Analiza danych
Hurtownie danych. Od przetwarzania analitycznego do raportowania. Wydanie II
Adam Pelikant
Idea hurtowni danych ściśle wiąże się z ich kolosalnymi ilościami, gromadzonymi podczas tysięcy różnych sytuacji - przy dowolnej transakcji, w urzędzie, na lotnisku, w internecie... Nawet nasze połączenia telefoniczne są przechowywane przez operatora. Te wszystkie dane trzeba gdzieś pomieścić, sensownie posegregować i zapewnić sobie możliwość sięgnięcia do wybranego ich zakresu bez długotrwałych poszukiwań. Taką możliwość dają właśnie hurtownie danych - przemyślane, bardzo pojemne bazy, oferujące zarówno integrację wprowadzanych danych, jak i znakomite mechanizmy ich przeszukiwania. Jeśli chcesz poszerzyć swoją wiedzę na temat tworzenia i przeglądania zawartości hurtowni danych, trafiłeś pod właściwy adres! Książka Hurtownie danych. Od przetwarzania analitycznego do raportowania zawiera materiał przeznaczony nie tylko dla studentów wydziałów informatycznych, ale także dla pasjonatów tej tematyki oraz specjalistów zainteresowanych poszerzeniem wiedzy. W możliwie najprostszy, praktyczny sposób opisano w niej składnię i postać zapytań analitycznych, strukturę hurtowni danych oraz kwestię ich integracji i wizualnego tworzenia elementów hurtowni. Znajdziesz tu także omówienie analizy danych z wykorzystaniem rozszerzenia MDX SQL oraz zastosowań raportowania. Zapoznanie się z tymi informacjami oraz prześledzenie zgromadzonych tu przykładów pozwoli Ci zrozumieć problemy powstające przy budowie hurtowni danych i wykorzystać tę wiedzę we własnych projektach. Zapytania analityczne Struktura hurtowni danych Integracja danych Wizualne tworzenie elementów hurtowni danych Analiza danych z wykorzystaniem rozszerzenia MDX SQL Raportowanie
Keith McCormick, Jesus Salcedo
IBM SPSS Modeler allows users to quickly and efficiently use predictive analytics and gain insights from your data. With almost 25 years of history, Modeler is the most established and comprehensive Data Mining workbench available. Since it is popular in corporate settings, widely available in university settings, and highly compatible with all the latest technologies, it is the perfect way to start your Data Science and Machine Learning journey. This book takes a detailed, step-by-step approach to introducing data mining using the de facto standard process, CRISP-DM, and Modeler’s easy to learn “visual programming” style. You will learn how to read data into Modeler, assess data quality, prepare your data for modeling, find interesting patterns and relationships within your data, and export your predictions. Using a single case study throughout, this intentionally short and focused book sticks to the essentials. The authors have drawn upon their decades of teaching thousands of new users, to choose those aspects of Modeler that you should learn first, so that you get off to a good start using proven best practices. This book provides an overview of various popular data modeling techniques and presents a detailed case study of how to use CHAID, a decision tree model. Assessing a model’s performance is as important as building it; this book will also show you how to do that. Finally, you will see how you can score new data and export your predictions. By the end of this book, you will have a firm understanding of the basics of data mining and how to effectively use Modeler to build predictive models.
Jagjeet Singh Makhija, Charles Odunukwe
The DP-600 exam tests your ability to design and implement analytics solutions using Microsoft Fabric, including planning data analytics environments, managing data integration and security, and optimizing performance. Written by two Microsoft specialists with over three decades of combined experience, this book will help you confidently prepare for the DP-600 exam by teaching you the skills that are essential for effectively implementing and designing analytics solutions.You’ll explore data analytics in Microsoft Fabric in detail and understand foundational topics such as data exploration, SQL querying, and data transformation, alongside advanced techniques such as semantic model optimization, performance tuning, and enterprise-scale model design. The book addresses strategic planning, data integration, security, scalability, and the complete project lifecycle, including version control, deployment, and continuous improvement. You’ll also get to grips with practical SQL integration with Microsoft Fabric components, with mock exams to help you reinforce what you’ve learned.By the end of this book, you’ll be able to plan, implement, and optimize analytics solutions using Microsoft Fabric, and you'll be well-equipped with the practical skills needed to tackle real-world data challenges and pass the DP-600 exam.
Andrew Bell, Francisco Arturo Viveros, Sander Rensen,...
Implementing Oracle API Platform Cloud Service moves from theory to practice using the newest Oracle API management platform. This critical new platform for Oracle developers allows you to interface the complex array of services your clients expect in the modern world.First, you'll learn about Oracle’s new platform and get an overview of it, then you'll see a use case showing the functionality and use of this new platform for Oracle customers. Next, you’ll see the power of Apiary and begin designing your own APIs. From there, you’ll build and run microservices and set up the Oracle API gateways. Moving on, you’ll discover how to customize the developer portal and publish your own APIs. You’ll spend time looking at configuration management on the new platform, and implementing the Oauth 2.0 policy, as well as custom policies. The latest finance modules from Oracle will be examined, with some of the third party alternatives in sight as well.This broad-scoped book completes your journey with a clear examination of how to transition APIs from Oracle API Management 12c to the new Oracle API Platform, so that you can step into the future confidently.
Implementing Qlik Sense. Design, Develop, and Validate BI solutions for consultants
Ganapati Hegde, Kaushik Solanki
Qlik Sense is a leading platform for business intelligence (BI) solutions. Qlik Sense helps organizations in making informed decisions based on the data they have.This book will teach you how to effectively use Qlik for optimum customer satisfaction. You will undergo a metamorphosis from a developer to a consultant who is capable of building the most suitable BI solutions for your clients. The book will take you through several business cases – this will give you enough insight to understand the needs of the client clearly and build a BI solution that meets or exceeds their expectations. Starting from the pre-project activities, you will go to the actual execution of the project, the implementation, and even maintenance. This book will give you all the information you need - from the strategy to requirement gathering to implementing BI solutions using Qlik Sense. The book will empower you to take the right decisions in tricky and diffi cult situations while developing analytics and dashboards.
James D. Miller
Splunk is the leading platform that fosters an efficient methodology and delivers ways to search, monitor, and analyze growing amounts of big data. This book will allow you to implement new services and utilize them to quickly and efficiently process machine-generated big data. We introduce you to all the new features, improvements, and offerings of Splunk 7. We cover the new modules of Splunk: Splunk Cloud and the Machine Learning Toolkit to ease data usage. Furthermore, you will learn to use search terms effectively with Boolean and grouping operators. You will learn not only how to modify your search to make your searches fast but also how to use wildcards efficiently. Later you will learn how to use stats to aggregate values, a chart to turn data, and a time chart to show values over time; you'll also work with fields and chart enhancements and learn how to create a data model with faster data model acceleration. Once this is done, you will learn about XML Dashboards, working with apps, building advanced dashboards, configuring and extending Splunk, advanced deployments, and more. Finally, we teach you how to use the Machine Learning Toolkit and best practices and tips to help you implement Splunk services effectively and efficiently. By the end of this book, you will have learned about the Splunk software as a whole and implemented Splunk services in your tasks at projects
Liyanapathirannahelage H Perera
MapReduce is a technology that enables users to process large datasets and Hadoop is an implementation of MapReduce. We are beginning to see more and more data becoming available, and this hides many insights that might hold key to success or failure. However, MapReduce has the ability to analyze this data and write code to process it.Instant MapReduce Patterns – Hadoop Essentials How-to is a concise introduction to Hadoop and programming with MapReduce. It is aimed to get you started and give you an overall feel for programming with Hadoop so that you will have a well-grounded foundation to understand and solve all of your MapReduce problems as needed.Instant MapReduce Patterns – Hadoop Essentials How-to will start with the configuration of Hadoop before moving on to writing simple examples and discussing MapReduce programming patterns.We will start simply by installing Hadoop and writing a word count program. After which, we will deal with the seven styles of MapReduce programs: analytics, set operations, cross correlation, search, graph, Joins, and clustering. For each case, you will learn the pattern and create a representative example program. The book also provides you with additional pointers to further enhance your Hadoop skills.
Interactive Applications using Matplotlib
This book is intended for Python programmers who want to do more than just see their data. Experience with GUI toolkits is not required, so this book can be an excellent complement to other GUI programming resources.
Elias Dabbas
Plotly's Dash framework is a life-saver for Python developers who want to develop complete data apps and interactive dashboards without JavaScript, but you'll need to have the right guide to make sure you’re getting the most of it. With the help of this book, you'll be able to explore the functionalities of Dash for visualizing data in different ways.Interactive Dashboards and Data Apps with Plotly and Dash will first give you an overview of the Dash ecosystem, its main packages, and the third-party packages crucial for structuring and building different parts of your apps. You'll learn how to create a basic Dash app and add different features to it.Next, you’ll integrate controls such as dropdowns, checkboxes, sliders, date pickers, and more in the app and then link them to charts and other outputs. Depending on the data you are visualizing, you'll also add several types of charts, including scatter plots, line plots, bar charts, histograms, and maps, as well as explore the options available for customizing them.By the end of this book, you'll have developed the skills you need to create and deploy an interactive dashboard, handle complexities and code refactoring, and understand the process of improving your application.
MrExcel's Holy Macro! Books, Liam Bastick
This book serves as a comprehensive guide to financial modeling, equipping readers with the skills and knowledge to create accurate, reliable models for analysis and decision-making. Designed for professionals, students, and finance enthusiasts, it bridges theoretical principles with practical Excel-based techniques, ensuring a balanced and thorough understanding of the subject.Key Excel functions such as SUMPRODUCT, INDEX and MATCH, and LOOKUP are covered in depth, alongside essential tools like conditional formatting, data validation, and solver. The book emphasizes best practices in layout design, error checking, and model transparency, helping users build robust and easy-to-follow financial models. Practical methodologies for time-series analysis, control accounts, and financial statement theory are explored, making it a versatile resource.The step-by-step model-building example guides readers through structuring, linking, and finalizing financial statements, including revenue, expenditure, taxation, and cash flow. Ratio analysis and self-review techniques are also discussed to ensure model accuracy and integrity. This detailed yet accessible guide empowers readers to create professional financial models with confidence and clarity.
Jay Gendron
Explore the world of Business Intelligence through the eyes of an analyst working in a successful and growing company. Learn R through use cases supporting different functions within that company. This book provides data-driven and analytically focused approaches to help you answer questions in operations, marketing, and finance. In Part 1, you will learn about extracting data from different sources, cleaning that data, and exploring its structure. In Part 2, you will explore predictive models and cluster analysis for Business Intelligence and analyze financial times series. Finally, in Part 3, you will learn to communicate results with sharp visualizations and interactive, web-based dashboards.After completing the use cases, you will be able to work with business data in the R programming environment and realize how data science helps make informed decisions and develops business strategy. Along the way, you will find helpful tips about R and Business Intelligence.
Inżynieria danych w praktyce. Kluczowe koncepcje i najlepsze technologie
Joe Reis, Matt Housley
Ze względu na gwałtowny rozwój inżynierii danych, jaki nastąpił w ciągu ostatniej dekady, wielu inżynierów oprogramowania, badaczy i analityków danych zaczęło odczuwać potrzebę kompleksowego spojrzenia na tę praktykę. Dzięki tej praktycznej książce zawierającej opis najlepszych technologii dostępnych w ramach frameworka cyklu życia inżynierii danych, dowiesz się, jak planować i budować systemy, które mają zaspokoić potrzeby Twojej organizacji i klientów. Autorzy, Joe Reis i Matt Housley, przeprowadzą Cię przez cykl życia inżynierii danych i pokażą, jak połączyć różne technologie chmurowe, aby spełnić potrzeby konsumentów danych w dolnej części strumienia przetwarzania. Dzięki lekturze tej książki dowiesz się, jak zastosować koncepcje generowania, pozyskiwania, orkiestracji, przekształcania, przechowywania i zarządzania danymi - kluczowe w każdym środowisku danych, niezależnie od wykorzystywanej technologii. Dzięki książce: Uzyskasz zwięzły przegląd całego środowiska inżynierii danych. Nauczysz się oceniać problemy inżynierii danych i stosować kompleksowe frameworki najlepszych praktyk. Dowiesz się jak przebić się przez szum marketingowy i wybrać odpowiednie technologie, architekturę danych i procesy? Nauczysz się wykorzystywać cykl życia inżynierii danych do zaprojektowania i zbudowania solidnej architektury. Poznasz mechanizmy zarządzania danymi i bezpieczeństwa w całym cyklu życia inżynierii danych. "Świat danych ewoluuje już od jakiegoś czasu. Najpierw byli projektanci. Następnie administratorzy baz danych. Potem CIO. Następnie architekci danych. Ta książka sygnalizuje kolejny krok w ewolucji i dojrzałości branży. Jest to lektura obowiązkowa dla każdego, kto uczciwie podchodzi do swojego zawodu i kariery". Bill Inmon, twórca hurtowni danych "Inżynieria danych w praktyce" to świetne wprowadzenie do branży przenoszenia, przetwarzania i obsługi danych. Gorąco polecam ją każdemu, kto chce być na bieżąco z inżynierią danych lub analizą oraz wszystkim osobom zajmującym się danymi, którzy chcą uzupełnić luki w swojej wiedzy". Jordan Tigani, założyciel i dyrektor generalny firmy MotherDuck oraz inżynier-założyciel i współtwórca firmy BigQuery
Cyrille Rossant
Intended to anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, hobbyists... Basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods.
Cyrille Rossant
Python is one of the leading open source platforms for data science and numerical computing. IPython and the associated Jupyter Notebook offer efficient interfaces to Python for data analysis and interactive visualization, and they constitute an ideal gateway to the platform.IPython Interactive Computing and Visualization Cookbook, Second Edition contains many ready-to-use, focused recipes for high-performance scientific computing and data analysis, from the latest IPython/Jupyter features to the most advanced tricks, to help you write better and faster code. You will apply these state-of-the-art methods to various real-world examples, illustrating topics in applied mathematics, scientific modeling, and machine learning.The first part of the book covers programming techniques: code quality and reproducibility, code optimization, high-performance computing through just-in-time compilation, parallel computing, and graphics card programming. The second part tackles data science, statistics, machine learning, signal and image processing, dynamical systems, and pure and applied mathematics.
Jak analizować dane z biblioteką Pandas. Praktyczne wprowadzenie. Wydanie II
Daniel Y. Chen
Wprawny analityk potrafi się posługiwać zbiorami danych o wysokiej dynamice i różnorodności. Działanie to ułatwia biblioteka open source Pandas, która pozwala, przy użyciu języka Python, zrealizować niemal każde zadanie wymagające analizy danych. Pandas może pomóc w zapewnieniu wiarygodności danych, wizualizowaniu ich pod kątem efektywnego podejmowania decyzji i analizowaniu wielu zbiorów danych. Oto drugie, zaktualizowane i uzupełnione wydanie przewodnika po bibliotece Pandas. Dzięki tej przystępnej książce nauczysz się w pełni korzystać z możliwości oferowanych przez bibliotekę, nawet jeśli dopiero zaczynasz przygodę z analizą danych w Pythonie. Naukę rozpoczniesz z użyciem rzeczywistego zbioru danych, aby wkrótce rozwiązywać złożone problemy danologii, takie jak obsługa brakujących danych, stosowanie regularyzacji czy też używanie metod nienadzorowanego uczenia maszynowego do odnajdywania podstawowej struktury w zbiorze danych. Pracę z poszczególnymi zagadnieniami ułatwia to, że zostały one zilustrowane prostymi, ale praktycznymi przykładami. W książce: importowanie i eksportowanie danych, przygotowywanie ich zbiorów tworzenie wykresów za pomocą bibliotek matplotlib, seaborn i Pandas konwersja typów danych skalowanie operacji przetwarzania danych zaawansowane możliwości biblioteki Pandas powiązane z datami i czasem dopasowywanie modeli liniowych przy użyciu bibliotek statsmodels i scikit-learn Analizuj zbiory danych i odkrywaj ukrytą w nich wiedzę!
Java Data Analysis. Data mining, big data analysis, NoSQL, and data visualization
John R. Hubbard
Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the aim of discovering useful information. Java is one of the most popular languages to perform your data analysis tasks.This book will help you learn the tools and techniques in Java to conduct data analysis without any hassle. After getting a quick overview of what data science is and the steps involved in the process, you’ll learn the statistical data analysis techniques and implement them using the popular Java APIs and libraries. Through practical examples, you will also learn the machine learning concepts such as classification and regression. In the process, you’ll familiarize yourself with tools such as Rapidminer and WEKA and see how these Java-based tools can be used effectively for analysis. You will also learn how to analyze text and other types of multimedia. Learn to work with relational, NoSQL, and time-series data. This book will also show you how you can utilize different Java-based libraries to create insightful and easy to understand plots and graphs.By the end of this book, you will have a solid understanding of the various data analysis techniques, and how to implement them using Java.