OpenGL Data Visualization Cookbook. Over 35 hands-on recipes to create impressive, stunning visuals for a wide range of real-time, interactive applications using OpenGL

William Lo, Raymond Chun Hing Lo

OpenGL is a great multi-platform, cross-language, and hardware-accelerated graphics interface for visualizing large 2D and 3D datasets. Data visualization has become increasingly challenging using conventional approaches as datasets become larger and larger, especially with the Big Data evolution. From a mobile device to a sophisticated high-performance computing cluster, OpenGL libraries provide developers with an easy-to-use interface to create stunning visuals in 3D in real time for a wide range of interactive applications.This book provides a series of easy-to-follow, hands-on tutorials to create appealing OpenGL-based visualization tools with minimal development time. We will first illustrate how to quickly set up the development environment in Windows, Mac OS X, and Linux. Next, we will demonstrate how to visualize data for a wide range of applications using OpenGL, starting from simple 2D datasets to increasingly complex 3D datasets with more advanced techniques. Each chapter addresses different visualization problems encountered in real life and introduces the relevant OpenGL features and libraries in a modular fashion.By the end of this book, you will be equipped with the essential skills to develop a wide range of impressive OpenGL-based applications for your unique data visualization needs, on platforms ranging from conventional computers to the latest mobile/wearable devices.

OpenStack Sahara Essentials. Integrate, deploy, rapidly configure, and successfully manage your own big data-intensive clusters in the cloud using OpenStack Sahara

Omar Khedher

The Sahara project is a module that aims to simplify the building of data processing capabilities on OpenStack.The goal of this book is to provide a focused, fast paced guide to installing, configuring, and getting started with integrating Hadoop with OpenStack, using Sahara.The book should explain to users how to deploy their data-intensive Hadoop and Spark clusters on top of OpenStack. It will also cover how to use the Sahara REST API, how to develop applications for Elastic Data Processing on Openstack, and setting up hadoop or spark clusters on Openstack.

Optimizing Databricks Workloads. Harness the power of Apache Spark in Azure and maximize the performance of modern big data workloads

Anirudh Kala, Anshul Bhatnagar, Sarthak Sarbahi

Databricks is an industry-leading, cloud-based platform for data analytics, data science, and data engineering supporting thousands of organizations across the world in their data journey. It is a fast, easy, and collaborative Apache Spark-based big data analytics platform for data science and data engineering in the cloud.In Optimizing Databricks Workloads, you will get started with a brief introduction to Azure Databricks and quickly begin to understand the important optimization techniques. The book covers how to select the optimal Spark cluster configuration for running big data processing and workloads in Databricks, some very useful optimization techniques for Spark DataFrames, best practices for optimizing Delta Lake, and techniques to optimize Spark jobs through Spark core. It contains an opportunity to learn about some of the real-world scenarios where optimizing workloads in Databricks has helped organizations increase performance and save costs across various domains.By the end of this book, you will be prepared with the necessary toolkit to speed up your Spark jobs and process your data more efficiently.

Optimizing Hadoop for MapReduce. This book is the perfect introduction to sophisticated concepts in MapReduce and will ensure you have the knowledge to optimize job performance. This is not an academic treatise; it’s an example-driven tutorial for the real world

Khaled Tannir

Oracle Database 12c Backup and Recovery Survival Guide. A comprehensive guide for every DBA to learn recovery and backup solutions

Francisco Munoz Alvarez, Aman Sharma

The three main responsibilities of a successful DBA are to ensure the availability, recoverability, and performance of any database. To ensure the recoverability of any database, a DBA needs to have a strong backup and recovery skills set. Every DBA is always looking for a reference book that will help them to solve any possible backup and recovery situation that they can come across in their professional life.Oracle Database 12c Backup and Recovery Survival Guide has the unique advantage to be a reference to all Oracle backup and recovery options available, making it essential for any DBA in the world. If you are new to Oracle Database, this book will introduce you to the fantastic world of backup and recovery that is vital to your success. If you are an experienced DBA, this book will become a reference guide and will also help you to learn some possible new skills, or give you some new ideas you were never aware about. It will also help you to easily find the solution to some of the most well known problems you could find during your career as a DBA. This book contains useful screenshots, scripts, and examples that you will find more than useful.Most of the books currently available in the market concentrate only on the RMAN utility to backup and recovery. This book will be an exception to the rule and will become a must-have reference, allowing you to design a real and complete backup and recovery strategy. It covers the most important topics on Oracle database such as backup strategies, Nologging operations, new features in 12c, user managed backups and recoveries, RMAN (including reporting, catalog management, troubleshooting, and performance tuning), advanced data pump, Oracle Enterprise Manager 12c and SQL Developer.Oracle Database 12c Backup and Recovery Survival Guide contains everything a DBA needs to know to keep data safe and recoverable, using real-life scenarios.

Pandas Basics. Mastering Data Analysis with Pandas

Mercury Learning and Information, Oswald Campesato

This book is essential for aspiring data scientists and anyone needing to perform data cleaning using Pandas and NumPy. It offers numerous code samples and comprehensive coverage of NumPy and Pandas features, including writing regular expressions. Chapter 3 introduces fundamental statistical concepts, while Chapter 7 delves into data visualization using Matplotlib and Seaborn. Companion files with code are available for download from the publisher.Starting with an introduction to Python, the course progresses through working with data, and then moves into Pandas, covering its functionalities in three detailed chapters. The statistical concepts provided are crucial for analyzing data effectively, while the visualization techniques enhance the ability to present data insights clearly.By the end of this course, users will have a solid foundation in data manipulation and cleaning, statistical analysis, and data visualization, enabling them to tackle real-world data science tasks confidently and efficiently.

Pandas Cookbook. Practical recipes for scientific computing, time series, and exploratory data analysis using Python - Third Edition

William Ayd, Matthew Harrison, Wes McKinney

The pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands as one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through situations that you are highly likely to encounter.With this latest edition unlock the full potential of pandas 2.x onwards. Whether you're a beginner or an experienced data analyst, this book offers a wealth of practical recipes to help you excel in your data analysis projects. This cookbook covers everything from fundamental data manipulation tasks to advanced techniques for handling big data, visualization, and more. Each recipe is designed to address common real-world challenges, providing clear explanations and step-by-step instructions to guide you through the process.Explore cutting-edge topics such as idiomatic pandas coding, efficient handling of large datasets, and advanced data visualization techniques.  Whether you're looking to sharpen or expand your skills, the Pandas Cookbook is your essential companion for mastering data analysis and manipulation with pandas 2.x, and beyond.

Pandas Cookbook. Recipes for Scientific Computing, Time Series Analysis and Data Visualization using Python

Theodore Petrou

This book will provide you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas 0.20. Some recipes focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes will dive deep into a particular dataset, uncovering new and unexpected insights along the way.The pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands like one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through practical situations that you are highly likely to encounter.Many advanced recipes combine several different features across the pandas 0.20 library to generate results.

Pentaho 8 Reporting for Java Developers. Create pixel-perfect analytical reports using reporting tools

Francesco Corti

This hands-on tutorial, filled with exercises and examples, introduces the reader to a variety of concepts within Pentaho Reporting. With screenshots that show you how reports look at design time as well as how they should look when rendered as PDF, Excel, HTML, Text, Rich-Text-File, XML, and CSV, this book also contains complete example source code that you can copy and paste into your environment to get up-and-running quickly. Updated to cover the features of Pentaho 8, this book will teach you everything you need to know to build fast, efficient reports using Pentaho. If your interest lies in the technical details of creating reports and you want to see how to solve common reporting problems with a minimum of fuss, this is the book for you.

Pentaho Data Integration Beginner's Guide. Get up and running with the Pentaho Data Integration tool using this hands-on, easy-to-read guide with this book and ebook - Second Edition

María Carina Roldán

Capturing, manipulating, cleansing, transferring, and loading data effectively are the prime requirements in every IT organization. Achieving these tasks require people devoted to developing extensive software programs, or investing in ETL or data integration tools that can simplify this work.Pentaho Data Integration is a full-featured open source ETL solution that allows you to meet these requirements. Pentaho Data Integration has an intuitive, graphical, drag-and-drop design environment and its ETL capabilities are powerful. However, getting started with Pentaho Data Integration can be difficult or confusing.Pentaho Data Integration Beginner's Guide - Second Edition provides the guidance needed to overcome that difficulty, covering all the possible key features of Pentaho Data Integration.Pentaho Data Integration Beginner's Guide - Second Edition starts with the installation of Pentaho Data Integration software and then moves on to cover all the key Pentaho Data Integration concepts. Each chapter introduces new features, allowing you to gradually get involved with the tool. First, you will learn to do all kinds of data manipulation and work with plain files. Then, the book gives you a primer on databases and teaches you how to work with databases inside Pentaho Data Integration. Moreover, you will be introduced to data warehouse concepts and you will learn how to load data in a data warehouse. After that, you will learn to implement simple and complex processes. Finally, you will have the opportunity of applying and reinforcing all the learned concepts through the implementation of a simple datamart.With Pentaho Data Integration Beginner's Guide - Second Edition, you will learn everything you need to know in order to meet your data manipulation requirements.

Pentaho Data Integration Quick Start Guide. Create ETL processes using Pentaho

María Carina Roldán

Pentaho Data Integration(PDI) is an intuitive and graphical environment packed with drag and drop design and powerful Extract-Transform-Load (ETL) capabilities. Given its power and flexibility, initial attempts to use the Pentaho Data Integration tool can be difficult or confusing. This book is the ideal solution.This book reduces your learning curve with PDI. It provides the guidance needed to make you productive, covering the main features of Pentaho Data Integration. It demonstrates the interactive features of the graphical designer, and takes you through the main ETL capabilities that the tool offers.By the end of the book, you will be able to use PDI for extracting, transforming, and loading the types of data you encounter on a daily basis.

Pig Design Patterns. Simplify Hadoop programming to create complex end-to-end Enterprise Big Data solutions with Pig

Pradeep Pasupuleti

Podstawy wizualizacji danych. Zasady tworzenia atrakcyjnych wykresów

Claus O. Wilke

Aby skutecznie przekazać wiedzę płynącą z zebranych danych, szczególnie w przypadku nauk przyrodniczych, ekonomicznych i społecznych, warto sięgnąć po narzędzia do wizualizacji. Nie jest to trywialne zadanie: często trzeba korzystać z coraz większych i coraz bardziej złożonych zbiorów danych, a dostępne narzędzia do wizualizacji zapewniają oszałamiający wybór rozwiązań i opcji, w których łatwo się pogubić. Co więcej, podczas przygotowywania prezentacji należy wziąć pod uwagę szczególne właściwości ludzkiego umysłu w zakresie postrzegania i przyswajania informacji. Efektywna wizualizacja danych jest bardzo istotną sprawą: nierzadko od jakości przekazywanych w ten sposób informacji zależy trafność podejmowanych decyzji. Ten poradnik pomoże Ci uniknąć często spotykanych problemów z wizualizacją danych. Zawiera wskazówki, dzięki którym szybko zaczniesz tworzyć świetnie wyglądające i bogate w treść wykresy. Nauczysz się bezbłędnego dobierania najlepszego w danej sytuacji sposobu wizualizacji, poznasz reguły stosowania kolorów, wielkości i rodzaju czcionki, zachowywania odpowiednich proporcji poszczególnych części wykresu — i przekonasz się, że dobrymi decyzjami co do jego estetyki możesz zapewnić mu przejrzystość i elegancję. Znajdziesz tu również obszerny katalog wizualizacji, co ułatwi zapoznanie się z powszechnie używanymi metodami wizualizowania danych. Ważną częścią książki jest zestaw przykładów dobrze i źle przygotowanych wykresów z wyczerpującymi wyjaśnieniami. Najciekawsze koncepcje opisane w książce: kolor jako cenne narzędzie wyróżniania danych dostarczanie kluczowych informacji na wiele sposobów dobór technik wizualizacji do różnych rodzajów danych reguły pomocne w projektowaniu estetycznych wykresów technika stosowania wykresów w większym dokumencie A więc jak wygląda wykres, który decyduje o sukcesie prezentacji?

Polars Cookbook. Over 60 practical recipes to transform, manipulate, and analyze your data using Python Polars 1.x

Yuki Kakegawa, Marco Gorelli

The Polars Cookbook is a comprehensive, hands-on guide to Python Polars, one of the first resources dedicated to this powerful data processing library. Written by Yuki Kakegawa, a seasoned data analytics consultant who has worked with industry leaders like Microsoft and Stanford Health Care, this book offers targeted, real-world solutions to data processing, manipulation, and analysis challenges. The book also includes a foreword by Marco Gorelli, a core contributor to Polars, ensuring expert insights into Polars' applications. From installation to advanced data operations, you’ll be guided through data manipulation, advanced querying, and performance optimization techniques. You’ll learn to work with large datasets, conduct sophisticated transformations, leverage powerful features like chaining, and understand its caveats. This book also shows you how to integrate Polars with other Python libraries such as pandas, numpy, and PyArrow, and explore deployment strategies for both on-premises and cloud environments like AWS, BigQuery, GCS, Snowflake, and S3. With use cases spanning data engineering, time series analysis, statistical analysis, and machine learning, Polars Cookbook provides essential techniques for optimizing and securing your workflows. By the end of this book, you'll possess the skills to design scalable, efficient, and reliable data processing solutions with Polars.

PostgreSQL 11 Server Side Programming Quick Start Guide. Effective database programming and interaction

Luca Ferrari

PostgreSQL is a rock-solid, scalable, and safe enterprise-level relational database. With a broad range of features and stability, it is ever increasing in popularity.This book shows you how to take advantage of PostgreSQL 11 features for server-side programming. Server-side programming enables strong data encapsulation and coherence.The book begins with the importance of server-side programming and explains the risks of leaving all the checks outside the database. To build your capabilities further, you will learn how to write stored procedures, both functions and the new PostgreSQL 11 procedures, and create triggers to perform encapsulation and maintain data consistency.You will also learn how to produce extensions, the easiest way to package your programs for easy and solid deployment on different PostgreSQL installations.

PostgreSQL High Performance Cookbook. Mastering query optimization, database monitoring, and performance-tuning for PostgreSQL

Chitij Chauhan, Dinesh Kumar

PostgreSQL is one of the most powerful and easy to use database management systems. It has strong support from the community and is being actively developed with a new release every year. PostgreSQL supports the most advanced features included in SQL standards. It also provides NoSQL capabilities and very rich data types and extensions. All of this makes PostgreSQL a very attractive solution in software systems.If you run a database, you want it to perform well and you want to be able to secure it. As the world’s most advanced open source database, PostgreSQL has unique built-in ways to achieve these goals. This book will show you a multitude of ways to enhance your database’s performance and give you insights into measuring and optimizing a PostgreSQL database to achieve better performance. This book is your one-stop guide to elevate your PostgreSQL knowledge to the next level. First, you’ll get familiarized with essential developer/administrator concepts such as load balancing, connection pooling, and distributing connections to multiple nodes. Next, you will explore memory optimization techniques before exploring the security controls offered by PostgreSQL. Then, you will move on to the essential database/server monitoring and replication strategies with PostgreSQL. Finally, you will learn about query processing algorithms.

Potoki danych. Leksykon kieszonkowy. Przenoszenie i przetwarzanie danych na potrzeby ich analizy

James Densmore

Poprawnie zaprojektowane i wdrożone potoki danych mają kluczowe znaczenie dla pomyślnej analizy danych, a także w trakcie uczenia maszynowego. Pozyskanie ogromnych ilości danych z różnych źródeł najczęściej nie stanowi problemu. Nieco trudniejsze jest zaprojektowanie procesu ich przetwarzania w celu dostarczenia kontekstu w taki sposób, aby efektywnie korzystać z posiadanych danych w codziennej pracy organizacji i podejmować dzięki nim rozsądne decyzje. Oto zwięzły przewodnik przeznaczony dla inżynierów danych, którzy chcą poznać zasady implementacji potoków danych. Wyjaśnia najważniejsze pojęcia związane z potokami danych, opisuje zasady ich tworzenia i implementacji, prezentuje także najlepsze praktyki stosowane przez liderów w branży analizy danych. Dzięki książce zrozumiesz, w jaki sposób potoki danych działają na nowoczesnym stosie danych, poznasz też typowe zagadnienia, które trzeba przemyśleć przed podjęciem decyzji dotyczących implementacji. Dowiesz się, jakie są zalety samodzielnego opracowania rozwiązania, a jakie - zakupu gotowego produktu. Poznasz również podstawowe koncepcje, które mają zastosowanie dla frameworków typu open source, produktów komercyjnych i samodzielnie opracowywanych rozwiązań. Dowiedz się: czym jest potok danych i na czym polega jego działanie jak się odbywa przenoszenie i przetwarzanie danych w nowoczesnej infrastrukturze jakie narzędzia są szczególnie przydatne do tworzenia potoków danych jak używać potoków danych do analizy i tworzenia raportów jakie są najważniejsze aspekty obsługi potoków, ich testowania i rozwiązywania problemów Poznaj najlepsze praktyki projektowania i implementacji potoków danych!

Power BI i Power Pivot dla Excela. Analiza danych

Alberto Ferrari, Marco Russo

Profesjonalne modelowanie danych — pewny sukces w biznesie! Możliwości Excela są imponujące, a odkąd Microsoft udostępnił narzędzia w rodzaju Analysis Services, Power BI czy Power Pivot, arkusz ten stał się znakomitym narzędziem do analizy, modelowania oraz innych form przetwarzania dużych i złożonych zbiorów danych. Są to umiejętności, które przydadzą się w wielu dziedzinach życia, nie tylko w biznesie. Ich opanowanie nie jest zbyt trudne, a może stać się źródłem wielkiej radości i prawdziwej satysfakcji zwłaszcza dla każdego, kto lubi pracować z liczbami. Oczywiście osoby, które osiągną wysoki poziom umiejętności w tym zakresie, będą mogły liczyć na bardzo konkretne profity! Ta książka jest świetnym wprowadzeniem do modelowania danych w Excelu za pomocą narzędzi Power BI i Power Pivot. Dowiesz się z niej, jak optymalnie analizować zgromadzone dane i skutecznie wydobyć z nich potrzebne informacje. Zapoznasz się z ważnymi pojęciami i przyswoisz podstawowe techniki kształtowania modeli danych w Excelu i Power BI. Dzięki licznym praktycznym i przydatnym przykładom uzyskasz nową perspektywę — spojrzysz na zgromadzone dane okiem wytrawnego modelarza. Co więcej, szybko się przekonasz, że należyte zbudowanie modelu wcale nie jest trudne, a w efekcie przynosi prawidłowe odpowiedzi na wiele ważnych pytań! W tej książce między innymi: zasady i popularne techniki modelowania danych tabele faktów w złożonym modelu danych metody śledzenia atrybutów historycznych migawki i ich zastosowania analiza zdarzeń o określonym czasie trwania dobieranie rodzaju modelu do konkretnych pytań biznesowych Alberto Ferrari i Marco Russo od dwóch dekad zajmują się procesami business intelligence i Analysis Services. Obaj posiadają tytuły Microsoft MVP i SSAS Maestro. Często występują na prestiżowych konferencjach. Ferrari jest autorytetem w dziedzinie modelowania danych oraz usług analitycznych w dużych i złożonych hurtowniach danych, Russo specjalizuje się w analizie danych dla potrzeb wywiadu gospodarczego.

Power Excel with MrExcel. Master Pivot Tables, Subtotals, VLOOKUP, Power Query, Dynamic Arrays & Data Analysis

MrExcel's Holy Macro! Books, Bill Jelen

Excel 2019 is more than just a spreadsheet tool; it's a powerful platform for solving complex data challenges. In this guide, MrExcel takes you through the essentials of Excel 2019, incorporating the latest features from Office 365. You'll start by mastering the Excel interface before moving on to advanced calculation techniques that streamline your workflow. The guide emphasizes data wrangling, teaching you how to transform raw data into meaningful insights with ease.Beyond calculations, you'll learn to create visually appealing spreadsheets that communicate your data effectively. MrExcel's approach combines problem-solving strategies with real-world scenarios, ensuring you gain practical skills that apply directly to your work. Reader-sourced tips and solutions to common user pitfalls are integrated throughout the guide, offering a personalized learning experience.By the end of this book, you'll have a solid understanding of Excel 2019's capabilities, enabling you to work faster, make informed decisions, and present your data professionally. Whether you're looking to enhance your existing skills or learn new techniques, MrExcel's expert guidance will help you master Excel and elevate your data analysis game.

Power Query Cookbook. Use effective and powerful queries in Power BI Desktop and Dataflows to prepare and transform your data

Andrea Janicijevic

Power Query is a data preparation tool that enables data engineers and business users to connect, reshape, enrich, and transform their data to facilitate relevant business insights and analysis. With Power Query's wide range of features, you can perform no-code transformations and complex M code functions at the same time to get the most out of your data.This Power Query book will help you to connect to data sources, achieve intuitive transformations, and get to grips with preparation practices. Starting with a general overview of Power Query and what it can do, the book advances to cover more complex topics such as M code and performance optimization. You'll learn how to extend these capabilities by gradually stepping away from the Power Query GUI and into the M programming language. Additionally, the book also shows you how to use Power Query Online within Power BI Dataflows.By the end of the book, you'll be able to leverage your source data, understand your data better, and enrich it with a full stack of no-code and custom features that you'll learn to design by yourself for your business requirements.

Poznaj Tableau 2022. Wizualizacja danych, interaktywna analiza danych i umiejętność data storytellingu. Wydanie V

Joshua N. Milligan

Dane stały się paliwem rozwoju cywilizacji. Wykorzystanie ich potencjału jest jednak trudne: problemem okazuje się wyciąganie z nich informacji i wniosków, aby można było na ich podstawie podejmować trafne decyzje. Jednym z narzędzi ułatwiających tę pracę jest Tableau - program do analityki danych, który umożliwia ich zrozumienie, interpretację i prowadzenie na nich efektywnych działań. Dzięki tej książce płynnie rozpoczniesz pracę z Tableau 2022 i nauczysz się wizualizacji danych. Dowiesz się, jak je analizować i przedstawiać w formie graficznej, a także jak opowiadać oparte na nich historie. W tym wydaniu ujęto najnowsze funkcje programu, między innymi rozszerzenia pulpitów nawigacyjnych, Explain Data i integrację z CRM Analytics (Einstein Analytics), służącym do modelowania predyktywnego w Tableau. Pokazano również, jak używać tabel i obliczeń na różnych poziomach szczegółowości i stosować wizualną analitykę statystyczną. Następnie zademonstrowano techniki łączenia różnych źródeł danych z funkcjonalnościami modeli danych Tableau wraz z mapami i wizualizacjami geoprzestrzennymi. Z tego przewodnika dowiesz się też, jak korzystać z funkcji Tableau Prep Builder, by skutecznie oczyścić i zorganizować dane. Dzięki książce nauczysz się: tworzyć zachwycające wizualizacje złożonych danych budować interaktywne pulpity nawigacyjne korzystać z obliczeń w celu rozwiązywania problemów i uzupełniania analiz wzbogacać możliwości Tableau poprzez rozszerzenia, skrypty i CRM Analytics oczyszczać i organizować dane w Tableau tworzyć angażujące historie oparte na danych Przekonaj się, co Tableau wyczaruje z Twoich danych!

Practical Big Data Analytics. Hands-on techniques to implement enterprise analytics and machine learning using Hadoop, Spark, NoSQL and R

Nataraj Dasgupta

Big Data analytics relates to the strategies used by organizations to collect, organize, and analyze large amounts of data to uncover valuable business insights that cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization’s data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages, and BI tools, selecting the right combination of technologies is an even greater challenge. This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology and the practical reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB, and even learn how to write R code for neural networks.By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using the different tools and methods articulatedin this book.

Practical Business Intelligence. Optimize Business Intelligence for Efficient Data Analysis

Ahmed Sherif

Business Intelligence (BI) is at the crux of revolutionizing enterprise. Everyone wants to minimize losses and maximize profits. Thanks to Big Data and improved methodologies to analyze data, Data Analysts and Data Scientists are increasingly using data to make informed decisions. Just knowing how to analyze data is not enough, you need to start thinking how to use data as a business asset and then perform the right analysis to build an insightful BI solution. Efficient BI strives to achieve the automation of data for ease of reporting and analysis. Through this book, you will develop the ability to think along the right lines and use more than one tool to perform analysis depending on the needs of your business. We start off by preparing you for data analytics. We then move on to teach you a range of techniques to fetch important information from various databases, which can be used to optimize your business.The book aims to provide a full end-to-end solution for an environment setup that can help you make informed business decisions and deliver efficient and automated BI solutions to any company.It is a complete guide for implementing Business intelligence with the help of the most powerful tools like D3.js, R, Tableau, Qlikview and Python that are available on the market.

Practical Computer Vision. Extract insightful information from images using TensorFlow, Keras, and OpenCV

Abhinav Dadhich

In this book, you will find several recently proposed methods in various domains of computer vision. You will start by setting up the proper Python environment to work on practical applications. This includes setting up libraries such as OpenCV, TensorFlow, and Keras using Anaconda. Using these libraries, you'll start to understand the concepts of image transformation and filtering. You will find a detailed explanation of feature detectors such as FAST and ORB; you'll use them to find similar-looking objects.With an introduction to convolutional neural nets, you will learn how to build a deep neural net using Keras and how to use it to classify the Fashion-MNIST dataset. With regard to object detection, you will learn the implementation of a simple face detector as well as the workings of complex deep-learning-based object detectors such as Faster R-CNN and SSD using TensorFlow. You'll get started with semantic segmentation using FCN models and track objects with Deep SORT. Not only this, you will also use Visual SLAM techniques such as ORB-SLAM on a standard dataset. By the end of this book, you will have a firm understanding of the different computer vision techniques and how to apply them in your applications.