This book focuses on topics that have been ignored in most other JDBC books, such as database and result set metadata. It will help you develop database solutions, like adapters, connectors, and frameworks using Java/JDBC. The insightful solutions will enable you to handle all data types, including large binary objects. A unique feature of the book is that it presents JDBC solutions (result sets) in XML.
This edition is also a Java EE 5-compliant book, perfect for lightweight Java database development. And it provides cut-and-paste code templates that can be immediately customized and applied in each developer's application development.
Written by the developers of Spark, this book will have data scientists and engineers up and running in no time. You’ll learn how to express parallel jobs with just a few lines of code, and cover applications from simple batch jobs to stream processing and machine learning.Quickly dive into Spark capabilities such as distributed datasets, in-memory caching, and the interactive shellLeverage Spark’s powerful built-in libraries, including Spark SQL, Spark Streaming, and MLlibUse one programming paradigm instead of mixing and matching tools like Hive, Hadoop, Mahout, and StormLearn how to deploy interactive, batch, and streaming applicationsConnect to data sources including HDFS, Hive, JSON, and S3Master advanced topics like data partitioning and shared variables
Complete with case studies that illustrate how Hadoop solves specific problems, this book helps you:
Use the Hadoop Distributed File System (HDFS) for storing large datasets, and run distributed computations over those datasets using MapReduceBecome familiar with Hadoop's data and I/O building blocks for compression, data integrity, serialization, and persistenceDiscover common pitfalls and advanced features for writing real-world MapReduce programsDesign, build, and administer a dedicated Hadoop cluster, or run Hadoop in the cloudUse Pig, a high-level query language for large-scale data processingTake advantage of HBase, Hadoop's database for structured and semi-structured dataLearn ZooKeeper, a toolkit of coordination primitives for building distributed systems
If you have lots of data -- whether it's gigabytes or petabytes -- Hadoop is the perfect solution. Hadoop: The Definitive Guide is the most thorough book available on the subject.
"Now you have the opportunity to learn about Hadoop from a master-not only of the technology, but also of common sense and plain talk."-- Doug Cutting, Hadoop Founder, Yahoo!
Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It’s ideal for analysts new to Python and for Python programmers new to scientific computing.Use the IPython interactive shell as your primary development environmentLearn basic and advanced NumPy (Numerical Python) featuresGet started with data analysis tools in the pandas libraryUse high-performance tools to load, clean, transform, merge, and reshape dataCreate scatter plots and static or interactive visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsMeasure data by points in time, whether it’s specific instances, fixed periods, or intervalsLearn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples
If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out.Get a crash course in PythonLearn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data scienceCollect, explore, clean, munge, and manipulate dataDive into the fundamentals of machine learningImplement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clusteringExplore recommender systems, natural language processing, network analysis, MapReduce, and databases
SQLite is a small, embeddable, SQL-based, relational database management system. It has been widely used in low- to medium-tier database applications, especially in embedded devices. This book provides a comprehensive description of SQLite database system. It describes design principles, engineering trade-offs, implementation issues, and operations of SQLite.
If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource.What You Will LearnExplore how to use different machine learning models to ask different questions of your dataLearn how to build neural networks using Keras and TheanoFind out how to write clean and elegant Python code that will optimize the strength of your algorithmsDiscover how to embed your machine learning model in a web application for increased accessibilityPredict continuous target outcomes using regression analysisUncover hidden patterns and structures in data with clusteringOrganize data using effective pre-processing techniquesGet to grips with sentiment analysis to delve deeper into textual and social media dataIn Detail
Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success.
Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization.Style and approach
Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.
By using concrete examples, minimal theory, and two production-ready Python frameworks—scikit-learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started.Explore the machine learning landscape, particularly neural netsUse scikit-learn to track an example machine-learning project end-to-endExplore several training models, including support vector machines, decision trees, random forests, and ensemble methodsUse the TensorFlow library to build and train neural netsDive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learningLearn techniques for training and scaling deep neural netsApply practical code examples without acquiring excessive machine learning theory or algorithm details
Updated for the latest versions of this popular database, this edition covers many complex features that have been added to MySQL 5.0 and 5.1, including a section dedicated to stored procedures and triggers. After a brief introduction on installation and initial setup, the book explains: How to configure MySQL, such as setting the root passwordMySQL data types, including numerics, strings, dates, and complex typesSQL syntax, commands, data types, operators, and functionsArithmetic, comparison and logical operatorsAggregate and general functionsStored procedures and triggers, including procedure definition, procedure calls, procedure management, cursors, and triggersYou don't have time to stop and thumb through an exhaustive reference when you're hard at work. This portable and affordable guide is small enough to fit into your pocket, and gives you a convenient reference that you can consult anywhere. When you reach a sticking point and need to get to a solution quickly, the MySQL Pocket Reference is the book you want to have.
Updated for R 2.14 and 2.15, this second edition includes new and expanded chapters on R performance, the ggplot2 data visualization package, and parallel R computing with Hadoop.Get started quickly with an R tutorial and hundreds of examplesExplore R syntax, objects, and other language detailsFind thousands of user-contributed R packages online, including BioconductorLearn how to use R to prepare data for analysisVisualize your data with R’s graphics, lattice, and ggplot2 packagesUse R to calculate statistical fests, fit models, and compute probability distributionsSpeed up intensive computations by writing parallel R programs for HadoopGet a complete desktop reference to R
The potential user base and the wide array of available high-performance devices makes Android an attractive target for aspiring game developers. Do you have an awesome idea for the next break-through mobile gaming title? Beginning Android Games will help you kick-start your project. This book will guide you through the process of making several example game apps using APIs available in new Android SDK and earlier SDK releases for Android smartphones and tablets:The fundamentals of game development and design suitable for Android smartphones and tablets The Android platform basics to apply those fundamentals in the context of making a game, including new File Manager system and better battery life management The design of 2D and 3D games and their successful implementation on the Android platform
This book lets developers see and use some Android SDK Jelly Bean; however, this book is structured so that app developers can use earlier Android SDK releases. This book is backward compatible like the Android SDK.
This book is dedicated to all the machine learning and deep learning enthusiasts, data scientists, researchers, and even students who want to perform more accurate, fast machine learning operations with TensorFlow. Those with basic knowledge of programming (Python and C/C++) and math concepts who want to be introduced to the topics of machine learning will find this book useful.What You Will LearnInstall and adopt TensorFlow in your Python environment to solve mathematical problemsGet to know the basic machine and deep learning conceptsTrain and test neural networks to fit your data modelMake predictions using regression algorithmsAnalyze your data with a clustering procedureDevelop algorithms for clustering and data classificationUse GPU computing to analyze big dataIn Detail
Google's TensorFlow engine, after much fanfare, has evolved in to a robust, user-friendly, and customizable, application-grade software library of machine learning (ML) code for numerical computation and neural networks.
This book takes you through the practical software implementation of various machine learning techniques with TensorFlow. In the first few chapters, you'll gain familiarity with the framework and perform the mathematical operations required for data analysis. As you progress further, you'll learn to implement various machine learning techniques such as classification, clustering, neural networks, and deep learning through practical examples.
By the end of this book, you'll have gained hands-on experience of using TensorFlow and building classification, image recognition systems, language processing, and information retrieving systems for your application.Style and approach
Get quickly up and running with TensorFlow using this fast-paced guide. You will get to know everything that can be done with TensorFlow and we'll show you how to implement it in your environment. The examples in the book are from the core of the computation industry—something you can connect to and will find familiar.
"Building a Scalable Data Warehouse" covers everything one needs to know to create a scalable data warehouse end to end, including a presentation of the Data Vault modeling technique, which provides the foundations to create a technical data warehouse layer. The book discusses how to build the data warehouse incrementally using the agile Data Vault 2.0 methodology. In addition, readers will learn how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 architecture including implementation best practices. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Linstedt and Michael Olschimke discuss:
How to load each layer using SQL Server Integration Services (SSIS), including automation of the Data Vault loading processes.
Important data warehouse technologies and practices.
Data Quality Services (DQS) and Master Data Services (MDS) in the context of the Data Vault architecture.Provides a complete introduction to data warehousing, applications, and the business context so readers can get-up and running fast Explains theoretical concepts and provides hands-on instruction on how to build and implement a data warehouseDemystifies data vault modeling with beginning, intermediate, and advanced techniquesDiscusses the advantages of the data vault approach over other techniques, also including the latest updates to Data Vault 2.0 and multiple improvements to Data Vault 1.0
This updated second edition provides guidance for database developers, advanced configuration for system administrators, and an overview of the concepts and use cases for other people on your project. Ideal for NoSQL newcomers and experienced MongoDB users alike, this guide provides numerous real-world schema design examples.Get started with MongoDB core concepts and vocabularyPerform basic write operations at different levels of safety and speedCreate complex queries, with options for limiting, skipping, and sorting resultsDesign an application that works well with MongoDBAggregate data, including counting, finding distinct values, grouping documents, and using MapReduceGather and interpret statistics about your collections and databasesSet up replica sets and automatic failover in MongoDBUse sharding to scale horizontally, and learn how it impacts applicationsDelve into monitoring, security and authentication, backup/restore, and other administrative tasks
Authors Ben Spivey and Joey Echeverria provide in-depth information about the security features available in Hadoop, and organize them according to common computer security concepts. You’ll also get real-world examples that demonstrate how you can apply these concepts to your use cases.Understand the challenges of securing distributed systems, particularly HadoopUse best practices for preparing Hadoop cluster hardware as securely as possibleGet an overview of the Kerberos network authentication protocolDelve into authorization and accounting principles as they apply to HadoopLearn how to use mechanisms to protect data in a Hadoop cluster, both in transit and at restIntegrate Hadoop data ingest into enterprise-wide security architectureEnsure that security architecture reaches all the way to end-user access
By reading this definitive tutorial and reference, you'll gain the knowledge and experience to create stunning, cutting-edge Android apps that can make you money, while keeping you agile enough to respond to changes in the future.
Rather than run through all possible scenarios, this pragmatic operations guide calls out what works, as demonstrated in critical deployments.Get a high-level overview of HDFS and MapReduce: why they exist and how they workPlan a Hadoop deployment, from hardware and OS selection to network requirementsLearn setup and configuration details with a list of critical propertiesManage resources by sharing a cluster across multiple groupsGet a runbook of the most common cluster maintenance tasksMonitor Hadoop clusters—and learn troubleshooting with the help of real-world war storiesUse basic tools and techniques to handle backup and catastrophic failure
Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way.
You’ll learn how to:Wrangle—transform your datasets into a form convenient for analysisProgram—learn powerful R tools for solving data problems with greater clarity and easeExplore—examine your data, generate hypotheses, and quickly test themModel—provide a low-dimensional summary that captures true "signals" in your datasetCommunicate—learn R Markdown for integrating prose, code, and results
This book offers practical answers to some of the hardest questions faced by PL/SQL developers, including:What is the best way to write the SQL logic in my application code?
How should I write my packages so they can be leveraged by my entire team of developers?
How can I make sure that all my team's programs handle and record errors consistently?Oracle PL/SQL Best Practices summarizes PL/SQL best practices in nine major categories: overall PL/SQL application development; programming standards; program testing, tracing, and debugging; variables and data structures; control logic; error handling; the use of SQL in PL/SQL; building procedures, functions, packages, and triggers; and overall program performance.
This book is a concise and entertaining guide that PL/SQL developers will turn to again and again as they seek out ways to write higher quality code and more successful applications.
"This book presents ideas that make the difference between a successful project and one that never gets off the ground. It goes beyond just listing a set of rules, and provides realistic scenarios that help the reader understand where the rules come from. This book should be required reading for any team of Oracle database professionals."
--Dwayne King, President, KRIDAN Consulting
Implementations, as well as interesting, real-world examples of each data structure and algorithm, are included.
Using both a programming style and a writing style that are exceptionally clean, Kyle Loudon shows you how to use such essential data structures as lists, stacks, queues, sets, trees, heaps, priority queues, and graphs. He explains how to use algorithms for sorting, searching, numerical analysis, data compression, data encryption, common graph problems, and computational geometry. And he describes the relative efficiency of all implementations. The compression and encryption chapters not only give you working code for reasonably efficient solutions, they offer explanations of concepts in an approachable manner for people who never have had the time or expertise to study them in depth.
Anyone with a basic understanding of the C language can use this book. In order to provide maintainable and extendible code, an extra level of abstraction (such as pointers to functions) is used in examples where appropriate. Understanding that these techniques may be unfamiliar to some programmers, Loudon explains them clearly in the introductory chapters.
Contents include:PointersRecursionAnalysis of algorithmsData structures (lists, stacks, queues, sets, hash tables, trees, heaps, priority queues, graphs)Sorting and searchingNumerical methodsData compressionData encryptionGraph algorithmsGeometric algorithms
Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.
With this book, you’ll learn:Why exploratory data analysis is a key preliminary step in data scienceHow random sampling can reduce bias and yield a higher quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that “learn” from dataUnsupervised learning methods for extracting meaning from unlabeled data
How is Office for iPad different from Office on your Mac or PC? Which features do the Office for iPad apps have, which do they lack, and how can you work around their limitations? How can you share your files among the different versions of Office? How quickly can you work without the physical keyboard and keyboard shortcuts you're used to -- and which keyboard shortcuts can you use if you connect a hardware keyboard to your iPad?
Whether you plan to write a few letters or your dissertation, run your home office away from home, or use your iPad for daily business, Pro Office for iPad will show you how to get the most out of Word, Excel, and other Office apps on your iPad. Enjoy your new freedom and still be as productive as ever with the skills and techniques you'll learn in Pro Office for iPad.
OS X and iOS Kernel Programming provides an incisive and complete introduction to the XNU kernel, which runs iPhones, iPads, iPods, and Mac OS X servers and clients. Then, you’ll expand your horizons to examine Mac OS X and iOS system architecture. Understanding Apple’s operating systems will allow you to write efficient device drivers, such as those covered in the book, using I/O Kit.
With OS X and iOS Kernel Programming, you’ll:Discover classical kernel architecture topics such as memory management and thread synchronization Become well-versed in the intricacies of the kernel development process by applying kernel debugging and profiling tools Learn how to deploy your kernel-level projects and how to successfully package them Write code that interacts with hardware devices Examine easy to understand example code that can also be used in your own projects Create network filters
Whether you’re a hobbyist, student, or professional engineer, turn to OS X andiOS Kernel Programming and find the knowledge you need to start developing
Power View is Microsoft's ground-breaking tool for ad-hoc data visualization and analysis. It's designed to produce elegant and visually arresting output. It's also built to enhance user experience through polished interactivity. Power Map is a similarly powerful mechanism for analyzing data across geographic and political units. Power Query lets you load, shape and streamline data from multiple sources. PowerPivot can extend and develop data into a dynamic model. Power BI allows you to share your findings with colleagues, and present your insights to clients.
High Impact Data Visualization with Power View, Power Map, and Power BI helps you master this suite of powerful tools from Microsoft. You'll learn to identify data sources, and to save time by preparing your underlying data correctly. You'll also learn to deliver your powerful visualizations and analyses through the cloud to PCs, tablets and smartphones.Simple techniques take raw data and convert it into information.Slicing and dicing metrics delivers interactive insight.Visually arresting output grabs and focuses attention on key indicators.
This book is an introduction to wearable computing, prototyping, and smart materials using the Arduino platform. Every chapter takes you all the way from idea to finished project. Even if you have no experience with Arduino, this book will get you set up with all the materials, software, and hardware you need; you'll complete simple projects first, and then build on your growing expertise to make more complex projects. By the end of the book, you'll have learned:
Electronics basics How to prototype successfully Arduino programming How to design and build your own wearable Arduino creations
Along the way you'll create fun and inspiring wearables, such as:An LED bracelet: learn the basics of wearable electronics A synthesizer tie: accept user input and create output in response A solar-powered glow in the dark bag: create self-sufficient wearables A shape memory flower: store state and manipulate your wearables An EL wire dress: add designer touches to your wearables A beatbox hoodie: use a voice-activated sequencer and skin resistance to create the coolest of urban wearables
Arduino Wearables is the complete guide to getting started with Arduino and wearable computing. The 10 inspiring projects to make, learn from, and build upon will equip you for creating your own projects; the only limit is your imagination.
New to this edition:
The Backstage is introduced (a new Office 2013 feature); all the ‘external’ operations like Save, Print etc. are now in one placeThe chapter on charting is totally revised and updated – Excel 2013 differs greatly from earlier versionsIncludes many new end-of-chapter problems Most chapters have been edited to improve readability
Android game app development continues to be one of the hottest areas where indies and existing game app developers seem to be most active. Android is the second best mobile apps eco and arguably even a hotter game apps eco than iOS. 3D makes your games come alive; so in this book you'll find that we go in depth on creating 3D games for the Android platform with OpenGL ES 2.0 using an original case study game called Drone Grid.
Moreover, this book offers an extensive case study with code that will be modular and re-useable helping you create your own games using advanced vertex and fragment shaders. Drone Grid is a game app case study that is somewhat similar to the best selling Geometry Wars game series utilizing a gravity grid and colorful abstract graphics and particles.
After reading and using this book, you'll be able to build your first 3D Android game app for smartphones and tablets. You may even be able to upload and sell from popular Android app stores like Google Play and Amazon Appstore.
Covering all the mathematical techniques required to resolve geometric problems and design computer programs for computer graphic applications, each chapter explores a specific mathematical topic prior to moving forward into the more advanced areas of matrix transforms, 3D curves and surface patches. Problem-solving techniques using vector analysis and geometric algebra are also discussed.
All the key areas are covered including: Numbers, Algebra, Trigonometry, Coordinate geometry, Transforms, Vectors, Curves and surfaces, Barycentric coordinates, Analytic geometry.
Plus – and unusually in a student textbook – a chapter on geometric algebra is included.
Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.
Please visit the book companion website at http://www.cs.waikato.ac.nz/ml/weka/book.html
It containsPowerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the bookOnline Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the bookTable of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projectsPresents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methodsIncludes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interfaceIncludes open-access online courses that introduce practical applications of the material in the book
Ideal for beginners and professional database and web developers, this updated third edition covers powerful features in MySQL 5.6 (and some in 5.7). The book focuses on programming APIs in Python, PHP, Java, Perl, and Ruby. With more than 200+ recipes, you’ll learn how to:Use the mysql client and write MySQL-based programsCreate, populate, and select data from tablesStore, retrieve, and manipulate stringsWork with dates and timesSort query results and generate summariesUse stored routines, triggers, and scheduled eventsImport, export, validate, and reformat dataPerform transactions and work with statisticsProcess web input, and generate web content from query resultsUse MySQL-based web session managementProvide security and server administration
See Additional Notes for instructions to download the highly interactive PC software for your school. Used in thousands of schools and colleges worldwide the software is designed to work as a traditional textbook on your PC screen.
Comprising hundreds of menu selected colourful topics where the graphic images (from your eBook) are brought to life for every value change along with many additional learning software features.
Full colour printed is available for student handouts (using your values and selections) or images and text pasted to make student assignments.
Various additional software editors are included to enable your own calculations to be explored and evaluated from simple algebraic equations to complex formulae.
A combined eBook and educational software package at a tiny fraction of the previously published price.
Table of Contents (350 software topics) Introduction, Hardware Devices, Data Structures, Data Files, Computer Systems, Data Handling, System Development, Computer Programming, Binary Numbers, Binary Arithmetic, Logic Gates 1., Logic Gates 2., Logic Families, Flip Flops, Combinational Logic, Counters, Counting, Shift Registers, Logic Interfacing, Boolean and DeMorgan's, Micro-Computer, Data/Address Bus, Memory Addressing, Arithmetic and Logic Unit, Clock and Reset, Instructions and Control, Memory Cells, Microprocessor Memory, Addressing Modes, Instructions Set 1., Instructions Set 2., Instructions Set 3., Additional Notes.
In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science.
Topics include:Statistical inference, exploratory data analysis, and the data science processAlgorithmsSpam filters, Naive Bayes, and data wranglingLogistic regressionFinancial modelingRecommendation engines and causalityData visualizationSocial networks and data journalismData engineering, MapReduce, Pregel, and Hadoop
Doing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.
SAP ERP Financial Accounting and Controlling: Configuration and Use Management is in fact the most comprehensive and easy-to-follow SAP FICO configuration book in the market. It incorporates a hands-on approach, with hundreds of screen shots and practical examples, that allows a person without prior configuration training to make SAP FICO ready for use in the enterprise. You’ll find that you don’t need to be a rocket scientist to grasp the concepts explained and apply them to your work—even when the finances are complicated, such as with the ins and outs of taxes, currency conversions, or special general ledger entries such as down payments or bills of exchange.
Providing an in-depth coverage of both configuration and end user procedures, the book covers most aspects of the SAP FICO certification syllabus—SAP’s view of the module’s key tasks and procedures—including:Configuring and using the general ledger and accounts payable and receivable screensConfiguring and completing closing procedures, asset accounting, and financial reportingConfiguring global settings and enterprise variablesAccounting for both profit and cost centersCreating a house bankIntegrating FICO with other SAP modules
Taking a jargon-free tone and providing an abundance of examples, Andrew Okungbowa provides a clear understanding of configuration techniques and the breadth of functionalities encompassed by SAP FICO. And as an accountant, Okungbowa understands the needs of end users as well as of those answering to the CIO.
This book is very practical and contains many examples that not only show you how to write code for Glass and Android Wear, but also demonstrate how to apply this code in the context of an app.
To help realize Big Data’s full potential, the book addresses numerous challenges, offering the conceptual and technological solutions for tackling them. These challenges include life-cycle data management, large-scale storage, flexible processing infrastructure, data modeling, scalable machine learning, data analysis algorithms, sampling techniques, and privacy and ethical issues.Covers computational platforms supporting Big Data applicationsAddresses key principles underlying Big Data computingExamines key developments supporting next generation Big Data platformsExplores the challenges in Big Data computing and ways to overcome themContains expert contributors from both academia and industry
The recipes included in this book are wide in scope and have been geared toward the professional developer. You'll find clear and concise code samples accompanying each recipe, and you will be presented with cutting-edge solutions that bring forth the best that the iOS 7 SDK has to offer. The recipes include:
Working with Auto Layout to build flexible user interfaces that adapt to different screen sizes Building applications that incorporate multimedia Building location-aware apps Understanding best practices for application design and development You'll find this book to be an indispensable reference for all your iOS development.
Adobe LiveCycle is all about creating efficient workflows for processing information, and this book demonstrates the full power of the various workflows available for collecting data using one of the most ubiquitous tools available—forms.Complete and thorough coverage of Adobe LiveCycle Designer ES Workflows for the design, implementation, and processing of forms Create and deploy interactive XML-based forms as HTML, PDF, or SWF Integrate forms with third-party tools
The book presents fundamental concepts of enterprise architecture with definitions and real-world applications and scenarios. It teaches data managers and planners about the challenges of building a data architecture roadmap, structuring the right team, and building a long term set of solutions. It includes the detail needed to illustrate how the fundamental principles are used in current business practice. The book is divided into five sections, one of which addresses the software-application development process, defining tools, techniques, and methods that ensure repeatable results.
Data Architecture is intended for people in business management involved with corporate data issues and information technology decisions, ranging from data architects to IT consultants, IT auditors, and data administrators. It is also an ideal reference tool for those in a higher-level education process involved in data or information technology management.Presents fundamental concepts of enterprise architecture with definitions and real-world applications and scenariosTeaches data managers and planners about the challenges of building a data architecture roadmap, structuring the right team, and building a long term set of solutions Includes the detail needed to illustrate how the fundamental principles are used in current business practice
Author David Greenberg shows you how Mesos manages your entire datacenter as a single logical entity, eliminating the need to assign fixed sets of machines to applications. You’ll quickly discover why Mesos is the ultimate DevOps tool.Understand Mesos architecture, and learn how it manages CPU, memory, and other resources across a clusterBuild an application on top of Mesos with Marathon, a platform for hosting services on MesosCreate new, production-ready frameworks for MesosWrite a custom executor to provide richer interaction between the Mesos scheduler and workersDive into advanced topics, including the reconciliation process, Docker integration, dynamic reservations, and persistent volumesLearn about today’s Mesos initiatives that will likely become tomorrow’s features
This valuable handbook has attracted scores of contributors since the European Journalism Centre and the Open Knowledge Foundation launched the project at MozFest 2011. Through a collection of tips and techniques from leading journalists, professors, software developers, and data analysts, you’ll learn how data can be either the source of data journalism or a tool with which the story is told—or both.Examine the use of data journalism at the BBC, the Chicago Tribune, the Guardian, and other news organizationsExplore in-depth case studies on elections, riots, school performance, and corruptionLearn how to find data from the Web, through freedom of information laws, and by "crowd sourcing"Extract information from raw data with tips for working with numbers and statistics and using data visualizationDeliver data through infographics, news apps, open data platforms, and download links
Android Game Recipes is your first, reliable game coding reference for today's Android game apps. This book provides easy to follow real world game code problems and solutions, including source code.
This book covers code recipe solutions that are common to 2D game development problems such as designing a game menu, collision detection, moving characters, moving backgrounds and more. This book also includes how to work with player input, how to add multiple levels, how to create game graphics for different screen resolution, and how to work with device sensors.
After reading and using this book, you'll have the templated code snippets, solutions and frameworks to apply to your game app design to build your game, customize it, and then sell it on the Android app stores.