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Big Data Application in Power Systems

Big Data Application in Power Systems Book
Author : Reza Arghandeh,Yuxun Zhou
Publisher : Elsevier Science
Release : 2017-09-01
ISBN : 9780128119686
Language : En, Es, Fr & De

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Book Description :

Big Data Application in Power Systems brings together experts from academia, industry and regulatory agencies who share their understanding and discuss the big data analytics applications for power systems diagnostics, operation and control. Recent developments in monitoring systems and sensor networks dramatically increase the variety, volume and velocity of measurement data in electricity transmission and distribution level. The book focuses on rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches to process high dimensional, heterogeneous and spatiotemporal data. The book chapters discuss challenges, opportunities, success stories and pathways for utilizing big data value in smart grids. Provides expert analysis of the latest developments by global authorities Contains detailed references for further reading and extended research Provides additional cross-disciplinary lessons learned from broad disciplines such as statistics, computer science and bioinformatics Focuses on rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches to process high dimensional, heterogeneous and spatiotemporal data

Big Data Application in Power Systems

Big Data Application in Power Systems Book
Author : Reza Arghandeh,Yuxun Zhou
Publisher : Elsevier
Release : 2017-11-27
ISBN : 0128119691
Language : En, Es, Fr & De

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Book Description :

Big Data Application in Power Systems brings together experts from academia, industry and regulatory agencies who share their understanding and discuss the big data analytics applications for power systems diagnostics, operation and control. Recent developments in monitoring systems and sensor networks dramatically increase the variety, volume and velocity of measurement data in electricity transmission and distribution level. The book focuses on rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches to process high dimensional, heterogeneous and spatiotemporal data. The book chapters discuss challenges, opportunities, success stories and pathways for utilizing big data value in smart grids. Provides expert analysis of the latest developments by global authorities Contains detailed references for further reading and extended research Provides additional cross-disciplinary lessons learned from broad disciplines such as statistics, computer science and bioinformatics Focuses on rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches to process high dimensional, heterogeneous and spatiotemporal data

Big Data Analytics in Future Power Systems

Big Data Analytics in Future Power Systems Book
Author : Ahmed F. Zobaa,Trevor J. Bihl
Publisher : CRC Press
Release : 2018-08-14
ISBN : 1351601296
Language : En, Es, Fr & De

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Book Description :

Power systems are increasingly collecting large amounts of data due to the expansion of the Internet of Things into power grids. In a smart grids scenario, a huge number of intelligent devices will be connected with almost no human intervention characterizing a machine-to-machine scenario, which is one of the pillars of the Internet of Things. The book characterizes and evaluates how the emerging growth of data in communications networks applied to smart grids will impact the grid efficiency and reliability. Additionally, this book discusses the various security concerns that become manifest with Big Data and expanded communications in power grids. Provide a general description and definition of big data, which has been gaining significant attention in the research community. Introduces a comprehensive overview of big data optimization methods in power system. Reviews the communication devices used in critical infrastructure, especially power systems; security methods available to vet the identity of devices; and general security threats in CI networks. Presents applications in power systems, such as power flow and protection. Reviews electricity theft concerns and the wide variety of data-driven techniques and applications developed for electricity theft detection.

Innovation in Energy Systems

Innovation in Energy Systems Book
Author : Taha Selim Ustun
Publisher : BoD – Books on Demand
Release : 2019-11-27
ISBN : 1789841070
Language : En, Es, Fr & De

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Book Description :

It has been a little over a century since the inception of interconnected networks and little has changed in the way that they are operated. Demand-supply balance methods, protection schemes, business models for electric power companies, and future development considerations have remained the same until very recently. Distributed generators, storage devices, and electric vehicles have become widespread and disrupted century-old bulk generation - bulk transmission operation. Distribution networks are no longer passive networks and now contribute to power generation. Old billing and energy trading schemes cannot accommodate this change and need revision. Furthermore, bidirectional power flow is an unprecedented phenomenon in distribution networks and traditional protection schemes require a thorough fix for proper operation. This book aims to cover new technologies, methods, and approaches developed to meet the needs of this changing field.

Big Data Analytics in Future Power Systems

Big Data Analytics in Future Power Systems Book
Author : Ahmed F. Zobaa,Trevor J. Bihl
Publisher : CRC Press
Release : 2018
ISBN : 9781138095885
Language : En, Es, Fr & De

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Book Description :

Power systems are increasingly collecting large amounts of data due to the expansion of the Internet of Things into power grids. In a smart grids scenario, a huge number of intelligent devices will be connected with almost no human intervention characterizing a machine-to-machine scenario, which is one of the pillars of the Internet of Things. The book characterizes and evaluates how the emerging growth of data in communications networks applied to smart grids will impact the grid efficiency and reliability. Additionally, this book discusses the various security concerns that become manifest with Big Data and expanded communications in power grids. Provide a general description and definition of big data, which has been gaining significant attention in the research community. Introduces a comprehensive overview of big data optimization methods in power system. Reviews the communication devices used in critical infrastructure, especially power systems; security methods available to vet the identity of devices; and general security threats in CI networks. Presents applications in power systems, such as power flow and protection. Reviews electricity theft concerns and the wide variety of data-driven techniques and applications developed for electricity theft detection.

Enterprise Data Warehouse Optimization with Hadoop on IBM Power Systems Servers

Enterprise Data Warehouse Optimization with Hadoop on IBM Power Systems Servers Book
Author : Scott Vetter,Helen Lu,Maciej Olejniczak,IBM Redbooks
Publisher : IBM Redbooks
Release : 2018-01-31
ISBN : 0738456608
Language : En, Es, Fr & De

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Book Description :

Data warehouses were developed for many good reasons, such as providing quick query and reporting for business operations, and business performance. However, over the years, due to the explosion of applications and data volume, many existing data warehouses have become difficult to manage. Extract, Transform, and Load (ETL) processes are taking longer, missing their allocated batch windows. In addition, data types that are required for business analysis have expanded from structured data to unstructured data. The Apache open source Hadoop platform provides a great alternative for solving these problems. IBM® has committed to open source since the early years of open Linux. IBM and Hortonworks together are committed to Apache open source software more than any other company. IBM Power SystemsTM servers are built with open technologies and are designed for mission-critical data applications. Power Systems servers use technology from the OpenPOWER Foundation, an open technology infrastructure that uses the IBM POWER® architecture to help meet the evolving needs of big data applications. The combination of Power Systems with Hortonworks Data Platform (HDP) provides users with a highly efficient platform that provides leadership performance for big data workloads such as Hadoop and Spark. This IBM RedpaperTM publication provides details about Enterprise Data Warehouse (EDW) optimization with Hadoop on Power Systems. Many people know Power Systems from the IBM AIX® platform, but might not be familiar with IBM PowerLinuxTM, so part of this paper provides a Power Systems overview. A quick introduction to Hadoop is provided for those not familiar with the topic. Details of HDP on Power Reference architecture are included that will help both software architects and infrastructure architects understand the design. In the optimization chapter, we describe various topics: traditional EDW offload, sizing guidelines, performance tuning, IBM Elastic StorageTM Server (ESS) for data-intensive workload, IBM Big SQL as the common structured query language (SQL) engine for Hadoop platform, and tools that are available on Power Systems that are related to EDW optimization. We also dedicate some pages to the analytics components (IBM Data Science Experience (IBM DSX) and IBM SpectrumTM Conductor for Spark workload) for the Hadoop infrastructure.

Handbook of Research on Big Data Storage and Visualization Techniques

Handbook of Research on Big Data Storage and Visualization Techniques Book
Author : Segall, Richard S.,Cook, Jeffrey S.
Publisher : IGI Global
Release : 2018-01-05
ISBN : 1522531432
Language : En, Es, Fr & De

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Book Description :

The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. The Handbook of Research on Big Data Storage and Visualization Techniques is a critical scholarly resource that explores big data analytics and technologies and their role in developing a broad understanding of issues pertaining to the use of big data in multidisciplinary fields. Featuring coverage on a broad range of topics, such as architecture patterns, programing systems, and computational energy, this publication is geared towards professionals, researchers, and students seeking current research and application topics on the subject.

AI and Big Data on IBM Power Systems Servers

AI and Big Data on IBM Power Systems Servers Book
Author : Scott Vetter,Ivaylo B. Bozhinov,Anto A John,Rafael Freitas de Lima,Ahmed.(Mash) Mashhour,James Van Oosten,Fernando Vermelho,Allison White,IBM Redbooks
Publisher : IBM Redbooks
Release : 2019-04-10
ISBN : 0738457515
Language : En, Es, Fr & De

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Book Description :

As big data becomes more ubiquitous, businesses are wondering how they can best leverage it to gain insight into their most important business questions. Using machine learning (ML) and deep learning (DL) in big data environments can identify historical patterns and build artificial intelligence (AI) models that can help businesses to improve customer experience, add services and offerings, identify new revenue streams or lines of business (LOBs), and optimize business or manufacturing operations. The power of AI for predictive analytics is being harnessed across all industries, so it is important that businesses familiarize themselves with all of the tools and techniques that are available for integration with their data lake environments. In this IBM® Redbooks® publication, we cover the best practices for deploying and integrating some of the best AI solutions on the market, including: IBM Watson Machine Learning Accelerator (see note for product naming) IBM Watson Studio Local IBM Power SystemsTM IBM SpectrumTM Scale IBM Data Science Experience (IBM DSX) IBM Elastic StorageTM Server Hortonworks Data Platform (HDP) Hortonworks DataFlow (HDF) H2O Driverless AI We map out all the integrations that are possible with our different AI solutions and how they can integrate with your existing or new data lake. We also walk you through some of our client use cases and show you how some of the industry leaders are using Hortonworks, IBM PowerAI, and IBM Watson Studio Local to drive decision making. We also advise you on your deployment options, when to use a GPU, and why you should use the IBM Elastic Storage Server (IBM ESS) to improve storage management. Lastly, we describe how to integrate IBM Watson Machine Learning Accelerator and Hortonworks with or without IBM Watson Studio Local, how to access real-time data, and security. Note: IBM Watson Machine Learning Accelerator is the new product name for IBM PowerAI Enterprise. Note: Hortonworks merged with Cloudera in January 2019. The new company is called Cloudera. References to Hortonworks as a business entity in this publication are now referring to the merged company. Product names beginning with Hortonworks continue to be marketed and sold under their original names.

Application of Machine Learning and Deep Learning Methods to Power System Problems

Application of Machine Learning and Deep Learning Methods to Power System Problems Book
Author : Morteza Nazari-Heris,Somayeh Asadi,Behnam Mohammadi-Ivatloo,Moloud Abdar,Houtan Jebelli,Milad Sadat-Mohammadi
Publisher : Springer Nature
Release : 2021-11-21
ISBN : 3030776964
Language : En, Es, Fr & De

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Book Description :

This book evaluates the role of innovative machine learning and deep learning methods in dealing with power system issues, concentrating on recent developments and advances that improve planning, operation, and control of power systems. Cutting-edge case studies from around the world consider prediction, classification, clustering, and fault/event detection in power systems, providing effective and promising solutions for many novel challenges faced by power system operators. Written by leading experts, the book will be an ideal resource for researchers and engineers working in the electrical power engineering and power system planning communities, as well as students in advanced graduate-level courses.

Decision Making Applications in Modern Power Systems

Decision Making Applications in Modern Power Systems Book
Author : Shady H.E. Abdel Aleem,Almoataz Youssef Abdelaziz,Ahmed F. Zobaa,Ramesh Bansal
Publisher : Academic Press
Release : 2019-09-21
ISBN : 0128166266
Language : En, Es, Fr & De

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Book Description :

Decision Making Applications in Modern Power Systems presents an enhanced decision-making framework for power systems. Designed as an introduction to enhanced electricity system analysis using decision-making tools, it provides an overview of the different elements, levels and actors involved within an integrated framework for decision-making in the power sector. In addition, it presents a state-of-play on current energy systems, strategies, alternatives, viewpoints and priorities in support of decision-making in the electric power sector, including discussions of energy storage and smart grids. As a practical training guide on theoretical developments and the application of advanced methods for practical electrical energy engineering problems, this reference is ideal for use in establishing medium-term and long-term strategic plans for the electric power and energy sectors. Provides panoramic coverage of state-of-the-art energy systems, strategies and priorities in support of electrical power decision-making Introduces innovative research outcomes, programs, algorithms and approaches to address challenges in understanding, creating and managing complex techno-socio-economic engineering systems Includes practical training on theoretical developments and the application of advanced methods for realistic electrical energy engineering problems

Design and Optimization of Biogas Energy Systems

Design and Optimization of Biogas Energy Systems Book
Author : Prashant Baredar,Vikas Khare,Savita Nema
Publisher : Academic Press
Release : 2020-06-18
ISBN : 0128227192
Language : En, Es, Fr & De

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Book Description :

Design and Optimization of Biogas Energy Systems presents an overview on planning, implementing, assessing and optimizing biogas systems, from fuel conversion to power generation. The book introduces the fundamental elements of bioenergy systems, highlighting the specificities of biogas systems. It discusses the current state of their adoption at a global level and the challenges faced by designers and operators. Methods for sizing, simulating and modeling are discussed, including prefeasibility analysis, available production processes, integration into hybrid energy systems, and the application of Big Data analysis and game theory concepts. All chapters include real-life examples and exercises to illustrate the topics being covered. The book goes beyond theory to offer practical knowledge of methods to reach solutions to key challenges in the field. This is a valuable resource for researchers, practitioners and graduate students interested in developing smart, reliable and sustainable biogas technologies. Provides an applied approach to biogas systems, from technology fundamentals, to economic and environmental assessment Explores control methods and reliability prediction of each system component, including modeling and simulation with HOMER and MATLAB Discusses the use of Big Data analysis, numerical methods, and Game Theory for plant assessment

Signal Processing and Networking for Big Data Applications

Signal Processing and Networking for Big Data Applications Book
Author : Zhu Han,Mingyi Hong,Dan Wang
Publisher : Cambridge University Press
Release : 2017-04-27
ISBN : 1108155944
Language : En, Es, Fr & De

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Book Description :

This unique text helps make sense of big data in engineering applications using tools and techniques from signal processing. It presents fundamental signal processing theories and software implementations, reviews current research trends and challenges, and describes the techniques used for analysis, design and optimization. Readers will learn about key theoretical issues such as data modelling and representation, scalable and low-complexity information processing and optimization, tensor and sublinear algorithms, and deep learning and software architecture, and their application to a wide range of engineering scenarios. Applications discussed in detail include wireless networking, smart grid systems, and sensor networks and cloud computing. This is the ideal text for researchers and practising engineers wanting to solve practical problems involving large amounts of data, and for students looking to grasp the fundamentals of big data analytics.

Industrial IoT Technologies and Applications

Industrial IoT Technologies and Applications Book
Author : Jiafu Wan,Iztok Humar,Daqiang Zhang
Publisher : Springer
Release : 2016-08-17
ISBN : 331944350X
Language : En, Es, Fr & De

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Book Description :

This book constitutes the thoroughly refereed post-conference proceedings of the International Conference on Industrial IoT Technologies and Applications, IoT 2016, held in GuangZhou, China, in March 2016. The volume contains 26 papers carefully reviewed and selected from 55 submissions focusing on topics such as big data, cloud computing, Internet of Things (IoT).

IBM Power System S822LC for Big Data Technical Overview and Introduction

IBM Power System S822LC for Big Data  Technical Overview and Introduction Book
Author : Scott Vetter,David Barron,Alexandre Bicas Caldeira,Volker Haug,IBM Redbooks
Publisher : IBM Redbooks
Release : 2017-08-29
ISBN : 0738455776
Language : En, Es, Fr & De

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Book Description :

This IBM® RedpaperTM publication is a comprehensive guide that covers the IBM Power System S822LC for Big Data (8001-22C) server that uses the latest IBM POWER8® processor technology and supports Linux operating systems (OSs). The objective of this paper is to introduce the Power S822LC for Big Data offerings and their relevant functions as related to targeted application workloads. The new Linux scale-out systems provide differentiated performance, scalability, and low acquisition cost, including: Consolidated server footprint with up to 66% more virtual machines (VMs) per server than competitive x86 servers Superior data throughput and performance for high-value Linux workloads, such as big data, analytic, and industry applications Up to 12 LFF drives that are installed within the chassis to meet storage-rich application requirements Superior application performance due to a 2x per core performance advantage over x86-based systems Leadership data through put enabled by POWER8 multithreading with up to 4x more threads than x86 designs Acceleration of bid data workloads with up to two GPUs and superior I/O bandwidth with Coherent Accelerator Processor Interface (CAPI) This publication is for professionals who want to acquire a better understanding of IBM Power SystemsTM products. The intended audience includes: Clients Sales and marketing professionals Technical support professionals IBM Business Partners Independent software vendors

Design Analysis and Applications of Renewable Energy Systems

Design  Analysis and Applications of Renewable Energy Systems Book
Author : Ahmad Taher Azar,Nashwa Ahmad Kamal
Publisher : Academic Press
Release : 2021-09-09
ISBN : 0323859917
Language : En, Es, Fr & De

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Book Description :

Design, Analysis and Applications of Renewable Energy Systems covers recent advancements in the study of renewable energy control systems by bringing together diverse scientific breakthroughs on the modeling, control and optimization of renewable energy systems as conveyed by leading energy systems engineering researchers. The book focuses on present novel solutions for many problems in the field, covering modeling, control theorems and the optimization techniques that will help solve many scientific issues for researchers. Multidisciplinary applications are also discussed, along with their fundamentals, modeling, analysis, design, realization and experimental results. This book fills the gaps between different interdisciplinary applications, ranging from mathematical concepts, modeling, and analysis, up to the realization and experimental work. Presents some of the latest innovative approaches to renewable energy systems from the point-of-view of dynamic modeling, system analysis, optimization, control and circuit design Focuses on advances related to optimization techniques for renewable energy and forecasting using machine learning methods Includes new circuits and systems, helping researchers solve many nonlinear problems

Big Data on Real World Applications

Big Data on Real World Applications Book
Author : Sebastian Ventura Soto,José Luna,Alberto Cano
Publisher : BoD – Books on Demand
Release : 2016-07-20
ISBN : 9535124897
Language : En, Es, Fr & De

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Book Description :

As technology advances, high volumes of valuable data are generated day by day in modern organizations. The management of such huge volumes of data has become a priority in these organizations, requiring new techniques for data management and data analysis in Big Data environments. These environments encompass many different fields including medicine, education data, and recommender systems. The aim of this book is to provide the reader with a variety of fields and systems where the analysis and management of Big Data are essential. This book describes the importance of the Big Data era and how existing information systems are required to be adapted to face up the problems derived from the management of massive datasets.

Implementing an Optimized Analytics Solution on IBM Power Systems

Implementing an Optimized Analytics Solution on IBM Power Systems Book
Author : Dino Quintero,Kanako Harada,Reinaldo Tetsuo Katahira,Antonio Moreira de Oliveira Neto,Robert Simon,Brian Yaeger,IBM Redbooks
Publisher : IBM Redbooks
Release : 2016-06-01
ISBN : 0738441686
Language : En, Es, Fr & De

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Book Description :

This IBM® Redbooks® publication addresses topics to use the virtualization strengths of the IBM POWER8® platform to solve clients' system resource utilization challenges and maximize systems' throughput and capacity. This book addresses performance tuning topics that will help answer clients' complex analytic workload requirements, help maximize systems' resources, and provide expert-level documentation to transfer the how-to-skills to the worldwide teams. This book strengthens the position of IBM Analytics and Big Data solutions with a well-defined and documented deployment model within a POWER8 virtualized environment, offering clients a planned foundation for security, scaling, capacity, resilience, and optimization for analytics workloads. This book is targeted toward technical professionals (analytics consultants, technical support staff, IT Architects, and IT Specialists) who are responsible for providing analytics solutions and support on IBM Power SystemsTM.

Data Mining and Big Data

Data Mining and Big Data Book
Author : Ying Tan,Yuhui Shi
Publisher : Springer
Release : 2019-07-25
ISBN : 9813295635
Language : En, Es, Fr & De

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Book Description :

This book constitutes the refereed proceedings of the 4th International Conference on Data Mining and Big Data, DMBD 2019, held in Chiang Mai, Thailand, in July 2019. The 26 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 79 submissions. They are organized in topical sections named: data analysis; prediction; clustering; classification; mining pattern; mining tasks.

AI and Big Data s Potential for Disruptive Innovation

AI and Big Data   s Potential for Disruptive Innovation Book
Author : Strydom, Moses,Buckley, Sheryl
Publisher : IGI Global
Release : 2019-09-27
ISBN : 1522596895
Language : En, Es, Fr & De

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Book Description :

Big data and artificial intelligence (AI) are at the forefront of technological advances that represent a potential transformational mega-trend—a new multipolar and innovative disruption. These technologies, and their associated management paradigm, are already rapidly impacting many industries and occupations, but in some sectors, the change is just beginning. Innovating ahead of emerging technologies is the new imperative for any organization that aspires to succeed in the next decade. Faced with the power of this AI movement, it is imperative to understand the dynamics and new codes required by the disruption and to adapt accordingly. AI and Big Data’s Potential for Disruptive Innovation provides emerging research exploring the theoretical and practical aspects of successfully implementing new and innovative technologies in a variety of sectors including business, transportation, and healthcare. Featuring coverage on a broad range of topics such as semantic mapping, ethics in AI, and big data governance, this book is ideally designed for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research on the production of new and innovative mechanization and its disruptions.

BIG DATA SAS IBM ORACLE AND MICROSOFT TOOLS

BIG DATA  SAS  IBM  ORACLE  AND MICROSOFT TOOLS Book
Author : César Pérez López
Publisher : Lulu Press, Inc
Release : 2021-03-23
ISBN : 1008983608
Language : En, Es, Fr & De

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Book Description :

Big Data is the processing and analysis of large amounts of data, the size of which makes it impossible to handle with conventional database and analytical tools. The proliferation of websites, image and video applications, social networks, mobile devices, apps, sensors and other modern devices capable of generating huge amounts of data have made it necessary to develop Big Data tools for their analysis. As for Big Data tools, there is a growing development. Oracle uses Exadata for these purposes, SAS uses Visual Analytics and other tools, Microsoft uses Windows Azure, IBM uses Modeler and other tools based in Hadoop. Oracle includes Hadoop in Oracle Big Data Appliance, Oracle Big Data Connectors and Oracle Loader for Hadoop. SAS incorporates Hadoop in its applications (SAS Base, SAS Data Integration, SAS Enterprise Guide, SAS Enterprise Miner, SAS Visual Analytics, SAS Visual Statistics and others). IBM works with Hadoop in its IBM InfoSphere BigInsights platform (BigInsights) and Microsoft incorporates Hadoop in the Windows Azure platform with its Big Data applications (HDInsight, Polybase and others).