The document discusses big data and its potential applications for payment cards. It summarizes the European Commission's concerns about Europe falling behind the US and China in embracing big data. The Commission is calling for initiatives to develop enabling technologies, share public data, and ensure legal frameworks support innovation. The document defines big data and outlines typical benefits like improved marketing, pricing, and supply chain optimization. It also discusses how payment card schemes could be sources and users of big data to enhance fraud prevention, customer segmentation, merchant support, and new product development.
Sotiris is currently working as Research Director with the Institute of Computer Science at the Foundation for Research and Technology - Hellas, where his research interests include systems, networks, and security. He is also a member of the European Union Agency for Network and Information Security (ENISA) Permanent Stakeholders Group! During Data Science Conference, Sotiris will talk about how data sharing between private companies and research facilities may lead to monetization.
The document discusses analytics for Internet of Things (IoT) data from trucks. It describes an architecture that uses technologies like Kafka and Storm for real-time streaming of sensor data, HDFS for storage, Elasticsearch for retrieval, and Spark and machine learning tools for predictive analytics on the data to discover patterns related to violations. A web app with dashboards and alerts in ActiveMQ would display insights and messages based on the captured and analyzed truck event data.
Big Data PPP Industrial Data Platforms - Towards cross-sectorial optimization and traceability
To start identifying synergies and to learn how different projects will address key data collection, sharing, integration, and exploitation challenges, a series of webinars have been organized under the umbrella of this Big Data Value PPP. These webinars are also organized by BDVA, BDVe project, and other projects which are part of this PPP.
1) The document discusses how big data can be turned into smart data through thorough analytics that provide context and address limitations like bias and incompleteness.
2) It recommends capturing big data from various sources, processing and analyzing it using advanced techniques, and integrating reference data to understand context and create maximum value for clients.
3) An example shows combining behavioral internet data with survey data to map consumer purchase journeys in travel and optimize marketing spend.
Leveraging Service Computing and Big Data Analytics for E-CommerceKarthikeyan Umapathy
Panel discussions on Leveraging Service Computing and Big Data Analytics for E-Commerce at the Workshop on e-Business (WeB) 2015 held on December 12, 2015 at Fort Worth, Texas, USA.
Information technology by Hiresh Ahluwalia333jack333
IT refers to the use of electronic computers and computer software to store, process, transmit and retrieve information. Some key applications of IT include:
1. Banking - IT has enabled online/mobile banking and improved efficiency of banking operations.
2. Railways - IT is used for tracking, scheduling, monitoring railway traffic as well as design, construction and maintenance.
3. Business - Computers are widely used for record keeping, inventory management, forecasting, billing, payments and financial reporting in businesses.
4. Marketing - Businesses use databases, customer relationship management tools, and data analytics for targeted marketing, improving customer relationships and sales.
Using Big Data in Finance by Jonah EnglerJonah Engler
How can you utilize Big Data in the Financial Industry? To leverage Big Data - entrepreneur and finance expert Jonah Engler, has put together this presentation to help the slideshare community understand the value - and HOW TO - use big data in the financial campaigns.
Jonah Engler is a financial expert and stock broker based in NYC. Leveraging his experience in finance, Engler has gone on to have success in the franchise, coffee, startup industries and more. To connect with Jonah - checkout his profile on LinkedIn: https://www.linkedin.com/in/jonahengler
Sotiris is currently working as Research Director with the Institute of Computer Science at the Foundation for Research and Technology - Hellas, where his research interests include systems, networks, and security. He is also a member of the European Union Agency for Network and Information Security (ENISA) Permanent Stakeholders Group! During Data Science Conference, Sotiris will talk about how data sharing between private companies and research facilities may lead to monetization.
The document discusses analytics for Internet of Things (IoT) data from trucks. It describes an architecture that uses technologies like Kafka and Storm for real-time streaming of sensor data, HDFS for storage, Elasticsearch for retrieval, and Spark and machine learning tools for predictive analytics on the data to discover patterns related to violations. A web app with dashboards and alerts in ActiveMQ would display insights and messages based on the captured and analyzed truck event data.
Big Data PPP Industrial Data Platforms - Towards cross-sectorial optimization and traceability
To start identifying synergies and to learn how different projects will address key data collection, sharing, integration, and exploitation challenges, a series of webinars have been organized under the umbrella of this Big Data Value PPP. These webinars are also organized by BDVA, BDVe project, and other projects which are part of this PPP.
1) The document discusses how big data can be turned into smart data through thorough analytics that provide context and address limitations like bias and incompleteness.
2) It recommends capturing big data from various sources, processing and analyzing it using advanced techniques, and integrating reference data to understand context and create maximum value for clients.
3) An example shows combining behavioral internet data with survey data to map consumer purchase journeys in travel and optimize marketing spend.
Leveraging Service Computing and Big Data Analytics for E-CommerceKarthikeyan Umapathy
Panel discussions on Leveraging Service Computing and Big Data Analytics for E-Commerce at the Workshop on e-Business (WeB) 2015 held on December 12, 2015 at Fort Worth, Texas, USA.
Information technology by Hiresh Ahluwalia333jack333
IT refers to the use of electronic computers and computer software to store, process, transmit and retrieve information. Some key applications of IT include:
1. Banking - IT has enabled online/mobile banking and improved efficiency of banking operations.
2. Railways - IT is used for tracking, scheduling, monitoring railway traffic as well as design, construction and maintenance.
3. Business - Computers are widely used for record keeping, inventory management, forecasting, billing, payments and financial reporting in businesses.
4. Marketing - Businesses use databases, customer relationship management tools, and data analytics for targeted marketing, improving customer relationships and sales.
Using Big Data in Finance by Jonah EnglerJonah Engler
How can you utilize Big Data in the Financial Industry? To leverage Big Data - entrepreneur and finance expert Jonah Engler, has put together this presentation to help the slideshare community understand the value - and HOW TO - use big data in the financial campaigns.
Jonah Engler is a financial expert and stock broker based in NYC. Leveraging his experience in finance, Engler has gone on to have success in the franchise, coffee, startup industries and more. To connect with Jonah - checkout his profile on LinkedIn: https://www.linkedin.com/in/jonahengler
Big data provides opportunities for financial institutions to gain competitive advantages. It allows them to analyze vast amounts of structured and unstructured data from various sources to better understand customers, identify risks, predict behaviors, and improve financial products and services. While big data implementations face challenges like integrating diverse data sources and developing analytics talent, companies that execute big data strategies are seeing significant benefits like more personalized customer experiences and better risk management. TD Bank is an example of a company revolutionizing IT and banking through big data analytics that can build comprehensive customer profiles and segment their entire customer base within minutes.
Check out how big data is proving invaluable to finance. Here is the top 10 big data trends in finance. Big data place a vital role in analysing the feeds, Predictive models, forecasts & assess trading impacts
The document discusses IT systems in the retail industry. It states that IT systems are at the center of retail operations, affecting areas like transactions, communications, operations management, business planning and marketing. These systems include hardware, software, and services used to manage processes, payments, inventory and analytics. Retailers face challenges to modernize their IT infrastructure to support an omnichannel customer experience and gain insights from customer data and analytics. The document provides an overview of the IT challenges retailers face and opportunities for vendors in areas like cloud computing, digital wallets, IoT, and big data.
1. Determine if a Big Data approach is suitable based on factors like volume, variety and velocity of data as well as the need for iterative, exploratory analysis.
2. Use techniques like Hadoop, MapReduce and NoSQL databases that can analyze large, diverse, unstructured datasets in a distributed, parallel manner.
3. Follow data management best practices like data governance, quality checks, and master data management to ensure clean, well-organized data.
Big data comes from a variety of sources and in different formats. It is characterized by its volume, velocity, and variety. Organizations are using big data to gain business insights through analytics. This allows them to increase revenue, reduce costs, optimize processes, and manage risks. Examples of big data uses include marketing campaign analysis, customer segmentation, and fraud detection. Companies must overcome technological and organizational challenges to successfully leverage big data.
governance, management & compliance
Today, not only large companies, but also SMEs understand the economic and strategic value of big data, collected from customers, potential customers, partners, etc However, it is not only a question of collecting data, but also of analyzing and managing them, ensuring their quality, according to principles of accuracy, reliability and minimization.
Infact, it is necessary to have the possibility to process such huge data legitimately and profitably, mapping the activities of data collection, management and storage, with analysis programs in compliance with the regulations in force (GDPR first of all).
Corporate Governance today, therefore, passes from Data Governance and Data Analytics and the ability to organize the company in order to exploit the power of data.
8th International Conference of Managing Information Technology (CMIT 2020)ijmvsc
8th International Conference of Managing Information Technology (CMIT 2020) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the area advanced Computer Science and information technology. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of advanced CS & IT. Core areas of advanced IT and multi-disciplinary and its applications will be covered during the conferences. to discuss the latest issues and advancement in the area of advanced CS & IT. Core areas of advanced IT and multi-disciplinary and its applications will be covered during the conferences.
This document outlines the topics to be covered in a course on digital business and e-commerce. It includes:
1. An introduction to the digital transformation and topics like data, cloud computing, social media, mobile technologies, and the sharing economy.
2. A discussion of the digital platform and technologies like web standards, APIs, apps, and big/open data.
3. Sections on e-business, digital marketing, how digital disruption impacts companies, and perspectives from fields like media and industry 4.0.
4. Key principles of digital business and marketing like ubiquity, global reach, standardization, richness, and personalization through data and algorithms are also summarized.
Data is poised to play an important role in the enterprises of the future, with businesses looking to scale up production and recover costs. Visit: https://www.raybiztech.com/blog/data-analytics/what-are-big-data-data-science-and-data-analytics
Dark Data Revelation and its Potential BenefitsPromptCloud
Dark data refers to the large amounts of unused data organizations collect during regular business activities. While organizations invest heavily in collecting data, much of it remains unused. There are three main types of dark data: existing unstructured internal data, non-traditional unstructured external data, and data available on the deep web. Analyzing dark data can provide valuable insights but also risks such as privacy issues. Some companies are already leveraging dark data for applications like fraud detection and personalization in retail. Approaching dark data requires getting the right data, augmenting with external sources, building data talent, and using advanced visualization tools.
CITE Start Thinking Big Data 2019 01-30 FINALJon Kostyniuk
Whatever the size or type of organization, Big Data has permeated our transportation industry. It is no longer a question of IF Big Data will be useful, but instead WHY is it useful and HOW can we best apply it. This presentation aims to address how we can leverage existing services and available partnerships in transportation, consider new and emerging technologies, and determine strategy for what’s to come in transportation, including connected and autonomous vehicles. While it may be a huge challenge to solve transportation problems with Big Data, it can help us make better travel decisions today and plan for better infrastructure tomorrow.
8th International Conference of Managing Information Technology (CMIT 2020)Zac Darcy
8th International Conference of Managing Information Technology (CMIT 2020) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the area advanced Computer Science and information technology. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of advanced CS & IT. Core areas of advanced IT and multi-disciplinary and its applications will be covered during the conferences. to discuss the latest issues and advancement in the area of advanced CS & IT. Core areas of advanced IT and multi-disciplinary and its applications will be covered during the conferences.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Computer Science & Information Technology.
This document discusses opportunities for data-driven growth and innovation. It explains that analyzing large amounts of data from various sources (i.e. big data) can provide valuable insights to create new products and services, improve efficiency, and generate new revenue streams. Specifically, it provides examples of how telecom operators can leverage network usage data and customer insights to partner with other industries and monetize consumer data while respecting privacy. Transparency around data usage is important to build customer trust.
TechConnex Big Data Series - Big Data in BankingAndre Langevin
Big Data in Banking focuses on the use of big data and Hadoop in the Canadian banking sector. The key points are:
1) The RDARR regulatory project is driving major investments in data management by the big six Canadian banks, totaling around $800 million over three years. This has led banks to implement Hadoop data hubs to centralize data.
2) Adoption of Hadoop for risk applications is still in early stages, with a focus on regulatory reporting. Capital markets has led adoption so far.
3) Lessons learned include choosing flexible Hadoop distributions, using native Hadoop tools for best performance, and designing hubs for data engineers rather than casual users. Infrastructure must have
The Emergence of Alt-Data and its ApplicationsPromptCloud
Alternative data is information gathered from non-traditional information sources. Analysis of this data can provide insights beyond that which an industry’s regular data sources are capable of providing. Here is all you should know about alt-data.
This document discusses big data mining and the Internet of Things. It first presents challenges with big data mining including modeling big data characteristics, identifying key challenges, and issues with statistical analysis of IoT data. It then describes an architecture called IOT-StatisticDB that provides a generalized schema for storing sensor data from IoT devices and a distributed system for parallel computing and statistical analysis of IoT big data. The system includes query operators for data retrieval and statistical analysis of IoT data in areas like transportation networks.
Big data offers companies a big advantage if they can harness enormous data sets that were previously impossible to process. The document discusses how big data is transforming business models through creative destruction, as more data is created every day from various sources. It provides examples of how companies in various industries like retail, banking, and manufacturing are using big data for customer intimacy, product innovation, and improving operations. Specifically, companies are able to better customize products and services, improve supply chain management, and gain real-time insights from vast amounts of structured and unstructured data.
Big data offers opportunities for companies to gain competitive advantages through improved customer intimacy, product innovation, and operations. The document discusses how various companies are leveraging big data across industries. It notes that 45% of companies have implemented big data initiatives in the past two years and over 90% of Fortune 500 companies will have initiatives underway soon. Harnessing big data's potential requires understanding where it can create value within a company and having the right organizational structure, technology investments, and plan to capture those benefits.
Big data provides opportunities for financial institutions to gain competitive advantages. It allows them to analyze vast amounts of structured and unstructured data from various sources to better understand customers, identify risks, predict behaviors, and improve financial products and services. While big data implementations face challenges like integrating diverse data sources and developing analytics talent, companies that execute big data strategies are seeing significant benefits like more personalized customer experiences and better risk management. TD Bank is an example of a company revolutionizing IT and banking through big data analytics that can build comprehensive customer profiles and segment their entire customer base within minutes.
Check out how big data is proving invaluable to finance. Here is the top 10 big data trends in finance. Big data place a vital role in analysing the feeds, Predictive models, forecasts & assess trading impacts
The document discusses IT systems in the retail industry. It states that IT systems are at the center of retail operations, affecting areas like transactions, communications, operations management, business planning and marketing. These systems include hardware, software, and services used to manage processes, payments, inventory and analytics. Retailers face challenges to modernize their IT infrastructure to support an omnichannel customer experience and gain insights from customer data and analytics. The document provides an overview of the IT challenges retailers face and opportunities for vendors in areas like cloud computing, digital wallets, IoT, and big data.
1. Determine if a Big Data approach is suitable based on factors like volume, variety and velocity of data as well as the need for iterative, exploratory analysis.
2. Use techniques like Hadoop, MapReduce and NoSQL databases that can analyze large, diverse, unstructured datasets in a distributed, parallel manner.
3. Follow data management best practices like data governance, quality checks, and master data management to ensure clean, well-organized data.
Big data comes from a variety of sources and in different formats. It is characterized by its volume, velocity, and variety. Organizations are using big data to gain business insights through analytics. This allows them to increase revenue, reduce costs, optimize processes, and manage risks. Examples of big data uses include marketing campaign analysis, customer segmentation, and fraud detection. Companies must overcome technological and organizational challenges to successfully leverage big data.
governance, management & compliance
Today, not only large companies, but also SMEs understand the economic and strategic value of big data, collected from customers, potential customers, partners, etc However, it is not only a question of collecting data, but also of analyzing and managing them, ensuring their quality, according to principles of accuracy, reliability and minimization.
Infact, it is necessary to have the possibility to process such huge data legitimately and profitably, mapping the activities of data collection, management and storage, with analysis programs in compliance with the regulations in force (GDPR first of all).
Corporate Governance today, therefore, passes from Data Governance and Data Analytics and the ability to organize the company in order to exploit the power of data.
8th International Conference of Managing Information Technology (CMIT 2020)ijmvsc
8th International Conference of Managing Information Technology (CMIT 2020) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the area advanced Computer Science and information technology. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of advanced CS & IT. Core areas of advanced IT and multi-disciplinary and its applications will be covered during the conferences. to discuss the latest issues and advancement in the area of advanced CS & IT. Core areas of advanced IT and multi-disciplinary and its applications will be covered during the conferences.
This document outlines the topics to be covered in a course on digital business and e-commerce. It includes:
1. An introduction to the digital transformation and topics like data, cloud computing, social media, mobile technologies, and the sharing economy.
2. A discussion of the digital platform and technologies like web standards, APIs, apps, and big/open data.
3. Sections on e-business, digital marketing, how digital disruption impacts companies, and perspectives from fields like media and industry 4.0.
4. Key principles of digital business and marketing like ubiquity, global reach, standardization, richness, and personalization through data and algorithms are also summarized.
Data is poised to play an important role in the enterprises of the future, with businesses looking to scale up production and recover costs. Visit: https://www.raybiztech.com/blog/data-analytics/what-are-big-data-data-science-and-data-analytics
Dark Data Revelation and its Potential BenefitsPromptCloud
Dark data refers to the large amounts of unused data organizations collect during regular business activities. While organizations invest heavily in collecting data, much of it remains unused. There are three main types of dark data: existing unstructured internal data, non-traditional unstructured external data, and data available on the deep web. Analyzing dark data can provide valuable insights but also risks such as privacy issues. Some companies are already leveraging dark data for applications like fraud detection and personalization in retail. Approaching dark data requires getting the right data, augmenting with external sources, building data talent, and using advanced visualization tools.
CITE Start Thinking Big Data 2019 01-30 FINALJon Kostyniuk
Whatever the size or type of organization, Big Data has permeated our transportation industry. It is no longer a question of IF Big Data will be useful, but instead WHY is it useful and HOW can we best apply it. This presentation aims to address how we can leverage existing services and available partnerships in transportation, consider new and emerging technologies, and determine strategy for what’s to come in transportation, including connected and autonomous vehicles. While it may be a huge challenge to solve transportation problems with Big Data, it can help us make better travel decisions today and plan for better infrastructure tomorrow.
8th International Conference of Managing Information Technology (CMIT 2020)Zac Darcy
8th International Conference of Managing Information Technology (CMIT 2020) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the area advanced Computer Science and information technology. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of advanced CS & IT. Core areas of advanced IT and multi-disciplinary and its applications will be covered during the conferences. to discuss the latest issues and advancement in the area of advanced CS & IT. Core areas of advanced IT and multi-disciplinary and its applications will be covered during the conferences.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Computer Science & Information Technology.
This document discusses opportunities for data-driven growth and innovation. It explains that analyzing large amounts of data from various sources (i.e. big data) can provide valuable insights to create new products and services, improve efficiency, and generate new revenue streams. Specifically, it provides examples of how telecom operators can leverage network usage data and customer insights to partner with other industries and monetize consumer data while respecting privacy. Transparency around data usage is important to build customer trust.
TechConnex Big Data Series - Big Data in BankingAndre Langevin
Big Data in Banking focuses on the use of big data and Hadoop in the Canadian banking sector. The key points are:
1) The RDARR regulatory project is driving major investments in data management by the big six Canadian banks, totaling around $800 million over three years. This has led banks to implement Hadoop data hubs to centralize data.
2) Adoption of Hadoop for risk applications is still in early stages, with a focus on regulatory reporting. Capital markets has led adoption so far.
3) Lessons learned include choosing flexible Hadoop distributions, using native Hadoop tools for best performance, and designing hubs for data engineers rather than casual users. Infrastructure must have
The Emergence of Alt-Data and its ApplicationsPromptCloud
Alternative data is information gathered from non-traditional information sources. Analysis of this data can provide insights beyond that which an industry’s regular data sources are capable of providing. Here is all you should know about alt-data.
This document discusses big data mining and the Internet of Things. It first presents challenges with big data mining including modeling big data characteristics, identifying key challenges, and issues with statistical analysis of IoT data. It then describes an architecture called IOT-StatisticDB that provides a generalized schema for storing sensor data from IoT devices and a distributed system for parallel computing and statistical analysis of IoT big data. The system includes query operators for data retrieval and statistical analysis of IoT data in areas like transportation networks.
Big data offers companies a big advantage if they can harness enormous data sets that were previously impossible to process. The document discusses how big data is transforming business models through creative destruction, as more data is created every day from various sources. It provides examples of how companies in various industries like retail, banking, and manufacturing are using big data for customer intimacy, product innovation, and improving operations. Specifically, companies are able to better customize products and services, improve supply chain management, and gain real-time insights from vast amounts of structured and unstructured data.
Big data offers opportunities for companies to gain competitive advantages through improved customer intimacy, product innovation, and operations. The document discusses how various companies are leveraging big data across industries. It notes that 45% of companies have implemented big data initiatives in the past two years and over 90% of Fortune 500 companies will have initiatives underway soon. Harnessing big data's potential requires understanding where it can create value within a company and having the right organizational structure, technology investments, and plan to capture those benefits.
D2 d turning information into a competive asset - 23 jan 2014Henk van Roekel
Understanding the evolution of Business Intelligence and Analytics and the challenges and opportunities that come with it. Exploring CGI's Data2Diamonds™ approach ensuring financial sound, technical viable and socially desirable Big Data initiatives.
This document provides an overview of how big data and data science can create value for banks. It discusses how banks generate large amounts of structured and unstructured data from various sources that can be analyzed to improve areas like fraud detection, customer churn analysis, risk management, and marketing campaign optimization. The document also provides case studies of how one company, InData Labs, has helped various banks leverage big data analytics to solve business problems in these areas.
This document discusses how a big box retailer utilized big data to improve its business. It outlines the steps the retailer took:
1) It identified where big data could create advantages, such as predictive analytics to forecast sales declines. This would allow the retailer to be more proactive.
2) It built future capability scenarios to determine how to leverage big data, such as using social media data to predict problems.
3) It defined the benefits and roadmap for implementing big data, including investing millions over 5 years for a positive return. Benefits would include more consistent, faster information and insights.
The document provides details on how the retailer methodically planned and aligned its big data strategy to its business needs
Presentation of Digital Catapult's personal data activities in relation to Industry 4.0, digital transformation and advanced manufacturing actions, as presented by Digital Catapult's Michele Nati, Lead Technologist of Personal Data and Trust.
What is big data ? | Big Data ApplicationsShilpaKrishna6
Big data is similar to ‘small data’ but bigger in size. It is a term that describes the large volume of data both structured and unstructured. Big data generates value from the storage and processing of very large quantities of digital information that cannot be analyzed with traditional computing techniques
In this white paper, we’ll spread the light on such issues as:
- What big data is
- How data science creates a real value in retail
- 5 big data use-cases revealing how retail companies can turn their customers’ data in action
Unlocking Value of Data in a Digital AgeRuud Brink
InfoGraphic about Intelligence Hubs as accelerator of the Digital organisation. Five steps how you could think big, and act small to unlock value of Data in your organisation. Contact me for the office A0 poster.
This document discusses key technology trends impacting the retail industry in 2016, as identified by IBM. It covers four main dynamics of transformation: analytics, cloud computing, mobile and social engagement, and security. Analytics and cognitive computing allow retailers to gain insights from big data to personalize customer experiences. Cloud computing enables speed, agility and flexible infrastructure upgrades. Mobile and social technologies connect retailers with customers in real-time and on-the-go. Security is a growing concern as data volumes increase and attack sophistication rises. The document provides an overview of IBM solutions that address these trends, such as analytics platforms, cloud services, and security offerings to help retailers adapt to ongoing disruption and digital transformation in retail.
Big data is playing an increasingly important role in the retail industry. The document discusses how retailers can use big data analytics to gain competitive advantages through improved marketing, merchandising, operations, supply chain management, and new business models. Specifically, big data enables retailers to better understand customer behavior, personalize offerings, optimize pricing and inventory, and process customer information in real-time to improve the shopping experience.
This document discusses how big data can enable the travel and tourism industries. It defines big data as large datasets characterized by their volume, velocity, variety, and veracity. Big data comes from a variety of sources as people leave digital traces online and through mobile technologies. The benefits of big data for businesses include improved customer experience personalization, optimized marketing and products, predictive analytics, and risk management. The big data market is expected to double from 2014 to 2018. Future developments include improvements in data processing, centralized data repositories, and analytics solutions in the public cloud to reduce costs and security risks. Big data can deliver business insights, innovation, better customer relationships, and continuously improved experiences for the tourism industry.
L'economia europea dei dati. Politiche europee e opportunità di finanziamento...Data Driven Innovation
L'economia europea dei dati: soluzioni politiche e giuridiche per realizzare un'economia dei dati a livello di Unione Europea, nell'ambito della strategia per il mercato unico digitale. La consultazione pubblica 'Building the European Data Economy'. Il paternariato pubblico privato (PPP) Big Data Value ed opportunità di finanziamento in Horizon 2020. L'incubatore Data Pitch: opportunità per Start-up e Piccole e Medie Imprese.
Blockchain for Supply Chain Market Competitive Research And Precise Outlook 2...subishsam
The research firm Contrive Datum Insights has just recently added to its database a report with the heading global Blockchain for Supply Chain Market.Both primary and secondary research methodologies have been utilised in order to conduct an analysis of the worldwide Blockchain for Supply Chain Market. In order to provide a comprehensive comprehension of the topic at hand, it has been summed up using appropriate and accurate market insights. According to Contrive Datum Insights, this worldwide comprehensive report is broken up into several categories in order to present the data in a way that is understandable, succinct, and presented in a professional manner
The Future Of Big Data In Business – 4 Emerging Trends In 2022.pptxArpitGautam20
Here are some exciting trends that will dictate the future of Big Data in Business in 2022. Read on to know about these exciting developments. https://arsr.tech/the-future-of-big-data-in-business-4-emerging-trends-in-2022/
This document discusses several topics related to data and data-driven businesses. It begins by outlining trends in big data and machine learning. It then discusses how to build data-centric businesses by identifying data opportunities and sources, understanding the data lifecycle, and extracting value from data. Examples are provided of Netflix as a data-driven company. The future of professions in a data-driven world is also examined, as well as talent scarcity issues and the need for data-savvy managers. The document provides an overview of many relevant topics at the intersection of data and business.
According to Gartner, Big Data will be the next “disruptive technology” and will transform customer relationship management industry.The possibilities that Big Data offers are endless but companies first need to invest in CRM software
Smart Data Module 1 introduction to big and smart datacaniceconsulting
This document provides an overview of big and smart data. It defines big data as large volumes of structured, unstructured, and semi-structured data that is difficult to manage and process using traditional databases. It discusses how big data becomes smart data through analysis and insights. Examples of smart data applications are also provided across various industries like retail, healthcare, transportation and more. The document emphasizes that in order to start smart with data, companies need to review their existing data, ask the right questions, and form actionable insights rather than just conclusions.
La base para optimizar y potenciar la toma de decisiones en cualqueir empresa es la información. Pero no la información en bruto, sino aquella de la que podemos obtener valor tras su análisis.
Running at the Speed of Digital: Hyper-Digital Information ManagementCognizant
Consumers’ need for instant access to information through multiple channels is growing. While some companies in specific segments of the IS industry offer impressive capabilities, none provide the full range of technologies and resources needed to support a cohesive, all-inclusive, digitally-equipped environment for analyzing, ingesting, managing, and delivering content across the value chain. In a hyper-digital environment, IS organizations can distribute content at breakthrough speeds — anytime, anywhere.
Similar to D2-5_BIG DATA EmilianoAnzellotti_v2 [ (20)
2. 1
Agenda
• The European Commission Communication
• Big Data
• The definition,
• The Market sentiment
• Tipical Benefits
• What will mean to endorse the «BD approach»
• Applications for the card business
• What can be done by (the unbundled) schemes?
3. 2
EC concerns on BIG DATA
• “We witness a new industrial revolution driven by
digital data, computation and automation. Human
activities, industrial processes and research all lead
to data collection and processing on an
unprecedented scale, spurring new products and
services as well as new Business processes and
scientific methodologies.”
• “the European digital economy has been slow in
embracing the data revolution compared to the USA
and also lacks comparable industrial capability.
Research and innovation (R&I) funding on data in
the EU is sub-critical and the corresponding activities
are largely uncoordinated.”
• “the complexity of the current legal environment
together with the insufficient access to large datasets
and enabling infrastructure create entry barriers to
SMEs and stifle innovation”
4. 3
EC calls for an action
According to EC «the EU must:
• support "lighthouse" data initiatives capable of improving competitiveness, quality of public services
and citizen's life
• develop its enabling technologies, underlying infrastructures and skills, particularly to the benefit of
SMEs
• extensively share, use and develop its public data resources and research data infrastructures
• focus public R&I on technological, legal and other bottlenecks
• make sure that the relevant legal framework and the policies, such as on interoperability, data
protection, security and IPR are data‐friendly
• rapidly conclude the legislative processes on the reform of the EU data protection framework, network
and information security, and support exchange and cooperation between the relevant enforcement
authorities
• accelerate the digitisation of public administration and services to increase their efficiency
• use public procurement to bring the results of data technologies to the market
5. 4
Agenda
• The European Commission Communication
• Big Data
• The definition,
• The Market sentiment
• Tipical Benefits
• What will mean to endorse the «BD approach»
• Applications for the card business
• What can be done by (the unbundled) schemes?
6. 5
BIG DATA Definition
According to EC:
“Data is "a reinterpretable representation of information in a formalized manner, suitable for
communication, interpretation or processing". Data can either be created/authored by people or
generated by machines/sensors, often as a "by‐product". Examples: geospatial information,
statistics, weather data, research data, etc.
The term "big data" refers to large amounts of different types of data produced with high
velocity from a high number of various types of sources. Handling today's highly variable and
real‐time datasets requires new tools and methods, such as powerful processors, software and
Algorithms”
7. 6
Agenda
• The European Commission Communication
• Big Data
• The definition,
• The Market sentiment
• Tipical Benefits
• What will mean to endorse the «BD approach»
• Applications for the card business
• What can be done by (the unbundled) schemes?
8. 7
The Market sentiment
“Every 2 days we create as much information as we did from the
beginning of time until 2003“
“data have swept into every industry and business function and are
now an important factor of production”
“Over 90% of all the data in the world was created in the past 2 years.”
“The total amount of data being captured and stored by industry
doubles every 1.2 years“
“The big data industry is expected to grow from US$10.2 billion in 2013
to about US$54.3 billion by 2017.”
“Google alone processes on average over 40 thousand search queries
per second, making it over 3.5 billion in a single day.”
“use of big data will become a key basis of competition and growth for
individual firms”
Sources available on request
9. 8
Agenda
• The European Commission Communication
• Big Data
• The definition,
• The Market sentiment
• Tipical Benefits
• What will mean to endorse the «BD approach»
• Applications for the card business
• What can be done by (the unbundled) schemes?
10. 9
Big data levers grouped by function
Function Big data lever
Marketing • Cross selling
• Location based marketing
• In store behavior analisys
• Customer segmentation
• Sentiment analisys
• Enhaced customer experience
Merchandising • Pricing optimization
• Placement optimization
Operation • Performance trasparency
• Labor optimization
Supply chain • Distribution and logistic optimization
• Supplier optimization
Updated
business model
• Price comparison service
• Web based prices
(source MGI)
11. 10
Agenda
• The European Commission Communication
• Big Data
• The definition,
• The Market sentiment
• Tipical Benefits
• What will mean to endorse the «BD approach»
• Applications for the card business
• What can be done by (the unbundled) schemes?
12. 11
What will mean to endorse the «BD approach»
Big Data does not automatically means Big Value: the whole point of a big data strategy is to develop a system
which moves data along 4 boxes
Data sources Data storage Data analysis Data output
This is where the data is
arrives at your
organization. It includes
everything from
monitoring or measuring
aspects of your
operations. One of the
first steps in setting up a
data strategy is assessing
what you have here, and
measuring it against what
you need to answer the
critical questions you
want help with.
This is where your Big
Data lives, once it is
gathered from your
sources. As the volume of
data generated and stored
by companies has started
to explode, sophisticated
but accessible systems
and tools have been
developed (e.g. Apache
Hadoop DFS or Google
File system)
When you want to use the
data you have stored to
find out something useful,
you will need to process
and analyze it. A common
method is by using some
stat tool to select the
elements of the data that
you want to analyze, and
putting it into a format
from which insights can
be gleaned. Tools will
query the data, and will
use to determine trends,
as well as drawing their
conclusions from manual
analysis
The insights gleaned
through the analysis is
passed on to the
people who can take
action to benefit from
them. Clear and concise
communication
(particularly if your
decision‐makers don’t
have a background in
statistics) is essential,
and this output can
take the form of
reports, charts, figures
and key
recommendations
13. 12
Agenda
• The European Commission Communication
• Big Data
• The definition,
• The Market sentiment
• Tipical Benefits
• What will mean to endorse the «BD approach»
• Applications for the card business
• What can be done by (the unbundled) schemes?
15. 14
Applications for the card business
An example: “MasterCard Helps Retailers Perform Better with Big Data” ( cit. Mastercard Manager)
Apart from of course preventing fraudulent behaviour and identifying and preventing fraudulent transaction before they occur, Mastercard
applies big data in another way. It knows what everyone buys and they are using big data techniques to offer reports, insights, customer
information and forecasts to their merchants. The data that MasterCard obtains is not ready to use. With each transaction they receive
data regarding the amount of the transaction, the merchant name, the time, date and the credit card number. They then strip the account
number and make the data anonymous. The data obtained is messy as the name of the merchant on a point‐of‐sale machine is a free‐text
field, resulting in many different names for the same merchants, retail chains or businesses. In the past years MasterCard has worked on
creating the rules, algorithms and engines to clean such data and make it usable. For MasterCard, big data is big business and with all
their data at hand they are helping merchants gain better insights and more revenue while in the mean time grow their own business.
FRAUDS PREVENTION CARDHOLDERS SEGMENTATION
MERCHANT SUPPORT NEW PRODUCTS
SCHEMES ARE POTENTIAL SOURCES AND USERS OF BIG DATA
THERE IS A NEED TO UNDERSTAND IF A SUITABLE APPROACH /STRATEGY
CAN BE FOUND
16. 15
Agenda
• The European Commission Communication
• Big Data
• The definition,
• The Market sentiment
• Tipical Benefits
• What will mean to endorse the «BD approach»
• Applications for the card business
• What can be done by (the unbundled) schemes?
17. 16
What can be done by (the unbundled) schemes?
Card Schemes may be part of the Big Data initiatives, in order to :
‐ Clarify the business needs for the involved players
‐ Discuss and support the initiatives activated by the EC
‐ Agree on criteria for the data analisys
‐ indentify common layers for IT interventions
‐ Suggest focused market initiatives
‐ ….