Big data
Resource Information
The concept Big data represents the subject, aboutness, idea or notion of resources found in University of Missouri Libraries.
The Resource
Big data
Resource Information
The concept Big data represents the subject, aboutness, idea or notion of resources found in University of Missouri Libraries.
- Label
- Big data
- Authority link
- http://id.worldcat.org/fast/01892965
- Source
- fast
100+ Items that share the Concept Big data
Context
Context of Big dataSubject of
- Addressing data volume, velocity, and variety with IBM InfoSphere Streams V3.0
- Advanced analytics with Spark
- Advanced analytics with Spark : patterns from learning from data at scale
- Advances in information systems set, Volume 1, From big data to smart data
- Analiza danych w bizenesie : Sztuka podejmowania skutecznych decyzji
- Analytics and dynamic customer strategy : big profits from big data
- Analytics in a big data world : the essential guide to data science and its applications
- Apache Nifi fundamentals
- Apache Oozie essentials : unleash the power of Apache Oozie to create and manage your big data and machine learning pipelines in one go
- Apache Spark 2.x cookbook : Cloud-ready recipes to do analytics and data science on Apache Spark
- Apache Spark for Data Science Cookbook
- Apache Spark machine learning blueprints : develop a range of cutting-edge machine learning projects with Apache Spark using this actionable guide
- Application of big data for national security : a practitioner's guide to emerging technologies
- Applications of network analysis in psychology
- Applied business analytics : integrating business process, big data, and advanced analytics
- Architecting HBase applications : a guidebook for successful development and design
- Artificial intelligence for fashion : how AI is revolutionizing the fashion industry
- Azure IoT development cookbook : develop and manage robust IoT solutions
- BI & Analytics in der Cloud : Architektur, Vorgehen und Praxis
- Badanie danych Raport z pierwszej linii działań
- Beginning big data with Power BI and Excel 2013
- Beyond big data : using social MDM to drive deep customer insight
- Big Data : Entwicklung und Programmierung von Systemen für große Datenmengen und Einsatz der Lambda-Architektur
- Big Data For Dummies
- Big Data in Education : The Digital Future of Learning, Policy and Practice
- Big Data--Fluch oder Segen? : Unternehmen im Spiegel gesellschaftlichen Wandels
- Big data : a business and legal guide
- Big data : algorithms, analytics, and applications
- Big data : principles and best practices of scalable real-time data systems
- Big data : seizing opportunities, preserving values
- Big data SMACK : a guide to Apache Spark, Mesos, Akka, Cassandra, and Kafka
- Big data analytics : a handy reference guide for data analysts and data scientists to help obtain value from big data analytics using Spark on Hadoop clusters
- Big data analytics : from strategic planning to enterprise integration with tools, techniques, NoSQL, and graph
- Big data analytics beyond Hadoop : real-time applications with Storm, Spark, and more Hadoop alternatives
- Big data analytics using Splunk
- Big data analytics with Spark : a practitioner's guide to using Spark for large-scale data processing, machine learning, and graph analytics, and high-velocity data stream processing
- Big data and health analytics
- Big data and learning analytics in higher education : current theory and practice
- Big data and the internet of things : enterprise information architecture for a new age
- Big data application architecture Q & A : a problem-solution approach
- Big data at work : the data science revolution and organizational psychology
- Big data bootcamp : what managers need to know to profit from the big data revolution
- Big data driven supply chain management : a framework for implementing analytics and turning information into intelligence
- Big data factories : collaborative approaches
- Big data for chimps : a guide to massive-scale data processing in practice
- Big data forensics--learning Hadoop investigations : perform forensic investigations on Hadoop clusters with cutting-edge tools and techniques
- Big data fundamentals : concepts, drivers & techniques
- Big data fundamentals : concepts, drivers & techniques
- Big data imperatives : enterprise big data warehouse, BI implementations and analytics
- Big data research
- Big data visualization : learn effective tools and techniques to separate big data into manageable and logical components for efficient data visualization
- Big data, big innovation : enabling competitive differentiation through business analytics
- Big data, data mining and machine learning : value creation for business leaders and practitioners
- Big data-enabled nursing : education, research and practice
- Big data? : qualitative approaches to digital research
- Big learning data
- Business analytics : an introduction
- Business intelligence strategy and big data analytics : a general management perspective
- Ceph cookbook : over 100 effective recipes to help you design, implement, and manage the software-defined and massively scalable Ceph storage system
- Cloud computing and big data
- Cloudera Impala
- Complete guide to open source big data stack
- Creating value with big data analytics : making smarter marketing decisions
- Current state of big data use in retail supply chains
- Data Lake development with Big Data : explore architectural approaches to building Data Lakes that ingest, index, manage, and analyze massive amounts of data using Big Data technologies
- Data algorithms : recipes for scaling up with Hadoop and Spark
- Data analysis with Stata : explore the big data field and learn how to perform data analytics and predictive modeling in Stata
- Data architecture : a primer for the data scientist : big data, data warehouse and data vault
- Data catalogs may be the new black, but metadata is not cabbage
- Data crush : how the information tidal wave is driving new business opportunities
- Data divination : big data strategies
- Data just right : introduction to large-scale data & analytics
- Data marketing for dummies
- Data science : create teams that ask the right questions and deliver real value
- Data science and big data analytics : discovering, analyzing, visualizing and presenting data
- Data science for business
- Data scientist : the definitive guide to becoming a data scientist
- Data strategy and the enterprise data executive : ensuring that business and IT are in synch in the post-big data era
- Data warehousing in the age of big data
- Databusting for schools : how to use and interpret education data
- Decision analytics : Microsoft Excel
- Deep learning with Hadoop : build, implement and scale distributed deep learning models for large-scale datasets
- Designing and operating a data reservoir
- Designing software architectures : a practical approach
- Developing Analytic Talent : Becoming a Data Scientist
- Digital dominance : the power of Google, Amazon, Facebook, and Apple
- Digital exhaust : what everyone should know about big data, digitization, and digitally driven innovation
- Disruptive possibilities : how big data changes everything
- Doing data science
- E-renovarse o morir : 7 tendencias tecnológicas para convertirte en un líder digital : realidad aumentada, gamificación, drones, impresoras 3D, bioimpresión, internet de las cosas, big data
- Elasticsearch : Ein praktischer Einstieg
- Enterprise business intelligence and data warehousing : program management essentials
- Entity information life cycle for big data : master data management and information integration
- Fact-based data integration : matching and transformation
- Fast data processing systems with SMACK stack
- Fast data processing systems with SMACK stack : combine the incredible powers of Spark, Mesos, Akka, Cassandra, and Kafka to build data processing platforms that can take on even the hardest of your data troubles
- Fast data processing with Spark : high-speed distributed computing made easy with Spark
- Feature engineering made easy : identify unique features from your dataset in order to build powerful machine learning systems
- Fog computing, deep learning and big data analytics-research directions
- Frank Kane's Taming big data with Apache Spark and Python : real-world examples to help you analyze large datasets with Apache Spark
- Getting started with Greenplum for big data analytics : a hands-on guide on how to execute an analytics project from conceptualization to operationalization using Greenplum
- Getting started with Impala
- Global managerial perspectives of big data strategy in supply chain management
- Green information technology : a sustainable approach
- Growing business intelligence : an agile approach to leveraging data and analytics for maximum business value
- HDInsight essentials : learn how to build and deploy a modern big data architecture to empower your business
- Hadoop 2 Quick-Start Guide : Learn the Essentials of Big Data Computing in the Apache Hadoop 2 Ecosystem
- Hadoop application architectures
- Hadoop backup and recovery solutions : learn the best strategies for data recovery from Hadoop backup clusters and troubleshoot problems
- Hadoop blueprints : use Hadoop to solve business problems by learning from a rich set of real-life case studies
- Hadoop for finance essentials : harness big data to provide meaningful insights, analytics, and business intelligence for your financial institution
- Hands-on big data analytics with PySpark : analyze large datasets and discover techniques for testing, immunizing, and parallelizing Spark jobs
- Harness oil and gas big data with analytics : optimize exploration and production with data driven models
- High performance Spark : best practices for scaling and optimizing Apache Spark
- How 'big data' is different
- IBM Technical Computing Clouds
- IBM information governance solutions
- IEEE transactions on big data
- Implementing Splunk : a comprehensive guide to help you transform big data into valuable business insights with Splunk 6.2
- Implementing Splunk : big data reporting and development for operational intelligence ...
- Implementing an IBM Infosphere BigInsights Cluster using Linux on Power
- Information governace principles and practices for a big data landscape
- Information management : strategies for gaining a competitive advantage with data
- Innovative applications of big data in the railway industry
- Intertwingled
- Introducing data science : big data, machine learning, and more, using Python tools
- Introduction to Apache Flink : stream processing for real time and beyond
- IoT solutions in Microsoft's Azure IoT suite : data acquisition and analysis in the real world
- Journal of big data
- Journal of big data
- Kognitio architecture and SQL
- Learning Apache Flink
- Learning Cascading : build reliable, robust, and high-performance big data applications using the Cascading application development efficiently
- Learning Hadoop 2 : design and implement data processing, lifecycle management, and analytic workflows with the cutting-edge toolbox of Hadoop 2
- Learning Hunk : visualize and analyze your Hadoop data using Hunk
- Learning PySpark
- Learning Spark : lightening fast data analysis
- Learning Spark SQL
- Learning big data with Amazon Elastic MapReduce : easily learn, build, and execute real-world Big Data solutions using Hadoop and AWS EMR
- Learning programmatic access to MongoDB
- Learning to love data science : explorations of emerging technologies and platforms for predictive analytics, machine learning, digital manufacturing, and supply chain optimization
- Machine learning with Go : implement regression, classification, clustering, time-series models, neural networks, and more using the Go programming language
- Making Big Data Work for Your Business
- Mastering Ceph : redefine your storage system
- Mastering Hadoop 3 : big data processing at scale to unlock unique business insights
- Mastering Spark for data science
- Mastering Splunk : optimize your machine-generated data effectively by developing advanced analytics with Splunk
- Mastering data-intensive collaboration and decision making : research and practical applications in the Dicode Project
- Mastering the SAS DS2 Procedure : Advanced Data-Wrangling Techniques, Second Edition
- Mastering the SAS DS2 procedure : advanced data wrangling techniques
- Mining of massive datasets
- Modern enterprise business intelligence and data management : a roadmap for IT directors, managers, and architects
- Monitoring Hadoop : get to grips with the intricacies of Hadoop monitoring using the power of Ganglia and Nagios
- MySQL 8 for big data : effective data processing with MySQL 8, Hadoop, NoSQL APIs, and other big data tools
- Optimize your greatest asset--your people : how to apply analytics to big data to improve your human capital investments
- Outside-in marketing : using big data to guide your content marketing
- Pentaho for Big Data Analytics
- Perspectives on big data analysis : methodologies and applications : International Workshop on Perspectives on High-Dimension Data Anlaysis II, May 30-June 1, 2012, Centre de Recherches Mathématiques, Université de Montréal, Montréal
- Practical MongoDB : architecting, developing, and administering MongoDB
- Practical big data analytics : hands-on techniques to implement enterprise analytics and machine learning using Hadoop, Spark, NoSQL and R
- Practical business analytics using SAS : a hands-on guide
- Practical graph analytics with Apache Giraph
- Practical real-time data processing and analytics : distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka
- Predictive analytics with TensorFlow : implement deep learning principles to predict valuable insights using TensorFlow
- Principles of big data : preparing, sharing, and analyzing complex information
- Pro Apache Hadoop
- Pro Microsoft HDInsight : Hadoop on Windows
- Pro Spark streaming : the zen of real-time analytics using Apache Spark
- Processing big data with Azure HDInsight : building real-world big data systems on Azure HDInsight using the Hadoop ecosystem
- Professional Hadoop solutions
- Programming Elastic MapReduce
- PySpark SQL Recipes : with HiveQL, Dataframe and Graphframes
- Python for finance : financial modeling and quantitative analysis explained
- R for data science : import, tidy, transform, visualize, and model data
- Real-time big data analytics : design, process, and analyze large sets of complex data in real time
- Real-time big data analytics : emerging architecture
- Real-world data mining : applied business analytics and decision making
- Reality mining : using big data to engineer a better world
- Reliability assurance of big data in the cloud : cost-effective replication-based storage
- SAP Lumira essentials : discover how to make your business data more interactive and engaging with SAP Lumira
- SAS Viya : the Python perspective
- Sams teach yourself : big data analytics with Microsoft HDInsight in 24 hours
- Sams teach yourself Hadoop in 24 hours
- Scala and Spark for big data analytics : tame big data with Scala and Apache Spark!
- Scalable big data architecture : a practitioner's guide to choosing relevant big data architecture
- Smarter decisions - the intersection of internet of things and decision science : enter the world of internet of things with the power of data science with this highly practical, engaging book
- Social sensing : building reliable systems on unreliable data
- Software architecture for big data and the cloud
- Spark : big data cluster computing in production
- Spark cookbook : over 60 recipes on Spark, covering Spark Core, Spark SQL, Spark Streaming, MLib, and GraphX libraries
- Spark for data science : analyze your data and delve deep into the world of machine learning with the latest Spark version, 2.0
- Spark in motion
- Spark, the definitive guide : big data processing made simple
- Splunk : enterprise operational intelligence delivered : demystify big data and discover how to bring operational intelligence to your data to revolutionize your work
- Splunk Essentials - Second Edition
- Splunk best practices : design, implement, and publish custom Splunk applications by following best practices
- Splunk operational intelligence cookbook : over 70 practical recipes to gain operational data intelligence with Splunk Enterprise
- Statistics for big data for dummies
- Statistics for data science : leverage the power of statistics for data analysis, classification, regression, machine learning, and neural networks
- Storm blueprints : patterns for distributed real-time computation : use storm design patterns to perform distributed, real-time big data processing, and analytics for real-world use cases
- Storm real-time processing cookbook
- Strata Data Conference : London, UK 2018
- Strategic analytics and SAS : using aggregate data to drive organizational initiatives
- Stream processing with Apache Flink : fundamentals, implementation, and operation of streaming applications
- Streaming, sharing, stealing : big data and the future of entertainment
- Structured search for big data : from keywords to key-objects
- Talend for Big Data
- TensorFlow : powerful predictive analytics with TensorFlow : predict valuable insights of your data with TensorFlow
- The DS2 procedure : SAS programming methods at work
- The accidental data scientist : big data applications and opportunities for librarians and information professionals
- The analytic hospitality executive : implementing data analytics in hotels and casinos
- The data and analytics playbook : proven methods for governed data and analytic quality
- The new rules of sales and service : how to use agile selling, real-time customer engagement, big data, content, and storytelling to grow your business
- The new rules of sales and service : how to use agile selling, real-time customer engagement, big data, content, and storytelling to grow your business
- The visual imperative : creating a visual culture of data discovery
- The visual organization : data visualization, big data, and the quest for better decisions
- Think bigger : developing a successful big data strategy for your business
- Think like a data scientist : tackle the data science process step-by-step
- Threat forecasting : leveraging big data for predictive analysis
- Understanding big data scalability, Part 1,
- Using simulated experience to make sense of big data
- Why your company needs data translators : In many organizations, there remains a consistent disconnect between data scientists and the executive decision makers they support. That{u2019}s why it{u2019}s time for a new role: the data translator
- Zwinna analiza danych : Apache Hadoop dla każdego
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.library.missouri.edu/resource/OW5yZISLFPs/" typeof="CategoryCode http://bibfra.me/vocab/lite/Concept"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.library.missouri.edu/resource/OW5yZISLFPs/">Big data</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.library.missouri.edu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.library.missouri.edu/">University of Missouri Libraries</a></span></span></span></span></div>
