Data capture and analysis

The surging predictive analytics market is expected to grow from $10.

Data is powerful.

In one short decade, the internet has become a critical part of our everyday lives.

Construct a robust end-to-end solution for analyzing and visualizing streaming data Real-time analytics is the hottest topic in data analytics today.

Speed up the design and implementation of deep learning solutions using Apache SparkKey FeaturesExplore the world of distributed deep learning with Apache SparkTrain neural networks with deep learning libraries such as BigDL and TensorFlowDevelop Spark deep learning applications to intelligently handle large and complex datasetsBook DescriptionDeep learning is a subset of machine learning where datasets with several layers of complexity can be processed.

Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and methods for mining patterns, knowledge, and models from various kinds of data for diverse applications.

In this explosive memoir, a political consultant and technology whistleblower reveals the disturbing truth about the multi-billion-dollar data industry, revealing to the public how companies are getting richer using our personal information and exposing how Cambridge Analytica exploited weaknesses in privacy laws to help elect Donald Trump.

The migration of data is an important process when introducing SAP systems or adopting new data from third-party systems.

An intuitive, up-to-date introduction to random matrix theory and free calculus, with real world illustrations and Big Data applications.

Von einfachen Routineaufgaben bis zu komplexen Geschäftsprozessen – Automatisierung ohne Programmierkenntnisse- Sich wiederholende Aufgaben ganz einfach automatisieren- Geschäftsprozesse ohne manuelle Eingaben abwickeln- Flows mit Templates erstellen oder komplett neu entwerfen Die effiziente Verarbeitung von Informationen ist für den erfolgreichen Betrieb moderner Unternehmen von entscheidender Bedeutung.

Information and how we manage, process and govern it is becoming increasingly important as organizations ride the wave of the big data revolution.

Over insightful 90 recipes to get lightning-fast analytics with Apache SparkAbout This BookUse Apache Spark for data processing with these hands-on recipesImplement end-to-end, large-scale data analysis better than ever beforeWork with powerful libraries such as MLLib, SciPy, NumPy, and Pandas to gain insights from your dataWho This Book Is ForThis book is for novice and intermediate level data science professionals and data analysts who want to solve data science problems with a distributed computing framework.

Master machine learning techniques with real-world projects that interface TensorFlow with R, H2O, MXNet, and other languagesKey FeaturesGain expertise in machine learning, deep learning and other techniquesBuild intelligent end-to-end projects for finance, social media, and a variety of domainsImplement multi-class classification, regression, and clusteringBook DescriptionR is one of the most popular languages when it comes to exploring the mathematical side of machine learning and easily performing computational statistics.

Speed up the design and implementation of deep learning solutions using Apache SparkKey FeaturesExplore the world of distributed deep learning with Apache SparkTrain neural networks with deep learning libraries such as BigDL and TensorFlowDevelop Spark deep learning applications to intelligently handle large and complex datasetsBook DescriptionDeep learning is a subset of machine learning where datasets with several layers of complexity can be processed.

Online social networking sites like Facebook, LinkedIn, and Twitter, offer millions of members the opportunity to befriend one another, send messages to each other, and post content on the site - actions which generate mind-boggling amounts of data every day.

Learn Azure's cloud capabilities with the help of this introductory guide to employing Azure for your cloud infrastructure needs.

If youre a business team leader, CIO, business analyst, or developer interested in how Apache Hadoop and Apache HBase-related technologies can address problems involving large-scale data in cost-effective ways, this book is for you.

Get going with tidymodels, a collection of R packages for modeling and machine learning.

Learn to view, edit and analyse geospatial data using QGIS and Python 3Key FeaturesLeverage the power of QGIS to add professionalism to your mapsExplore and work with the newly released features like Python 3, GeoPackage, 3D views, Print layouts in QGIS 3.

An updated edition on membrane biology, providing new high resolution structures of membrane proteins and insights into how they function.

Meta-Analytics: Consensus Approaches and System Patterns for Data Analysis presents an exhaustive set of patterns for data science to use on any machine learning based data analysis task.

The immense increase on the size and type of real time data generated across various edge computing platform results in unstructured databases and data silos.

Explore the different data mining techniques using the libraries and packages offered by PythonKey FeaturesGrasp the basics of data loading, cleaning, analysis, and visualizationUse the popular Python libraries such as NumPy, pandas, matplotlib, and scikit-learn for data miningYour one-stop guide to build efficient data mining pipelines without going into too much theoryBook DescriptionData mining is a necessary and predictable response to the dawn of the information age.

Data Simplification: Taming Information With Open Source Tools addresses the simple fact that modern data is too big and complex to analyze in its native form.

Provides a summary of the key developments of a decade of research into the area of data exchange.

There is an easier way to build Hadoop applications.

Decision Support Systems for Sustainable Computing investigates recent technological advances in decision support systems models designed to solve real world applications.

Regarding the set of all feature attributes in a given database as the universal set, this monograph discusses various nonadditive set functions that describe the interaction among the contributions from feature attributes towards a considered target attribute.

Make sense of your data and predict the unpredictableAbout This BookA unique book that centers around develop six key practical skills needed to develop and implement predictive analyticsApply the principles and techniques of predictive analytics to effectively interpret big dataSolve real-world analytical problems with the help of practical case studies and real-world scenarios taken from the world of healthcare, marketing, and other business domainsWho This Book Is ForThis book is for those with a mathematical/statistics background who wish to understand the concepts, techniques, and implementation of predictive analytics to resolve complex analytical issues.

Data Science and Analytics explores the solutions to problems in society, environment and in industry.

Master the intricacies of Elasticsearch 7.

A practical guide to data mining using SQL and Excel Data Analysis Using SQL and Excel, 2nd Edition shows you how to leverage the two most popular tools for data query and analysis SQL and Excel to perform sophisticated data analysis without the need for complex and expensive data mining tools.

A good visualization can communicate the nature and potential impact of ideas more powerfully than any other form of communication.

Python is a first-class tool for many researchers, primarily because of its libraries for storing, manipulating, and gaining insight from data.

Implement blockchain principles in your choice of domain using Ethereum Key FeaturesBuild permissioned enterprise-grade blockchain applications from scratchImplement Blockchain-as-a-Service to enterprises in terms of deployment and securityAchieve privacy in blockchains using proxy re-encryption algorithmsBook DescriptionThe increasing growth in blockchain use is enormous, and it is changing the way business is done.

Network Re-Engineering: Foundations of Enterprise Computing deals with the aspects of an organization's information systems and communications assets.

Data Analysis for Social Microblogging Platforms explores the nature of microblog datasets, also covering the larger field which focuses on information, data and knowledge in the context of natural language processing.

Design clever algorithms that discover hidden patterns and draw responses from unstructured, unlabeled data.

Die Migration von Daten ist ein wichtiger Prozess bei der Einführung von SAP Systemen oder der Übernahme neuer Daten aus Fremdsystemen.

Data-gathering technology is more sophisticated than ever, as are the ethical standards for using this data.

Meeting the Challenges of Data Quality Management outlines the foundational concepts of data quality management and its challenges.

Understand the Ethereum platform to build distributed applications that are secured and decentralized using blockchain technologyKey FeaturesBuild your own decentralized applications using real-world blockchain examplesImplement Ethereum for building smart contracts and cryptocurrency applications with easy-to-follow projectsEnhance your application security with blockchainBook DescriptionEthereum enables the development of efficient, smart contracts that contain code.

Die praktische Anleitung für den Umgang mit großen Datenmengen:- Stets aktuelle Auswertungen umfangreicher externer Daten- Anschauliche Anleitungen mit Beispielen zum DownloadSie benötigen laufend aktuelle Daten aus externen Quellen?

Business Intelligence Strategy and Big Data Analytics is written for business leaders, managers, and analysts - people who are involved with advancing the use of BI at their companies or who need to better understand what BI is and how it can be used to improve profitability.

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice.