, and how to explain algorithms using those programming models.Above all, by following the explanations in this book, you’ll learn not just how to be effective using the current state-of-the-art methods in data science, but why such methods work so that you can continue to be productive as the field evolves into the future.
Sanket Thodge
With the ongoing data explosion, more and more organizations all over the world are slowly migrating their infrastructure to the cloud. These cloud platforms also provide their distinct analytics services to help you get faster insights from your data. This book will give you an introduction to the concept of analytics on the cloud, and the different cloud services popularly used for processing and analyzing data. If you’re planning to adopt the cloud analytics model for your business, this book will help you understand the design and business considerations to be kept in mind, and choose the best tools and alternatives for analytics, based on your requirements. The chapters in this book will take you through the 70+ services available in Google Cloud Platform and their implementation for practical purposes. From ingestion to processing your data, this book contains best practices on building an end-to-end analytics pipeline on the cloud by leveraging popular concepts such as machine learning and deep learning.By the end of this book, you will have a better understanding of cloud analytics as a concept as well as a practical know-how of its implementation
Kathrin Melcher, Rosaria Silipo
KNIME Analytics Platform is an open source software used to create and design data science workflows. This book is a comprehensive guide to the KNIME GUI and KNIME deep learning integration, helping you build neural network models without writing any code. It’ll guide you in building simple and complex neural networks through practical and creative solutions for solving real-world data problems.Starting with an introduction to KNIME Analytics Platform, you’ll get an overview of simple feed-forward networks for solving simple classification problems on relatively small datasets. You’ll then move on to build, train, test, and deploy more complex networks, such as autoencoders, recurrent neural networks (RNNs), long short-term memory (LSTM), and convolutional neural networks (CNNs). In each chapter, depending on the network and use case, you’ll learn how to prepare data, encode incoming data, and apply best practices.By the end of this book, you’ll have learned how to design a variety of different neural architectures and will be able to train, test, and deploy the final network.
Cameron Dodd
The CompTIA Data+ certification exam not only helps validate a skill set required to enter one of the fastest-growing fields in the world, but also is starting to standardize the language and concepts within the field. However, there’s a lot of conflicting information and a lack of existing resources about the topics covered in this exam, and even professionals working in data analytics may need a study guide to help them pass on their first attempt.The CompTIA Data + (DAO-001) Certification Guide will give you a solid understanding of how to prepare, analyze, and report data for better insights.You’ll get an introduction to Data+ certification exam format to begin with, and then quickly dive into preparing data. You'll learn about collecting, cleaning, and processing data along with data wrangling and manipulation. As you progress, you’ll cover data analysis topics such as types of analysis, common techniques, hypothesis techniques, and statistical analysis, before tackling data reporting, common visualizations, and data governance. All the knowledge you've gained throughout the book will be tested with the mock tests that appear in the final chapters.By the end of this book, you’ll be ready to pass the Data+ exam with confidence and take the next step in your career.
Ian Neil
CompTIA Security+ is a core security certification that will validate your baseline skills for a career in cybersecurity. Passing this exam will not only help you identify security incidents but will also equip you to resolve them efficiently. This book builds on the popular CompTIA Security+ Certification Guide, which mirrors the SY0-501 exam pattern.This practice test-based guide covers all six domains of the Security+ SY0-501 exam: threats, attacks, and vulnerabilities; technologies and tools; architecture and design; identity and access management; cryptography and PKI; and risk management. You’ll take six mock tests designed as per the official Security+ certification exam pattern, each covering significant aspects from an examination point of view. For each domain, the book provides a dedicated cheat sheet that includes important concepts covered in the test. You can even time your tests to simulate the actual exam. These tests will help you identify gaps in your knowledge and discover answers to tricky exam questions.By the end of this book, you’ll have developed and enhanced the skills necessary to pass the official CompTIA Security+ exam.
Continuing Financial Modelling. Advanced Techniques and Insights for Modern Financial Modelling
MrExcel's Holy Macro! Books, Liam Bastick
This book provides a thorough exploration of advanced financial modeling techniques, designed to elevate the skills of finance professionals. Starting with a recap of essential concepts, it progresses into dynamic 'What-If?' analysis, advanced forecasting methods, and inventory modeling. The focus is on practical applications, ensuring readers can implement the techniques immediately.Topics such as capital expenditure, debt calculations, and valuation are covered in detail, including DCF and MIRR analysis. The book emphasizes accuracy and efficiency in financial models, offering insights into refining forecasts and linking complex models. With a focus on sensitivity analysis and scenario planning, readers gain tools to handle real-world financial challenges.The final chapters delve into advanced Excel functions like XLOOKUP, dynamic arrays, and scenario-building tools. Best practices for maintaining model accuracy, reducing file sizes, and creating professional models are thoroughly discussed. This guide equips readers with the expertise to manage complex financial modeling tasks confidently.
Alex Büchner
Moodle Workplace is a comprehensive extension to Standard Moodle, the world's most used learning management system (LMS) platform, empowering millions of learners worldwide. Moodle Workplace is suitable for businesses and organizations, from small enterprises to global corporations.Corporate Learning with Moodle Workplace is a comprehensive introduction to this latest product from Moodle, which facilitates collaborative learning in enterprises and larger teams. Complete with detailed descriptions, a variety of diagrams, and real working examples, this easy-to-follow guide will teach you everything you need to know to manage a Moodle Workplace system. You’ll learn how to manage your users along reporting lines and organize them in to tenants, organizations, positions, job assignments, and teams, before setting up typical HR processes such as induction, compliance, and reporting. Filled with real-world examples, the book covers blended and offline scenarios, including appointments and the Moodle Workplace mobile app.By the end of this Moodle book, you’ll have learned how to fully manage a Moodle Workplace instance.
Kedeisha Bryan, Taamir Ransome
Preparing for a data engineering interview can often get overwhelming due to the abundance of tools and technologies, leaving you struggling to prioritize which ones to focus on. This hands-on guide provides you with the essential foundational and advanced knowledge needed to simplify your learning journey.The book begins by helping you gain a clear understanding of the nature of data engineering and how it differs from organization to organization. As you progress through the chapters, you’ll receive expert advice, practical tips, and real-world insights on everything from creating a resume and cover letter to networking and negotiating your salary. The chapters also offer refresher training on data engineering essentials, including data modeling, database architecture, ETL processes, data warehousing, cloud computing, big data, and machine learning. As you advance, you’ll gain a holistic view by exploring continuous integration/continuous development (CI/CD), data security, and privacy. Finally, the book will help you practice case studies, mock interviews, as well as behavioral questions.By the end of this book, you will have a clear understanding of what is required to succeed in an interview for a data engineering role.
Julian Villafuerte
QlikView is one of the most powerful analytical tools in the market. Based on an in-memory associative model, it lets users freely navigate through the data, spot trends and make better decisions. This platform is capable of integrating a wide range of data sources like ERP systems, data warehouses or spreadsheets into a single application in order display dashboards with state-of-the-art visualizations.Creating Stunning Dashboards with QlikView is an easy to follow handbook that guides you through the process of creating an effective and engaging dashboard that delivers tangible value to the business. It starts with the identification of the business needs and the definition of the main KPIs, and takes you all the way to the application rollout.Throughout the book, you will learn how to apply some of the best practices in the field of data visualization, create a robust navigation schema, chose the best chart types for each scenario and many other things that will help you create effective dashboards that uncover all the stories behind the data.