Codecademy Hadoop

  codecademy hadoop: Data Science from Scratch Steven Cooper, 2018-08-10 ★☆If you are looking to start a new career that is in high demand, then you need to continue reading!★☆​​​​​​​ Data scientists are changing the way big data is used in different institutions. Big data is everywhere, but without the right person to interpret it, it means nothing. So where do business find these people to help change their business? You could be that person! It has become a universal truth that businesses are full of data. With the use of big data, the US healthcare could reduce their health-care spending by $300 billion to $450 billion. It can easily be seen that the value of big data lies in the analysis and processing of that data, and that's where data science comes in. ★★ Grab your copy today and learn ★★ ♦ In depth information about what data science is and why it is important. ♦ The prerequisites you will need to get started in data science. ♦ What it means to be a data scientist. ♦ The roles that hacking and coding play in data science. ♦ The different coding languages that can be used in data science. ♦ Why python is so important. ♦ How to use linear algebra and statistics. ♦ The different applications for data science. ♦ How to work with the data through munging and cleaning ♦ And much more... The use of data science adds a lot of value to businesses, and we will continue to see the need for data scientists grow. As businesses and the internet change, so will data science. This means it's important to be flexible. When data science can reduce spending costs by billions of dollars in the healthcare industry, why wait to jump in? If you want to get started in a new, ever growing, career, don't wait any longer. Scroll up and click the buy now button to get this book today!
  codecademy hadoop: Big Data Bootcamp David Feinleib, 2014-09-26 Investors and technology gurus have called big data one of the most important trends to come along in decades. Big Data Bootcamp explains what big data is and how you can use it in your company to become one of tomorrow’s market leaders. Along the way, it explains the very latest technologies, companies, and advancements. Big data holds the keys to delivering better customer service, offering more attractive products, and unlocking innovation. That’s why, to remain competitive, every organization should become a big data company. It’s also why every manager and technology professional should become knowledgeable about big data and how it is transforming not just their own industries but the global economy. And that knowledge is just what this book delivers. It explains components of big data like Hadoop and NoSQL databases; how big data is compiled, queried, and analyzed; how to create a big data application; and the business sectors ripe for big data-inspired products and services like retail, healthcare, finance, and education. Best of all, your guide is David Feinleib, renowned entrepreneur, venture capitalist, and author of Why Startups Fail. Feinleib’s Big Data Landscape, a market map featured and explained in the book, is an industry benchmark that has been viewed more than 150,000 times and is used as a reference by VMWare, Dell, Intel, the U.S. Government Accountability Office, and many other organizations. Feinleib also explains: • Why every businessperson needs to understand the fundamentals of big data or get run over by those who do • How big data differs from traditional database management systems • How to create and run a big data project • The technical details powering the big data revolution Whether you’re a Fortune 500 executive or the proprietor of a restaurant or web design studio, Big Data Bootcamp will explain how you can take full advantage of new technologies to transform your company and your career.
  codecademy hadoop: The Medical Library Association Guide to Data Management for Librarians Lisa Federer, 2016-09-15 Technological advances and the rise of collaborative, interdisciplinary approaches have changed the practice of research. The 21st century researcher not only faces the challenge of managing increasingly complex datasets, but also new data sharing requirements from funders and journals. Success in today’s research enterprise requires an understanding of how to work effectively with data, yet most researchers have never had any formal training in data management. Libraries have begun developing services and programs to help researchers meet the demands of the data-driven research enterprise, giving librarians exciting new opportunities to use their expertise and skills. The Medical Library Association Guide to Data Management for Librarians highlights the many ways that librarians are addressing researchers’ changing needs at a variety of institutions, including academic, hospital, and government libraries. Each chapter ends with “pearls of wisdom,” a bulleted list of 5-10 takeaway messages from the chapter that will help readers quickly put the ideas from the chapter into practice. From theoretical foundations to practical applications, this book provides a background for librarians who are new to data management as well as new ideas and approaches for experienced data librarians.
  codecademy hadoop: Data Science and Digital Business Fausto Pedro García Márquez, Benjamin Lev, 2019-01-04 This book combines the analytic principles of digital business and data science with business practice and big data. The interdisciplinary, contributed volume provides an interface between the main disciplines of engineering and technology and business administration. Written for managers, engineers and researchers who want to understand big data and develop new skills that are necessary in the digital business, it not only discusses the latest research, but also presents case studies demonstrating the successful application of data in the digital business.
  codecademy hadoop: Coding All-in-One For Dummies Nikhil Abraham, 2017-05-01 See all the things coding can accomplish The demand for people with coding know-how exceeds the number of people who understand the languages that power technology. Coding All-in-One For Dummies gives you an ideal place to start when you're ready to add this valuable asset to your professional repertoire. Whether you need to learn how coding works to build a web page or an application or see how coding drives the data revolution, this resource introduces the languages and processes you'll need to know. Peek inside to quickly learn the basics of simple web languages, then move on to start thinking like a professional coder and using languages that power big applications. Take a look inside for the steps to get started with updating a website, creating the next great mobile app, or exploring the world of data science. Whether you're looking for a complete beginner's guide or a trusted resource for when you encounter problems with coding, there's something for you! Create code for the web Get the tools to create a mobile app Discover languages that power data science See the future of coding with machine learning tools With the demand for skilled coders at an all-time high, Coding All-in-One For Dummies is here to propel coding newbies to the ranks of professional programmers.
  codecademy hadoop: The SAGE Handbook of Online Research Methods Nigel G Fielding, Raymond M Lee, Grant Blank, 2016-09-30 Online research methods are popular, dynamic and fast-changing. Following on from the great success of the first edition, published in 2008, The SAGE Handbook of Online Research Methods, Second Edition offers both updates of existing subject areas and new chapters covering more recent developments, such as social media, big data, data visualization and CAQDAS. Bringing together the leading names in both qualitative and quantitative online research, this new edition is organised into nine sections: 1. Online Research Methods 2. Designing Online Research 3. Online Data Capture and Data Collection 4. The Online Survey 5. Digital Quantitative Analysis 6. Digital Text Analysis 7. Virtual Ethnography 8. Online Secondary Analysis: Resources and Methods 9. The Future of Online Social Research The SAGE Handbook of Online Research Methods, Second Edition is an essential resource for anyone interested in the contemporary practice of computer-mediated research and scholarship.
  codecademy hadoop: 計算機概論－科技趨勢深度剖析(第八版)  全華研究室, 王麗琴, 郭欣怡, 2022-04-01 本書乃針對資訊科學基礎教育所設計，內容涵蓋計算機概論的諸多領域，諸如：資訊科技與智慧科技、人工智慧、數字及資料表示法、軟體與硬體基礎知識、網路與行動通訊、物聯網、雲端運算、區塊鏈與金融科技、電子商務、資料庫、大數據、資訊系統、資訊安全與社會議題、資訊素養與倫理等。 各章節除了以豐富的圖文與清楚的圖表來呈現資訊科學的理論基礎，更適當穿插與主題相關的熱門應用，納入時事與生活相關的最新科技發展趨勢，讓讀者一手掌握核心知識與資訊脈動。 本書特色 1.內容完整 本書乃針對資訊科學基礎教育所設計，內容涵蓋計算機概論的諸多領域。 2.理論紮實 各章節搭配豐富圖文與清晰圖表來呈現資訊科學的理論基礎，以淺顯易懂的方式培養讀者的基本瞭解能力。 3.掌握資訊潮流 依文中主題適當穿插相關的熱門應用與主題介紹，納入相關時事生活的最新科技發展趨勢，讓讀者一手掌握核心知識與資訊脈動。 4.收納科技新知 本書介紹最新且熱門的科技趨勢，如量子科技、元宇宙、NFT、去中心化金融、遊戲化金融、DTC/D2C、先買後付、NoSQL、暗網、AI創作著作權、NFT著作權等。
  codecademy hadoop: Python Data Science Essentials Alberto Boschetti, Luca Massaron, 2016-10-28 Become an efficient data science practitioner by understanding Python's key concepts About This Book Quickly get familiar with data science using Python 3.5 Save time (and effort) with all the essential tools explained Create effective data science projects and avoid common pitfalls with the help of examples and hints dictated by experience Who This Book Is For If you are an aspiring data scientist and you have at least a working knowledge of data analysis and Python, this book will get you started in data science. Data analysts with experience of R or MATLAB will also find the book to be a comprehensive reference to enhance their data manipulation and machine learning skills. What You Will Learn Set up your data science toolbox using a Python scientific environment on Windows, Mac, and Linux Get data ready for your data science project Manipulate, fix, and explore data in order to solve data science problems Set up an experimental pipeline to test your data science hypotheses Choose the most effective and scalable learning algorithm for your data science tasks Optimize your machine learning models to get the best performance Explore and cluster graphs, taking advantage of interconnections and links in your data In Detail Fully expanded and upgraded, the second edition of Python Data Science Essentials takes you through all you need to know to suceed in data science using Python. Get modern insight into the core of Python data, including the latest versions of Jupyter notebooks, NumPy, pandas and scikit-learn. Look beyond the fundamentals with beautiful data visualizations with Seaborn and ggplot, web development with Bottle, and even the new frontiers of deep learning with Theano and TensorFlow. Dive into building your essential Python 3.5 data science toolbox, using a single-source approach that will allow to to work with Python 2.7 as well. Get to grips fast with data munging and preprocessing, and all the techniques you need to load, analyse, and process your data. Finally, get a complete overview of principal machine learning algorithms, graph analysis techniques, and all the visualization and deployment instruments that make it easier to present your results to an audience of both data science experts and business users. Style and approach The book is structured as a data science project. You will always benefit from clear code and simplified examples to help you understand the underlying mechanics and real-world datasets.
  codecademy hadoop: Hadoop: The Definitive Guide Tom White, 2012-05-10 Ready to unlock the power of your data? With this comprehensive guide, you’ll learn how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters. You’ll find illuminating case studies that demonstrate how Hadoop is used to solve specific problems. This third edition covers recent changes to Hadoop, including material on the new MapReduce API, as well as MapReduce 2 and its more flexible execution model (YARN). Store large datasets with the Hadoop Distributed File System (HDFS) Run distributed computations with MapReduce Use Hadoop’s data and I/O building blocks for compression, data integrity, serialization (including Avro), and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster—or run Hadoop in the cloud Load data from relational databases into HDFS, using Sqoop Perform large-scale data processing with the Pig query language Analyze datasets with Hive, Hadoop’s data warehousing system Take advantage of HBase for structured and semi-structured data, and ZooKeeper for building distributed systems
  codecademy hadoop: Microsoft® Access® 2010 Step by Step Joan Lambert, Joyce Cox, 2010-07-15 Experience learning made easy-and quickly teach yourself how to build database solutions with Access 2010. With STEP BY STEP, you set the pace-building and practicing the skills you need, just when you need them! Topics include building an Access database from scratch or from templates; publishing your database to the Web; exchanging data with other databases and Microsoft Office documents; creating data-entry forms; using filters and queries; designing reports; using conditional formatting; preventing data corruption and unauthorized access; and other core topics.
  codecademy hadoop: 計算機概論－擁抱人工智慧新浪潮 全華研究室, 王麗琴, 郭欣怡, 2024-04-01 本書乃針對資訊科學基礎教育所設計，內容涵蓋計算機概論的諸多領域，諸如：資訊科技與智慧科技、人工智慧與機器人、數字及資料表示法、軟體與硬體基礎知識、網路與行動通訊、物聯網、雲端運算、區塊鏈與金融科技、電子商務與網路行銷、資料庫、大數據、資訊系統、資訊安全與社會議題、資訊素養與倫理等。 各章節除了以豐富的圖文與清楚的圖表來呈現資訊科學的理論基礎，更適當穿插與主題相關的熱門應用，納入時事與生活相關的最新科技發展趨勢，讓讀者一手掌握核心知識與資訊脈動。
  codecademy hadoop: Big Data para Ejecutivos y Profesionales Jose Antonio Ribeiro Neto, 2023-05-31 Bienvenidos al libro Big Data para Ejecutivos y Profesionales - Tecnologías, Aplicaciones y Carreras. Big Data es una tecnología “moonshot” que emerge y cambia profundamente la vida de las personas y sus carreras profesionales. Este libro está organizado para proporcionar una descripción general de Big Data, Data Science y Data Analytics. Estructura el conocimiento de forma informativa, menos técnica, para una mejor comprensión y un aprendizaje más rápido. Desmitificar y orientar a Ejecutivos y Profesionales en general sobre cómo utilizar el Big Data a su favor para obtener el éxito profesional. Un primer paso para que conozcas y te interese el Big Data. Avalie o resumo de aprendizado que fará nesta jornada. 1 - Introducción a Big Data y Data Science. Principales Tecnologías aplicadas al Big Data. Tecnologías en la nube, sistemas, hardware y software. 2 - Ecosistema Hadoop y su importancia para Big Data. Ambiente de Spark. El paradigma de programación paralela MapReduce para resolver problemas de Big Data. Data Lake, Data Warehouse y procesos ETL para Big Data. Casos de éxito: Tesla, Google, Amazon. 3 - La Ciencia de la Analítica y sus derivaciones para Predictivo y Big Data. Herramientas de analítica y sus aplicaciones en Big Data. Machine Learning (ML) y su relación con el Big Data. Aplicaciones ML para Big Data. Introducción a la visualización de datos. 4 - Privacidad en Big Data con RGPD y LGPD. Computación de borde. Transformación Digital. 5 - Principales carreras profesionales en Big Data. Empresas que crearon Big Data y utilizan la tecnología. Aplicaciones de Big Data en empresas brasileñas. Aplicaciones Big Data para redes sociales e Internet de las Cosas. Privacidad y Gobernanza en Big Data. 6 - Influencers de Big Data y Data Science. Cómo convertirse en un Científico de Datos. Currículo y Lineamientos Académicos. 7 - Conclusiones generales sobre la Era del Big Data y sus implicaciones para la vida empresarial y profesional.
  codecademy hadoop: Efficient R Programming Colin Gillespie, Robin Lovelace, 2016-12-08 There are many excellent R resources for visualization, data science, and package development. Hundreds of scattered vignettes, web pages, and forums explain how to use R in particular domains. But little has been written on how to simply make R work effectively—until now. This hands-on book teaches novices and experienced R users how to write efficient R code. Drawing on years of experience teaching R courses, authors Colin Gillespie and Robin Lovelace provide practical advice on a range of topics—from optimizing the set-up of RStudio to leveraging C++—that make this book a useful addition to any R user’s bookshelf. Academics, business users, and programmers from a wide range of backgrounds stand to benefit from the guidance in Efficient R Programming. Get advice for setting up an R programming environment Explore general programming concepts and R coding techniques Understand the ingredients of an efficient R workflow Learn how to efficiently read and write data in R Dive into data carpentry—the vital skill for cleaning raw data Optimize your code with profiling, standard tricks, and other methods Determine your hardware capabilities for handling R computation Maximize the benefits of collaborative R programming Accelerate your transition from R hacker to R programmer
  codecademy hadoop: Hadoop in Practice Alex Holmes, 2014-10-12 Summary Hadoop in Practice, Second Edition provides over 100 tested, instantly useful techniques that will help you conquer big data, using Hadoop. This revised new edition covers changes and new features in the Hadoop core architecture, including MapReduce 2. Brand new chapters cover YARN and integrating Kafka, Impala, and Spark SQL with Hadoop. You'll also get new and updated techniques for Flume, Sqoop, and Mahout, all of which have seen major new versions recently. In short, this is the most practical, up-to-date coverage of Hadoop available anywhere. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book It's always a good time to upgrade your Hadoop skills! Hadoop in Practice, Second Edition provides a collection of 104 tested, instantly useful techniques for analyzing real-time streams, moving data securely, machine learning, managing large-scale clusters, and taming big data using Hadoop. This completely revised edition covers changes and new features in Hadoop core, including MapReduce 2 and YARN. You'll pick up hands-on best practices for integrating Spark, Kafka, and Impala with Hadoop, and get new and updated techniques for the latest versions of Flume, Sqoop, and Mahout. In short, this is the most practical, up-to-date coverage of Hadoop available. Readers need to know a programming language like Java and have basic familiarity with Hadoop. What's Inside Thoroughly updated for Hadoop 2 How to write YARN applications Integrate real-time technologies like Storm, Impala, and Spark Predictive analytics using Mahout and RR Readers need to know a programming language like Java and have basic familiarity with Hadoop. About the Author Alex Holmes works on tough big-data problems. He is a software engineer, author, speaker, and blogger specializing in large-scale Hadoop projects. Table of Contents PART 1 BACKGROUND AND FUNDAMENTALS Hadoop in a heartbeat Introduction to YARN PART 2 DATA LOGISTICS Data serialization—working with text and beyond Organizing and optimizing data in HDFS Moving data into and out of Hadoop PART 3 BIG DATA PATTERNS Applying MapReduce patterns to big data Utilizing data structures and algorithms at scale Tuning, debugging, and testing PART 4 BEYOND MAPREDUCE SQL on Hadoop Writing a YARN application
  codecademy hadoop: Exam Ref 70-761 Querying Data with Transact-SQL Itzik Ben-Gan, 2017-04-04 Prepare for Microsoft Exam 70-761–and help demonstrate your real-world mastery of SQL Server 2016 Transact-SQL data management, queries, and database programming. Designed for experienced IT professionals ready to advance their status, Exam Ref focuses on the critical-thinking and decision-making acumen needed for success at the MCSA level. Focus on the expertise measured by these objectives: • Filter, sort, join, aggregate, and modify data • Use subqueries, table expressions, grouping sets, and pivoting • Query temporal and non-relational data, and output XML or JSON • Create views, user-defined functions, and stored procedures • Implement error handling, transactions, data types, and nulls This Microsoft Exam Ref: • Organizes its coverage by exam objectives • Features strategic, what-if scenarios to challenge you • Assumes you have experience working with SQL Server as a database administrator, system engineer, or developer • Includes downloadable sample database and code for SQL Server 2016 SP1 (or later) and Azure SQL Database Querying Data with Transact-SQL About the Exam Exam 70-761 focuses on the skills and knowledge necessary to manage and query data and to program databases with Transact-SQL in SQL Server 2016. About Microsoft Certification Passing this exam earns you credit toward a Microsoft Certified Solutions Associate (MCSA) certification that demonstrates your mastery of essential skills for building and implementing on-premises and cloud-based databases across organizations. Exam 70-762 (Developing SQL Databases) is also required for MCSA: SQL 2016 Database Development certification. See full details at: microsoft.com/learning
  codecademy hadoop: 計算機概論－擁抱AI，掌握新趨勢(第十一版) 全華研究室王麗琴, 全華研究室郭欣怡, 2025-04-25 本書乃針對資訊科學基礎教育所設計，內容涵蓋計算機概論的諸多領域，諸如：資訊科技與智慧科技、人工智慧與機器人、數字及資料表示法、軟體與硬體基礎知識、網路與行動通訊、物聯網、雲端運算、區塊鏈與金融科技、電子商務與網路行銷、資料庫、大數據、資訊系統、資訊安全與社會議題、資訊素養與倫理等。 各章節除了以豐富的圖文與清楚的圖表來呈現資訊科學的理論基礎，更適當穿插與主題相關的熱門應用，納入時事與生活相關的最新科技發展趨勢，讓讀者一手掌握核心知識與資訊脈動。
  codecademy hadoop: Python For Dummies Stef Maruch, Aahz Maruch, 2011-05-09 Python is one of the most powerful, easy-to-read programming languages around, but it does have its limitations. This general purpose, high-level language that can be extended and embedded is a smart option for many programming problems, but a poor solution to others. Python For Dummies is the quick-and-easy guide to getting the most out of this robust program. This hands-on book will show you everything you need to know about building programs, debugging code, and simplifying development, as well as defining what actions it can perform. You’ll wrap yourself around all of its advanced features and become an expert Python user in no time. This guide gives you the tools you need to: Master basic elements and syntax Document, design, and debug programs Work with strings like a pro Direct a program with control structures Integrate integers, complex numbers, and modules Build lists, stacks, and queues Create an organized dictionary Handle functions, data, and namespace Construct applications with modules and packages Call, create, extend, and override classes Access the Internet to enhance your library Understand the new features of Python 2.5 Packed with critical idioms and great resources to maximize your productivity, Python For Dummies is the ultimate one-stop information guide. In a matter of minutes you’ll be familiar with Python’s building blocks, strings, dictionaries, and sets; and be on your way to writing the program that you’ve dreamed about!
  codecademy hadoop: Data Analysis and Visualization Using Python Dr. Ossama Embarak, 2018-11-20 Look at Python from a data science point of view and learn proven techniques for data visualization as used in making critical business decisions. Starting with an introduction to data science with Python, you will take a closer look at the Python environment and get acquainted with editors such as Jupyter Notebook and Spyder. After going through a primer on Python programming, you will grasp fundamental Python programming techniques used in data science. Moving on to data visualization, you will see how it caters to modern business needs and forms a key factor in decision-making. You will also take a look at some popular data visualization libraries in Python. Shifting focus to data structures, you will learn the various aspects of data structures from a data science perspective. You will then work with file I/O and regular expressions in Python, followed by gathering and cleaning data. Moving on to exploring and analyzing data, you will look at advanced data structures in Python. Then, you will take a deep dive into data visualization techniques, going through a number of plotting systems in Python. In conclusion, you will complete a detailed case study, where you’ll get a chance to revisit the concepts you’ve covered so far. What You Will Learn Use Python programming techniques for data science Master data collections in Python Create engaging visualizations for BI systems Deploy effective strategies for gathering and cleaning data Integrate the Seaborn and Matplotlib plotting systems Who This Book Is For Developers with basic Python programming knowledge looking to adopt key strategies for data analysis and visualizations using Python.
  codecademy hadoop: Redis in Action Josiah Carlson, 2013-06-17 Summary Redis in Action introduces Redis and walks you through examples that demonstrate how to use it effectively. You'll begin by getting Redis set up properly and then exploring the key-value model. Then, you'll dive into real use cases including simple caching, distributed ad targeting, and more. You'll learn how to scale Redis from small jobs to massive datasets. Experienced developers will appreciate chapters on clustering and internal scripting to make Redis easier to use. About the Technology When you need near-real-time access to a fast-moving data stream, key-value stores like Redis are the way to go. Redis expands on the key-value pattern by accepting a wide variety of data types, including hashes, strings, lists, and other structures. It provides lightning-fast operations on in-memory datasets, and also makes it easy to persist to disk on the fly. Plus, it's free and open source. About this book Redis in Action introduces Redis and the key-value model. You'll quickly dive into real use cases including simple caching, distributed ad targeting, and more. You'll learn how to scale Redis from small jobs to massive datasets and discover how to integrate with traditional RDBMS or other NoSQL stores. Experienced developers will appreciate the in-depth chapters on clustering and internal scripting. Written for developers familiar with database concepts. No prior exposure to NoSQL database concepts nor to Redis itself is required. Appropriate for systems administrators comfortable with programming. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. What's Inside Redis from the ground up Preprocessing real-time data Managing in-memory datasets Pub/sub and configuration Persisting to disk About the Author Dr. Josiah L. Carlson is a seasoned database professional and an active contributor to the Redis community. Table of Contents PART 1 GETTING STARTED Getting to know Redis Anatomy of a Redis web application PART 2 CORE CONCEPTS Commands in Redis Keeping data safe and ensuring performance Using Redis for application support Application components in Redis Search-based applications Building a simple social network PART 3 NEXT STEPS Reducing memory use Scaling Redis Scripting Redis with Lua
  codecademy hadoop: Homeland Cory Doctorow, 2013-09-20 Marcus Yallow is no longer a student. California's economy has collapsed, taking his parents' jobs and his university tuition with it. Thanks to his activist past, Marcus lands a job as webmaster for a muckraking politician who promises reform. Things are never simple, though: soon Marcus finds himself embroiled in lethal political intrigue and the sharp end of class warfare, American style.
  codecademy hadoop: Business Intelligence Demystified Anoop Kumar V K, 2021-09-25 Clear your doubts about Business Intelligence and start your new journey KEY FEATURES ● Includes successful methods and innovative ideas to achieve success with BI. ● Vendor-neutral, unbiased, and based on experience. ● Highlights practical challenges in BI journeys. ● Covers financial aspects along with technical aspects. ● Showcases multiple BI organization models and the structure of BI teams. DESCRIPTION The book demystifies misconceptions and misinformation about BI. It provides clarity to almost everything related to BI in a simplified and unbiased way. It covers topics right from the definition of BI, terms used in the BI definition, coinage of BI, details of the different main uses of BI, processes that support the main uses, side benefits, and the level of importance of BI, various types of BI based on various parameters, main phases in the BI journey and the challenges faced in each of the phases in the BI journey. It clarifies myths about self-service BI and real-time BI. The book covers the structure of a typical internal BI team, BI organizational models, and the main roles in BI. It also clarifies the doubts around roles in BI. It explores the different components that add to the cost of BI and explains how to calculate the total cost of the ownership of BI and ROI for BI. It covers several ideas, including unconventional ideas to achieve BI success and also learn about IBI. It explains the different types of BI architectures, commonly used technologies, tools, and concepts in BI and provides clarity about the boundary of BI w.r.t technologies, tools, and concepts. The book helps you lay a very strong foundation and provides the right perspective about BI. It enables you to start or restart your journey with BI. WHAT YOU WILL LEARN ● Builds a strong conceptual foundation in BI. ● Gives the right perspective and clarity on BI uses, challenges, and architectures. ● Enables you to make the right decisions on the BI structure, organization model, and budget. ● Explains which type of BI solution is required for your business. ● Applies successful BI ideas. WHO THIS BOOK IS FOR This book is a must-read for business managers, BI aspirants, CxOs, and all those who want to drive the business value with data-driven insights. TABLE OF CONTENTS 1. What is Business Intelligence? 2. Why do Businesses need BI? 3. Types of Business Intelligence 4. Challenges in Business Intelligence 5. Roles in Business Intelligence 6. Financials of Business Intelligence 7. Ideas for Success with BI 8. Introduction to IBI 9. BI Architectures 10. Demystify Tech, Tools, and Concepts in BI
  codecademy hadoop: Practical SQL, 2nd Edition Anthony DeBarros, 2022-01-25 Analyze data like a pro, even if you’re a beginner. Practical SQL is an approachable and fast-paced guide to SQL (Structured Query Language), the standard programming language for defining, organizing, and exploring data in relational databases. Anthony DeBarros, a journalist and data analyst, focuses on using SQL to find the story within your data. The examples and code use the open-source database PostgreSQL and its companion pgAdmin interface, and the concepts you learn will apply to most database management systems, including MySQL, Oracle, SQLite, and others.* You’ll first cover the fundamentals of databases and the SQL language, then build skills by analyzing data from real-world datasets such as US Census demographics, New York City taxi rides, and earthquakes from US Geological Survey. Each chapter includes exercises and examples that teach even those who have never programmed before all the tools necessary to build powerful databases and access information quickly and efficiently. You’ll learn how to: Create databases and related tables using your own data Aggregate, sort, and filter data to find patterns Use functions for basic math and advanced statistical operations Identify errors in data and clean them up Analyze spatial data with a geographic information system (PostGIS) Create advanced queries and automate tasks This updated second edition has been thoroughly revised to reflect the latest in SQL features, including additional advanced query techniques for wrangling data. This edition also has two new chapters: an expanded set of instructions on for setting up your system plus a chapter on using PostgreSQL with the popular JSON data interchange format. Learning SQL doesn’t have to be dry and complicated. Practical SQL delivers clear examples with an easy-to-follow approach to teach you the tools you need to build and manage your own databases. * Microsoft SQL Server employs a variant of the language called T-SQL, which is not covered by Practical SQL.
  codecademy hadoop: Professional Hadoop Benoy Antony, Konstantin Boudnik, Cheryl Adams, Branky Shao, Cazen Lee, Kai Sasaki, 2016-05-03 The professional's one-stop guide to this open-source, Java-based big data framework Professional Hadoop is the complete reference and resource for experienced developers looking to employ Apache Hadoop in real-world settings. Written by an expert team of certified Hadoop developers, committers, and Summit speakers, this book details every key aspect of Hadoop technology to enable optimal processing of large data sets. Designed expressly for the professional developer, this book skips over the basics of database development to get you acquainted with the framework's processes and capabilities right away. The discussion covers each key Hadoop component individually, culminating in a sample application that brings all of the pieces together to illustrate the cooperation and interplay that make Hadoop a major big data solution. Coverage includes everything from storage and security to computing and user experience, with expert guidance on integrating other software and more. Hadoop is quickly reaching significant market usage, and more and more developers are being called upon to develop big data solutions using the Hadoop framework. This book covers the process from beginning to end, providing a crash course for professionals needing to learn and apply Hadoop quickly. Configure storage, UE, and in-memory computing Integrate Hadoop with other programs including Kafka and Storm Master the fundamentals of Apache Big Top and Ignite Build robust data security with expert tips and advice Hadoop's popularity is largely due to its accessibility. Open-source and written in Java, the framework offers almost no barrier to entry for experienced database developers already familiar with the skills and requirements real-world programming entails. Professional Hadoop gives you the practical information and framework-specific skills you need quickly.
  codecademy hadoop: Professional C++ Nicholas A. Solter, Scott J. Kleper, 2005-01-07 Geared to experienced C++ developers who may not be familiar with the more advanced features of the language, and therefore are not using it to its full capabilities Teaches programmers how to think in C++-that is, how to design effective solutions that maximize the power of the language The authors drill down into this notoriously complex language, explaining poorly understood elements of the C++ feature set as well as common pitfalls to avoid Contains several in-depth case studies with working code that's been tested on Windows, Linux, and Solaris platforms
  codecademy hadoop: Mastering Hadoop 3 Chanchal Singh, Manish Kumar, 2019-02-28 A comprehensive guide to mastering the most advanced Hadoop 3 concepts Key FeaturesGet to grips with the newly introduced features and capabilities of Hadoop 3Crunch and process data using MapReduce, YARN, and a host of tools within the Hadoop ecosystemSharpen your Hadoop skills with real-world case studies and codeBook Description Apache Hadoop is one of the most popular big data solutions for distributed storage and for processing large chunks of data. With Hadoop 3, Apache promises to provide a high-performance, more fault-tolerant, and highly efficient big data processing platform, with a focus on improved scalability and increased efficiency. With this guide, you’ll understand advanced concepts of the Hadoop ecosystem tool. You’ll learn how Hadoop works internally, study advanced concepts of different ecosystem tools, discover solutions to real-world use cases, and understand how to secure your cluster. It will then walk you through HDFS, YARN, MapReduce, and Hadoop 3 concepts. You’ll be able to address common challenges like using Kafka efficiently, designing low latency, reliable message delivery Kafka systems, and handling high data volumes. As you advance, you’ll discover how to address major challenges when building an enterprise-grade messaging system, and how to use different stream processing systems along with Kafka to fulfil your enterprise goals. By the end of this book, you’ll have a complete understanding of how components in the Hadoop ecosystem are effectively integrated to implement a fast and reliable data pipeline, and you’ll be equipped to tackle a range of real-world problems in data pipelines. What you will learnGain an in-depth understanding of distributed computing using Hadoop 3Develop enterprise-grade applications using Apache Spark, Flink, and moreBuild scalable and high-performance Hadoop data pipelines with security, monitoring, and data governanceExplore batch data processing patterns and how to model data in HadoopMaster best practices for enterprises using, or planning to use, Hadoop 3 as a data platformUnderstand security aspects of Hadoop, including authorization and authenticationWho this book is for If you want to become a big data professional by mastering the advanced concepts of Hadoop, this book is for you. You’ll also find this book useful if you’re a Hadoop professional looking to strengthen your knowledge of the Hadoop ecosystem. Fundamental knowledge of the Java programming language and basics of Hadoop is necessary to get started with this book.
  codecademy hadoop: SQL Queries for Mere Mortals John L. Viescas, Michael J. Hernandez, 2014-06-10 The #1 Easy, Common-Sense Guide to SQL Queries—Updated for Today’s Databases, Standards, and Challenges SQL Queries for Mere Mortals ® has earned worldwide praise as the clearest, simplest tutorial on writing effective SQL queries. The authors have updated this hands-on classic to reflect new SQL standards and database applications and teach valuable new techniques. Step by step, John L. Viescas and Michael J. Hernandez guide you through creating reliable queries for virtually any modern SQL-based database. They demystify all aspects of SQL query writing, from simple data selection and filtering to joining multiple tables and modifying sets of data. Three brand-new chapters teach you how to solve a wide range of challenging SQL problems. You’ll learn how to write queries that apply multiple complex conditions on one table, perform sophisticated logical evaluations, and think “outside the box” using unlinked tables. Coverage includes -- Getting started: understanding what relational databases are, and ensuring that your database structures are sound -- SQL basics: using SELECT statements, creating expressions, sorting information with ORDER BY, and filtering data using WHERE -- Summarizing and grouping data with GROUP BY and HAVING clauses -- Drawing data from multiple tables: using INNER JOIN, OUTER JOIN, and UNION operators, and working with subqueries -- Modifying data sets with UPDATE, INSERT, and DELETE statements Advanced queries: complex NOT and AND, conditions, if-then-else using CASE, unlinked tables, driver tables, and more Practice all you want with downloadable sample databases for today’s versions of Microsoft Office Access, Microsoft SQL Server, and the open source MySQL database. Whether you’re a DBA, developer, user, or student, there’s no better way to master SQL. informit.com/aw forMereMortals.com
  codecademy hadoop: Data Analytics with Hadoop Benjamin Bengfort, Jenny Kim, 2016-06 Ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. Instead of deployment, operations, or software development usually associated with distributed computing, you’ll focus on particular analyses you can build, the data warehousing techniques that Hadoop provides, and higher order data workflows this framework can produce. Data scientists and analysts will learn how to perform a wide range of techniques, from writing MapReduce and Spark applications with Python to using advanced modeling and data management with Spark MLlib, Hive, and HBase. You’ll also learn about the analytical processes and data systems available to build and empower data products that can handle—and actually require—huge amounts of data. Understand core concepts behind Hadoop and cluster computing Use design patterns and parallel analytical algorithms to create distributed data analysis jobs Learn about data management, mining, and warehousing in a distributed context using Apache Hive and HBase Use Sqoop and Apache Flume to ingest data from relational databases Program complex Hadoop and Spark applications with Apache Pig and Spark DataFrames Perform machine learning techniques such as classification, clustering, and collaborative filtering with Spark’s MLlib
  codecademy hadoop: Python Programming in Hindi | Complete Beginner to Advanced Guide code academy, 2025-05-30 Python Programming Language in Hindi is a comprehensive and practical guide designed for Hindi-speaking learners who want to master Python from the ground up. Starting with basic syntax and data types, the book gradually progresses to advanced topics like object-oriented programming, file handling, modules, and real-world applications. Written entirely in Hindi, this guide includes clear explanations, real-life examples, and coding exercises to make programming easy and enjoyable—even for beginners. Ideal for students, job seekers, and aspiring developers.
  codecademy hadoop: Database Design for Mere Mortals Michael James Hernandez, 2003 The bestselling book on database design is now fully updated and revised!
  codecademy hadoop: Practical Hive Scott Shaw, Andreas François Vermeulen, Ankur Gupta, David Kjerrumgaard, 2016-08-27 Dive into the world of SQL on Hadoop and get the most out of your Hive data warehouses. This book is your go-to resource for using Hive: authors Scott Shaw, Ankur Gupta, David Kjerrumgaard, and Andreas Francois Vermeulen take you through learning HiveQL, the SQL-like language specific to Hive, to analyze, export, and massage the data stored across your Hadoop environment. From deploying Hive on your hardware or virtual machine and setting up its initial configuration to learning how Hive interacts with Hadoop, MapReduce, Tez and other big data technologies, Practical Hive gives you a detailed treatment of the software. In addition, this book discusses the value of open source software, Hive performance tuning, and how to leverage semi-structured and unstructured data. What You Will Learn Install and configure Hive for new and existing datasets Perform DDL operations Execute efficient DML operations Use tables, partitions, buckets, and user-defined functions Discover performance tuning tips and Hive best practices Who This Book Is For Developers, companies, and professionals who deal with large amounts of data and could use software that can efficiently manage large volumes of input. It is assumed that readers have the ability to work with SQL.
  codecademy hadoop: Pro Hadoop Jason Venner, 2009-08-09 You've heard the hype about Hadoop: it runs petabyte–scale data mining tasks insanely fast, it runs gigantic tasks on clouds for absurdly cheap, it's been heavily committed to by tech giants like IBM, Yahoo!, and the Apache Project, and it's completely open-source (thus free). But what exactly is it, and more importantly, how do you even get a Hadoop cluster up and running? From Apress, the name you've come to trust for hands–on technical knowledge, Pro Hadoop brings you up to speed on Hadoop. You learn the ins and outs of MapReduce; how to structure a cluster, design, and implement the Hadoop file system; and how to build your first cloud–computing tasks using Hadoop. Learn how to let Hadoop take care of distributing and parallelizing your software—you just focus on the code, Hadoop takes care of the rest. Best of all, you'll learn from a tech professional who's been in the Hadoop scene since day one. Written from the perspective of a principal engineer with down–in–the–trenches knowledge of what to do wrong with Hadoop, you learn how to avoid the common, expensive first errors that everyone makes with creating their own Hadoop system or inheriting someone else's. Skip the novice stage and the expensive, hard–to–fix mistakes...go straight to seasoned pro on the hottest cloud–computing framework with Pro Hadoop. Your productivity will blow your managers away.
  codecademy hadoop: Database Internals Alex Petrov, 2019-09-13 When it comes to choosing, using, and maintaining a database, understanding its internals is essential. But with so many distributed databases and tools available today, it’s often difficult to understand what each one offers and how they differ. With this practical guide, Alex Petrov guides developers through the concepts behind modern database and storage engine internals. Throughout the book, you’ll explore relevant material gleaned from numerous books, papers, blog posts, and the source code of several open source databases. These resources are listed at the end of parts one and two. You’ll discover that the most significant distinctions among many modern databases reside in subsystems that determine how storage is organized and how data is distributed. This book examines: Storage engines: Explore storage classification and taxonomy, and dive into B-Tree-based and immutable Log Structured storage engines, with differences and use-cases for each Storage building blocks: Learn how database files are organized to build efficient storage, using auxiliary data structures such as Page Cache, Buffer Pool and Write-Ahead Log Distributed systems: Learn step-by-step how nodes and processes connect and build complex communication patterns Database clusters: Which consistency models are commonly used by modern databases and how distributed storage systems achieve consistency
  codecademy hadoop: Practical Hadoop Ecosystem Deepak Vohra, 2016-09-30 Learn how to use the Apache Hadoop projects, including MapReduce, HDFS, Apache Hive, Apache HBase, Apache Kafka, Apache Mahout, and Apache Solr. From setting up the environment to running sample applications each chapter in this book is a practical tutorial on using an Apache Hadoop ecosystem project. While several books on Apache Hadoop are available, most are based on the main projects, MapReduce and HDFS, and none discusses the other Apache Hadoop ecosystem projects and how they all work together as a cohesive big data development platform. What You Will Learn: Set up the environment in Linux for Hadoop projects using Cloudera Hadoop Distribution CDH 5 Run a MapReduce job Store data with Apache Hive, and Apache HBase Index data in HDFS with Apache Solr Develop a Kafka messaging system Stream Logs to HDFS with Apache Flume Transfer data from MySQL database to Hive, HDFS, and HBase with Sqoop Create a Hive table over Apache Solr Develop a Mahout User Recommender System Who This Book Is For: Apache Hadoop developers. Pre-requisite knowledge of Linux and some knowledge of Hadoop is required.
  codecademy hadoop: Excel 2019 Bible Michael Alexander, Richard Kusleika, John Walkenbach, 2018-09-25 The complete guide to Excel 2019 Whether you are just starting out or an Excel novice, the Excel 2019 Bible is your comprehensive, go-to guide for all your Excel 2019 needs. Whether you use Excel at work or at home, you will be guided through the powerful new features and capabilities to take full advantage of what the updated version offers. Learn to incorporate templates, implement formulas, create pivot tables, analyze data, and much more. Navigate this powerful tool for business, home management, technical work, and much more with the only resource you need, Excel 2019 Bible. Create functional spreadsheets that work Master formulas, formatting, pivot tables, and more Get acquainted with Excel 2019's new features and tools Whether you need a walkthrough tutorial or an easy-to-navigate desk reference, the Excel 2019 Bible has you covered with complete coverage and clear expert guidance.
  codecademy hadoop: Digitising the Industry - Internet of Things Connecting the Physical, Digital and Virtual Worlds Peter Friess , 2016-07-07 This book provides an overview of the current Internet of Things (IoT) landscape, ranging from the research, innovation and development priorities to enabling technologies in a global context. A successful deployment of IoT technologies requires integration on all layers, be it cognitive and semantic aspects, middleware components, services, edge devices/machines and infrastructures. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC - Internet of Things European Research Cluster from research to technological innovation, validation and deployment. The book builds on the ideas put forward by the European Research Cluster and the IoT European Platform Initiative (IoT-EPI) and presents global views and state of the art results on the challenges facing the research, innovation, development and deployment of IoT in the next years. The IoT is bridging the physical world with virtual world and requires sound information processing capabilities for the digital shadows of these real things. The research and innovation in nanoelectronics, semiconductor, sensors/actuators, communication, analytics technologies, cyber-physical systems, software, swarm intelligent and deep learning systems are essential for the successful deployment of IoT applications. The emergence of IoT platforms with multiple functionalities enables rapid development and lower costs by offering standardised components that can be shared across multiple solutions in many industry verticals. The IoT applications will gradually move from vertical, single purpose solutions to multi-purpose and collaborative applications interacting across industry verticals, organisations and people, being one of the essential paradigms of the digital economy. Many of those applications still have to be identified and involvement of end-users including the creative sector in this innovation is crucial. The IoT applications and deployments as integrated building blocks of the new digital economy are part of the accompanying IoT policy framework to address issues of horizontal nature and common interest (i.e. privacy, end-to-end security, user acceptance, societal, ethical aspects and legal issues) for providing trusted IoT solutions in a coordinated and consolidated manner across the IoT activities and pilots. In this, context IoT ecosystems offer solutions beyond a platform and solve important technical challenges in the different verticals and across verticals. These IoT technology ecosystems are instrumental for the deployment of large pilots and can easily be connected to or build upon the core IoT solutions for different applications in order to expand the system of use and allow new and even unanticipated IoT end uses. Technical topics discussed in the book include: IntroductionDigitising industry and IoT as key enabler in the new era of Digital EconomyIoT Strategic Research and Innovation Agenda IoT in the digital industrial context: Digital Single MarketIntegration of heterogeneous systems and bridging the virtual, digital and physical worldsFederated IoT platforms and interoperabilityEvolution from intelligent devices to connected systems of systems by adding new layers of cognitive behaviour, artificial intelligence and user interfaces. Innovation through IoT ecosystemsTrust-based IoT end-to-end security, privacy framework User acceptance, societal, ethical aspects and legal issuesInternet of Things Applications
  codecademy hadoop: Hadoop: The Definitive Guide Tom White, 2015-03-25 Get ready to unlock the power of your data. With the fourth edition of this comprehensive guide, youâ??ll learn how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters. Using Hadoop 2 exclusively, author Tom White presents new chapters on YARN and several Hadoop-related projects such as Parquet, Flume, Crunch, and Spark. Youâ??ll learn about recent changes to Hadoop, and explore new case studies on Hadoopâ??s role in healthcare systems and genomics data processing. Learn fundamental components such as MapReduce, HDFS, and YARN Explore MapReduce in depth, including steps for developing applications with it Set up and maintain a Hadoop cluster running HDFS and MapReduce on YARN Learn two data formats: Avro for data serialization and Parquet for nested data Use data ingestion tools such as Flume (for streaming data) and Sqoop (for bulk data transfer) Understand how high-level data processing tools like Pig, Hive, Crunch, and Spark work with Hadoop Learn the HBase distributed database and the ZooKeeper distributed configuration service
  codecademy hadoop: Engineering Mathematics C W. Evans, 2019-03-04 The programmed approach, established in the first two editions is maintained in the third and it provides a sound foundation from which the student can build a solid engineering understanding. This edition has been modified to reflect the changes in the syllabuses which students encounter before beginning undergraduate studies. The first two chapters include material that assumes the reader has little previous experience in maths. Written by CHarles Evans who lectures at the University of Portsmouth and has been teaching engineering and applied mathematics for more than 25 years. This text provides one of the essential tools for both undergraduate students and professional engineers.
  codecademy hadoop: Creating Value with Big Data Analytics Peter C. Verhoef, Edwin Kooge, Natasha Walk, 2016-01-08 Our newly digital world is generating an almost unimaginable amount of data about all of us. Such a vast amount of data is useless without plans and strategies that are designed to cope with its size and complexity, and which enable organisations to leverage the information to create value. This book is a refreshingly practical, yet theoretically sound roadmap to leveraging big data and analytics. Creating Value with Big Data Analytics provides a nuanced view of big data development, arguing that big data in itself is not a revolution but an evolution of the increasing availability of data that has been observed in recent times. Building on the authors’ extensive academic and practical knowledge, this book aims to provide managers and analysts with strategic directions and practical analytical solutions on how to create value from existing and new big data. By tying data and analytics to specific goals and processes for implementation, this is a much-needed book that will be essential reading for students and specialists of data analytics, marketing research, and customer relationship management.
  codecademy hadoop: Hadoop in Action Chuck Lam, 2010-12-25 Hadoop in Action teaches readers how to use Hadoop and write MapReduce programs. The intended readers are programmers, architects, and project managers who have to process large amounts of data offline. Hadoop in Action will lead the reader from obtaining a copy of Hadoop to setting it up in a cluster and writing data analytic programs. The book begins by making the basic idea of Hadoop and MapReduce easier to grasp by applying the default Hadoop installation to a few easy-to-follow tasks, such as analyzing changes in word frequency across a body of documents. The book continues through the basic concepts of MapReduce applications developed using Hadoop, including a close look at framework components, use of Hadoop for a variety of data analysis tasks, and numerous examples of Hadoop in action. Hadoop in Action will explain how to use Hadoop and present design patterns and practices of programming MapReduce. MapReduce is a complex idea both conceptually and in its implementation, and Hadoop users are challenged to learn all the knobs and levers for running Hadoop. This book takes you beyond the mechanics of running Hadoop, teaching you to write meaningful programs in a MapReduce framework. This book assumes the reader will have a basic familiarity with Java, as most code examples will be written in Java. Familiarity with basic statistical concepts (e.g. histogram, correlation) will help the reader appreciate the more advanced data processing examples. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.
  codecademy hadoop: Big Data Made Easy Michael Frampton, 2014-12-31 Many corporations are finding that the size of their data sets are outgrowing the capability of their systems to store and process them. The data is becoming too big to manage and use with traditional tools. The solution: implementing a big data system. As Big Data Made Easy: A Working Guide to the Complete Hadoop Toolset shows, Apache Hadoop offers a scalable, fault-tolerant system for storing and processing data in parallel. It has a very rich toolset that allows for storage (Hadoop), configuration (YARN and ZooKeeper), collection (Nutch and Solr), processing (Storm, Pig, and Map Reduce), scheduling (Oozie), moving (Sqoop and Avro), monitoring (Chukwa, Ambari, and Hue), testing (Big Top), and analysis (Hive). The problem is that the Internet offers IT pros wading into big data many versions of the truth and some outright falsehoods born of ignorance. What is needed is a book just like this one: a wide-ranging but easily understood set of instructions to explain where to get Hadoop tools, what they can do, how to install them, how to configure them, how to integrate them, and how to use them successfully. And you need an expert who has worked in this area for a decade—someone just like author and big data expert Mike Frampton. Big Data Made Easy approaches the problem of managing massive data sets from a systems perspective, and it explains the roles for each project (like architect and tester, for example) and shows how the Hadoop toolset can be used at each system stage. It explains, in an easily understood manner and through numerous examples, how to use each tool. The book also explains the sliding scale of tools available depending upon data size and when and how to use them. Big Data Made Easy shows developers and architects, as well as testers and project managers, how to: Store big data Configure big data Process big data Schedule processes Move data among SQL and NoSQL systems Monitor data Perform big data analytics Report on big data processes and projects Test big data systems Big Data Made Easy also explains the best part, which is that this toolset is free. Anyone can download it and—with the help of this book—start to use it within a day. With the skills this book will teach you under your belt, you will add value to your company or client immediately, not to mention your career.
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