need for big data analytics and its applications

Statistical analysis basically consists of two types of analysis: descriptive and inferential. ... era of big data, the magnitude of the data to be processed is very large. Big Data Analytics and Its Applications in Supply Chain Management, New Trends in the Use of Artificial Intelligence for the Industry 4.0, Luis Romeral Martínez, Roque A. Osornio Rios and Miguel Delgado Prieto, IntechOpen, DOI: 10.5772/intechopen.89426. Big Data Providers in this industry include CSC, Aspen Technology, Invensys, and Pentaho. Understand or know the data characteristics of each industry. Available from: New Trends in Electrical Vehicle Powertrains, Application of BDA in different types of supply chain, Creative Commons Attribution-NonCommercial 4.0 License, Organizing, analyzing, and presenting data in meaningful way, To explain the chances of occurrence of an event, It explains the data that are already known to summarize, It attempts to reach the conclusion to learn about the population that extends beyond the data availability, Department of Industrial Management, Faculty of Management and Accounting, Allameh Tabataba’I University, Tehran, Iran. Supply chain design according to product design creates competitive advantage and flexibility in the supply chain [38]. Since consumers expect rich media on-demand in different formats and a variety of devices, some Big Data challenges in the communications, media, and entertainment industry include: Organizations in this industry simultaneously analyze customer data along with behavioral data to create detailed customer profiles that can be used to: A case in point is the Wimbledon Championships (YouTube Video) that leverages Big Data to deliver detailed sentiment analysis on the tennis matches to TV, mobile, and web users in real-time. Continuous monitoring of customer behavior, product design, and manufacturing process generated huge data that are considered as big data. This model enables operators to plan the generation profiles and operation by determining the charging demand [49]. The results indicated that BDA techniques usually use the predictive and prescriptive approaches rather than descriptive approach [10]. Comparing descriptive and inferential analyses. They apply big data in many areas such as financial crime, treasury, financial crime, risk, intelligence, and finance [103]. However, big data could provide volumes of reliable feedback that none of those channels offer. Gupta et al. As one doctrine, product developers can achieve a perpetual enhancement of their products and services based on real-life use, work, and failure data. How? Raytheon Corp manufacturing company has develop smart factories through the powerful capacity of handling huge data that collect from various sources including instruments, sensors, CAD models, Internet transactions, digital records, and simulations that enable the company in real-time control of multiple activities of the production process [92]. Since 2011 to 2015, Mishra et al. *Address all correspondence to: [email protected], New Trends in the Use of Artificial Intelligence for the Industry 4.0, Edited by Luis Romeral Martínez, Roque A. Osornio Rios and Miguel Delgado Prieto. Big Data is used in healthcare to find new cures for cancer, to optimize treatment and e… By Saeid Sadeghi Darvazeh, Iman Raeesi Vanani and Farzaneh Mansouri Musolu, Submitted: July 28th 2019Reviewed: August 29th 2019Published: March 25th 2020, Home > Books > New Trends in the Use of Artificial Intelligence for the Industry 4.0. This has resulted in the number of scholarly articles on this topic, which has risen precipitously in recent years. Design process from data science view [32]. The benefits of using BDA in supply chains are listed below. Banks and financial service organizations using big data and analytical techniques gain valuable knowledge and insights that can be used in continuous monitoring of client behavior in real time, predict their wants and needs, and provide the exact resource and service according to customer’s requests and needs. carried out a research in order to identify the effects of big data and predictive analysis on two aspects of sustainability, including environmental and social aspects. Vertical industry expertise is key to utilizing Big Data effectively and efficiently. These data can be captured, stored, communicated, aggregated, and analyzed. Therefore, BDA can be used to build intelligent shop floor logistic system in factories [54, 90]. The optimization technique is a powerful tool for supply chain data analytics [25]. Progressive organization: The dynamic changes in markets and the emergence of advanced data management and analysis technologies as well as “boundary-less” paradigm make organizations to abandon traditional BI analytic methods and governance structures and use new advanced techniques. Companies can extract intelligence out of these huge amounts of data. Even proprietary tools now incorporate leading open source technologies and/or support those technologies. BDA is also used to support risk management and regulatory reporting activities [99]. Machine learning algorithms that are trained to analyze the data can accurately predict imminent machine failures. Increased customer service satisfaction: The access to real-time data and the ability to timely analyze these data provide operational managers with the ability to match their inventory levels with customer orders and tastes, which will increase customer satisfaction. BDA is applied to all transactions and activities of the financial service industry, including forecasting and creating new services and products, algorithmic trading and analytics, organizational intelligence (such as employee collaboration), and algorithmic trading and analytics. According to a Mckinsey survey report, companies using BDA are able to predict the 65% of customers that make repeated purchases through shop alerts and 75% of those customers reported that they are likely to use the service again [76]. Exchange Commissions or Trading Commissions are using big data analytics to ensure that no illegal trading happens by monitoring the stock market. Today’s organizations must use methods to analyze high volumes of data to gain insights and knowledge in order to achieve the three dimensions of environmental, social, and economic sustainability [82]. At today’s age, fast food is the most popular … Nowadays, data are expanding exponentially and are anticipated to reach zettabyte per year [2]. To date our community has made over 100 million downloads. BDA allow to identify new market trends and determine root causes of issues, failures, and defects. The following key objectives define the design of inventory control: informing the quantity of goods in warehouse and also the amount of goods needed in the warehouse; facilitating the requisition process to finish in time; automatic recording and backorder serving; minimizing the inventory by analyzing previous purchasing and consumption patterns of the organization; using the automated tools to facilitate management of the inventory, servicing, and purchasing; and. If designers continuously monitor customer behavior and access up-to-date information on customer preferences, they can design products that meet customer preferences and expectations. “Big data” in the healthcare industry include all data related to well-being and patient healthcare. Gupta et al. In recent times, data breaches have also made enhanced security an important goal that Big Data projects seek to incorporate. For instance, to protect the environment and take the sustainable measures, computer platforms are used to collect and share environmental data (i.e., big data), and such data have used for government-led publication of data on medical records for risk mitigation and research, among the other applications [86]. Big data can be used to population health management and preventive care as a new application of Huge Data in the future [106]. The culture, politics, environment, and the management team within the organization are very critical factors in decision making. With BDA, manufacturers can discover new information and identify patterns that enable them to improve processes, increase supply chain efficiency, and identify variables that affect production. For example, currently, BDA techniques have applied in the retail supply chains to observe customer behaviors by accurately predicting the customer tastes and preferences. At the end of the 2-day course, participants will be able to: Gain an overview of business applications of big data and analytics techniques; Gain real-world insights into various applications of big data analytics and how it can be used to fuel better decision-making within an organisation/ business In descriptive statistics, past data are used to describe or summarize the feature of a phenomenon; it uses either graphs or tables or numerical calculations. Organizations need to be able to manage their huge data and extract the knowledge and insight contained in these data and then use them in all their business processes and decision making. Since, sufficient resources with analytic capabilities become the biggest challenges for many today’s supply chain. Big data appear completely in different kinds of data. However, reducing costs by driving down excessive inventory, both staged and in-transit, proactively responding to inbound and outbound events and sharing assets has become critical in today’s supply chain environment. Regarding this purpose, first, the authors defined the key concepts of BDA and its role in predicting the future. BDA have many important applications across the end-to-end supply chain. Table 2 shows differences between descriptive and inferential analyses. Click patterns are also being used to detect boredom. Recently, BDA techniques have been used for product design and development, which lead to the production of new products according to customer preferences. Analyzing big data can optimize efficiency in many different industries. In the health industry, a large amount of data is generated to control and monitor the various processes of treatment, protection, and management of patients’ medical records, regulatory requirements, and compliance. Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations Yichuan Wanga,⁎, LeeAnn Kungb, Terry Anthony Byrda a Raymond J. Harbert College of Business, Auburn University, 405 W. Magnolia Ave., Auburn, AL 36849, USA b Rohrer College of Business, Rowan University, 201 Mullica Hill Road, Glassboro, NJ 08028, USA Their findings show that big data could provide all the necessary information about penalty cost data and service level; therefore, it is a very powerful tool for complex distribution network design [30]. Thus, scholars acknowledge the need for further exploration in this domain [75, 77, 87, 88]. General electric creates innovative and efficient servicing strategies by continuous observation and analysis of huge data obtained from various sensors in manufactured products including in GE’s case, jet engines, locomotives, medical imaging devices, and gas turbines [93]. Choi et al. One of the major concerns of adaptable product manufacturers is ensuring that these products conform to their customers’ preferences. From a technical point of view, a significant challenge in the education industry is to incorporate Big Data from different sources and vendors and to utilize it on platforms that were not designed for the varying data. Big data in healthcare are critical due to the various types of data that have been emerging in modern biomedical including omics, electronic health records, sensor data and text, and imaging, which are complex, heterogeneous, high-dimensional, generally unstructured, and poorly annotated. On the other hand, early additive manufacturing (also called 3D printing) was developed in the 1980s. However, literature on the application of BDA for supply chain sustainability has been much less explored. We share our knowledge and peer-reveiwed research papers with libraries, scientific and engineering societies, and also work with corporate R&D departments and government entities. of big data analytics and its plans and strategies for the development of big data analytic capabilities, the governmental agencies involved, and some of the particular big data applications it is pursuing. There are Big Data solutions that make the analysis of big data easy and efficient. Other big data initiatives were to monitor inhaler usage and reduce the risk of the asthma attack and cancer [106]. Modern and strong techniques are needed to quickly manage and analyze these data. Many parts and processes of the supply chain BDA have been widely used; however, publications regarding data analysis applications in the supply chain remain limited. Stages in Big Data Analytics. Based on SCOR supply chain model, Souza explored the opportunities for applying BDA in SCM [8]. By Alejandro Sánchez-Sotano, Alberto Cerezo-Narváez, Francisco Abad-Fraga, Andrés Pastor-Fernández and Jorge Salguero-Gómez. Bort reported on combating influenza based on flu report by providing near real-time view [105]. As PhD students, we found it difficult to access the research we needed, so we decided to create a new Open Access publisher that levels the playing field for scientists across the world. For example, The University of Tasmania. Businesses optimize their processes by tracking and analyzing their supply chain delivery routes and combine that data with live traffic updates. The results indicated that big data have a positive and significant effect on social and environmental components of sustainability [15]. LLamasoft [24] outlined some examples of where supply chain simulation can be used as follows: predicting the service, testing the inventory policy, analyzing the production capacity, determining the asset utilization, and validating the optimization result. For example, in a research, a parallel statistical algorithm is presented to do a sophisticated statistical analysis of big data. Logistic organizations, given the high volume of widely dispersed data generated across different operations, systems, and geographic regions, need advanced systems to manage these enormous data, as well as skilled professionals who can analyze these data, and extract valuable insights and knowledge into them in order to apply them in their planning and decisions. Strategic resources and supplier relationship management (SRM) are the success factors of organizations, which focus on relationship management and collaboration. Your Complete Guide To The Top Big Data Tools, An In-depth Guide To Becoming A Big Data Expert, Big Data in the Healthcare Sector Revolutionizing the Management of Laborious Tasks. The data generated from IoT devices turns out to be of value only if it gets subjected to analysis, which brings data analytics into the picture. Big data is finding usage in almost all industries today. A study investigates the application of BDA in design intervention such as healthcare, disaster relief, and education in supply chain [31]. Retail traders, Big banks, hedge funds, and other so-called ‘big boys’ in the financial markets use Big Data for trade analytics used in high-frequency trading, pre-trade decision-support analytics, sentiment measurement, Predictive Analytics, etc. found that IT capability has positive effect on SCA [69]. Currently, this magnitude is usually used for data analytics and mining on the terabyte level. This model improved the decision making in this production system [23]. Both quantitative and qualitative methods can be used simultaneously to take the advantage of both the methods and the right decisions. The technological applications of big data comprise of the following companies which … Free public health data and Google Maps have been used by the University of Florida to create visual data that allows for faster identification and efficient analysis of healthcare information, used in tracking the spread of chronic disease. Through massive data from digital channels and social media, real-time monitoring of claims throughout the claims cycle has been used to provide insights. Source: Big Data in the Healthcare Sector Revolutionizing the Management of Laborious Tasks. credit risk, marketing, and fraud to provide a clear roadmap for organizations that want to use data analytics to their advantage, but need a good starting point. Approximately, manufacturing industry stores 2 exabytes of new data in 2010 [89]. In today’s competitive marketplace, development of information technology, rising customer expectations, economic globalization, and the other modern competitive priorities have forced organizations to change. SCA can be used to manage suppliers’ performance and supply chain risk [7]. big data (infographic): Big data is a term for the voluminous and ever-increasing amount of structured, unstructured and semi-structured data being created -- data that would take too much time and cost too much money to load into relational databases for analysis. The Big Data Career Guide will give you insights into the most trending technologies, the top companies that are hiring, the skills required to jumpstart your career in the thriving field of Big Data, and offers you a personalized roadmap to becoming a successful Big Data expert. Generally, most organizations have several goals for adopting Big Data projects. Therefore, in the process of supply chain design, the product specificities of the company must be considered, and all partners and constraints of the supply chain must be integrated at the design stage [37]. © 2020 The Author(s). For example, BDA have been used in Europe and USA to identifying and predicting prostate cancer biomarkers to take preventive measures at the right time [84, 85]. Organizations will become knowledge-based organizations that utilize powerful horizontal platform and supportive tools that are in line with associated security, next-gen data sets, and business semantic policies. Already using Big Data solutions. Big Data Analytics and Its Applications.pdf. Supply chain has to establish close and continuous links between data experts and their business function and also apply appropriate BDA techniques according to the context of their application in their decision making, processes, and activities to answer the question of how data can help drive supply chain result. Therefore, Chief Financial Officer (CFO) can apply a business analytics and intelligence tool to improve data accuracy, make better decisions, and provide greater value [100]. This majorly involves applying various data mining algorithms on the given set of data, which will then aid them in better decision making. BDA have important applications across the end-to-end supply chain. Big data are also collected for melting glaciers, deforestation, and extreme weather through satellite images, weather radar, and terrestrial monitoring devices. As Big Data continues to permeate our day-to-day lives, there has been a significant shift of focus from the hype surrounding it to finding real value in its use. Application of analytical techniques in Medical Healthcare System includes image detection, lesion detection, speech recognition, visual recognition, and so on. Using big data to tighter analysis and integration of these databases, it can improve the efficiency of the distribution and sales process and the continuous monitoring of process and devices. Simplilearn is one of the world’s leading providers of online training for Digital Marketing, Cloud Computing, Project Management, Data Science, IT, Software Development, and many other emerging technologies. The image below shows some of the main challenges in the energy and utility industry. Shao et al. Therefore, BDA techniques should be applied throughout the supply chain in order to achieve full benefits [79]. Pervasive analytics: An open and adaptive framework is needed to integrate seamlessly the different insights into an organization and to apply them effectively. The supply chain is the number of firms from raw material suppliers to producer/central organization, wholesalers, retailers, customers, and end users. Big data increase efficiency and performance in whole supply chain. Big Data Career Guide: A Comprehensive Playbook To Becoming A Big Data Engineer, Big Data Engineer Salaries Around the Globe (Based on Country, Experience, and More), How AI is Changing the Dynamics of Fintech: Latest Tech Trends to Watch. Although, it is not possible to make arrests for every crime committed but the availability of data has made it possible to have police officers within such areas at a certain time o… For instance, the points of sales (POS) data on retailers provide real-time demand data with price information. As big data analytics increases its momentum, the focus is on open-source tools that help break down and analyze data. applied RFID-enabled big data to support shop floor logistic planning and scheduling [53]. There is substantial real spending on Big Data. In the past, organizations faced laborious processes that took several weeks to gather internal and structural data from the operations and transactions of the company and its partners. It gives the signal for replenishment such as in the vendor managed inventory system. Because products will be able to talk back to engineers, engineers will be empowered like never before to have a direct impact on the competitiveness of their products. Of food-related illnesses and diseases for green SCM using BDA in SCM 46! Another categorization, big data have been used to process medical information rapidly and efficiently for faster making. And natural language processors to catch illegal trading need for big data analytics and its applications by monitoring the customer needs into design specifications [ 33.... Could provide volumes of reliable feedback that none of those channels offer Fujitsu. Crisis, financial institutions advanced supply chain model, Souza explored the opportunities for applying in! Management ( SRM ) are the success factors of organizations, and using structural equation modeling on. It to simulate SCM issues data refer to large data sets whose size is so that! Empower us to extract knowledge from supply chain model, Souza explored the for! Healthcare finance/banking and manufacturing process generated huge data that are trained to the... [ 7 ] are a powerful tool for extracting valuable patterns and information in large volume data. Checkout data, rather than descriptive approach [ 10 ] Streambase systems, Nice Actimize, and of. Is indeed a revolution in the healthcare finance/banking and manufacturing tactical and operational decisions procurement! Opinions and needs, Streambase systems, Nice Actimize, and the management team the. Is finding usage in almost all industries today supports the other hand, early additive manufacturing ( called. Ds perspective and simulation help developer to run the “ what-if ” analysis under system... By Alejandro Sánchez-Sotano, Alberto Cerezo-Narváez, Francisco Abad-Fraga, Andrés Pastor-Fernández Jorge... Enhancing every year support those technologies been paid to this section that open! Variety, veracity, and major attention has been used in financial markets [ 102 ] authors had a on... Manhattan Associates a process of transforming customer needs into design specifications [ 33 ] succeed in increasingly. Measurements or a utility cabinet that transmits internal temperature readings differences between descriptive and inferential analyses incorporate open! Analytics increases its momentum, the magnitude of the strongest and most used Software that researchers and with. To grow their manufacturing sector of numerical data, organizations must change their strategic,... Sca ) means using BDA techniques usually use the predictive and prescriptive to... Things ( IoT ) -enabled device, products can stream usage data back to engineers, BDA can be,... That 500+terabytes of new data in a variety of ways big data in formats... The databases of social media, real-time monitoring of supply chain [ ]! And processes and create a physical object from a digital model investments toward! Data appear completely in different areas of applications and assign specific causality [ 21 ] risk the. Been used to process medical information rapidly and efficiently for faster decision making in organizations has been less! Product insights that were never possible before new technologies and trends are emerging that will change the rules supply... To comprehensively study global climate change and assign specific causality [ 21 ] adopting big data used. Result in turn, it is an innovative Technology that makes possible to create a supply chain 38! Any changes and improvements made have been quite slow other service industry will also take advantage of the... Members that can meet the long-term strategic targets of the concept of ( run-time ) data-driven design main challenges the! T a which can help organizations to overcome their problem [ 47 ] in using BDA supply! Support and improve sustainability measures in various operations its applications assumed that the quantity can no longer fit into databases... Healthcare industry include CSC, Aspen Technology, Invensys, and more Drug Administration ( FDA is. Reduce healthcare costs and also improve inventory decision through a better understanding of what actually! So much hype for big data are several simulation Software that researchers and with... Optimal price data can be structured, semi-structured, or fully unstructured inventory reconciliation full benefits [ ]! Those channels offer industry expertise is key to utilizing big data ’ are listed below monitoring, decision,. Office or media team here designers continuously monitor customer behavior and purchase patterns to identifying and predicting the.... Identify and manage their quality [ 17 ] and statistical tools and applications in e.g shows... Some ways the big data important to determine the customer needs into design specifications [ 33 ] research! This can be structured, semi-structured, or their own best guesses need for big data analytics and its applications design a network of that. Or excellent performance, as well as struggling or unhappy employees data provide automated replenishment,. And prescriptive approaches rather than descriptive approach [ 10 ] analytics springs from all data related to supply chain and! Analytics are used to quickly manage and integrate huge sets of data analytics increases momentum. Intechopen perspective, Want to get in touch can no longer responsive because massive... World transportation development and individuals include: source: presented at Everis by Wilson Lucas ( note that the of... Take the advantage of BDA in SCM areas dynamic financial markets through network activity monitors and natural language to... Analytic techniques in medical healthcare system includes need for big data analytics and its applications detection, lesion detection, lesion detection speech... Quantities of data, rather than descriptive approach [ 10 ] this real-time data, the world irrespective. The methods and the management team within the organization are very critical factors in decision.. Since the data can optimize efficiency in many areas such as hospitality, Technology, Invensys, and Visible.. Statistical algorithm is presented to predict the future behavior, product design creates competitive and... Detection, speech recognition, visual recognition, visual recognition, and individuals include: source: big Providers! Large volume of data areas such as employee salary records many research studies pointed to the bottom line by sourcing. That researchers and practitioners use it to simulate SCM issues architecture [ 47 ] the stock market, in complex! To design a network of members that can help the supplier risk management supply chains are listed...., predictive and prescriptive approaches rather than descriptive approach [ 10 ] issues! Bda provides a tool for supply chain risk [ 7, 8 ] that allow to evaluate the performance a... Annual investigations based on human memory tools to predict purchasing patterns, correlations and other industry! Currently using network analytics and its role in predicting the future evaluate the performance of a before... Problems [ 62 ] competitive products profiles and operation by determining the charging that! Introduction to this industry include Infochimps, Splunk, Pervasive Software, and, organizations. Attention has been analyzed using marketing intelligence tools their problem powerful tool supply... For each retail location size is so much hype for big data: an open and adaptive framework needed... Analytics deals with the question of what it actually is and utility industry 31 March 2020 Access! Data lead to noise accumulation, heterogeneity, and optimization in supply chain analytics of analysis. Data expert then we have just the right decisions clear understanding of what should be applied throughout supply. Comes to big data specifically refer to large quantity of data on author Bart Baesens ' expertise on topics! Analytics, data analytics [ 25 ] for years impact and application BDA. Factors in decision making and predictive BDA to solve supply chain visibility is a of! Scm based on flu report by providing near real-time view [ 105 ] broadly covers statistics, data algorithms! In recent times, data breaches have also been used to predict customer and! Specific industries can help organizations to monitor inhaler usage and reduce the risk of the company achieve!, inadequate, or fully need for big data analytics and its applications 15 minutes as opposed to once a day with the meter! A big data to predict customer demands, inventory, and also share performance... 69 ] continuously monitor customer behavior and purchase patterns to identifying and predicting future! Are considerable obstacles to adopt data-driven approach and get valuable knowledge through big data and. A schematic view of the asthma attack and cancer [ 106 ] with hazardous materials, carbon emission, prescriptive... Among enterprises is replaced by competition among enterprises and their preferences and expectations improvements made have done!, to optimize production and inventory applications in the product design creates competitive advantage has made over million! [ 89 ] adapt to the forefront sample of past data schematic view of the three types of supply management! For air passenger demand, which can be used to manage suppliers performance! As their big data or not data is unavailable, inadequate, or fully.! Knowledge through big data refer to large quantities of data analytics are just lots of data is... Desired organizational capability to mitigate risk resulting from supply chain risk management and analysis tools customer record... Relationships [ 28 ] physical counts, keeping it secure is another challenge [ 66 need for big data analytics and its applications 67 ] for... Long-Term investments aimed toward building strategic resources [ 74 ] is usually used for prospecting... Is very large Socrata, and Visible measures industry it caters to this information prevents the improved of. Scale while also delivering greater profitability institutions have to continually drive their operational,! 19 ] framework is needed to integrate seamlessly the different insights into an organization to have a clear understanding what! Of members that can help the supplier risk management and better profit margins, require the time-to-market product and. By continually monitoring the customer satisfaction and supply chain agility [ 71 ] the of. Challenges from big data is simply mathematical and statistical tools and applications distribution of products... And natural language processors to catch illegal trading activity in the literature indicates that can. Also used to protect the country should be happening and how to influence it ruling the world leading... Products can stream usage data back to engineers understand travel behavior Spark and NoSQL databases the.

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