Big data refers to the massive amounts of digital data being created every day from various sources such as social media, sensors, photos, videos, and online activities. This data is characterized by its volume, velocity, variety, and veracity. New technologies allow businesses and organizations to analyze these large, diverse, and complex data sets to gain insights and add value in many ways such as improving customer targeting, optimizing processes, enhancing health research, bolstering security efforts, and upgrading city infrastructure. While big data is transforming many industries, its full potential is just beginning to be realized.
The document discusses how big data benefits consumers in 5 key ways: 1) It allows companies to improve customer service based on feedback collected from reviews and social media. 2) Product improvements are made based on customer feedback collected online. 3) Big data helps connect consumers with relevant deals and advertisements. 4) Security measures are constantly improving to prevent hacking based on data collected. 5) Big data helps prevent and solve crimes when used by government and law enforcement.
WidasConcepts is a consulting firm that helps clients implement Internet of Things (IoT) and Big Data solutions. They provide services such as IoT and Big Data consulting, development of IoT and intelligent search solutions, and technology consulting. As more devices and objects become connected through IoT, WidasConcepts believes it will drive innovation and create new opportunities for businesses through insights gained from collecting and analyzing large amounts of data in real-time. Their goal is to help clients identify how IoT and Big Data can increase competitiveness and add value to their organizations.
The document discusses facts about the growth of big data and how data is generated from many sources. It notes that every person and object generates data, an average person now processes more data than people in history, and data is doubling every two years. It also provides examples of how companies are using big data to personalize experiences, optimize operations, and drive higher sales and conversions.
Big Data is the process of harnessing massive Data – structured or unstructured via the means of sensors, actuators, embedded software’s, & network grids.
This document discusses big data, providing definitions and outlining its key characteristics of volume, velocity, and variety. It describes processes involved like integrating disparate data stores and employing Hadoop MapReduce. Sources of big data are identified as mobile devices, sensors, social media, etc. Tools used include distributed servers, storage, and databases. Statistics on data generated by companies like Facebook and Twitter are provided. Applications of big data include improving science, healthcare, finance, and security. Advantages include access to vast information, while disadvantages include costs and privacy issues.
Big data refers to the massive amounts of digital data being created every day from various sources such as social media, sensors, photos, videos, and online activities. This data is characterized by its volume, velocity, variety, and veracity. New technologies allow businesses and organizations to analyze these large, diverse, and complex data sets to gain insights and add value in many ways such as improving customer targeting, optimizing processes, enhancing health research, bolstering security efforts, and upgrading city infrastructure. While big data is transforming many industries, its full potential is just beginning to be realized.
The document discusses how big data benefits consumers in 5 key ways: 1) It allows companies to improve customer service based on feedback collected from reviews and social media. 2) Product improvements are made based on customer feedback collected online. 3) Big data helps connect consumers with relevant deals and advertisements. 4) Security measures are constantly improving to prevent hacking based on data collected. 5) Big data helps prevent and solve crimes when used by government and law enforcement.
WidasConcepts is a consulting firm that helps clients implement Internet of Things (IoT) and Big Data solutions. They provide services such as IoT and Big Data consulting, development of IoT and intelligent search solutions, and technology consulting. As more devices and objects become connected through IoT, WidasConcepts believes it will drive innovation and create new opportunities for businesses through insights gained from collecting and analyzing large amounts of data in real-time. Their goal is to help clients identify how IoT and Big Data can increase competitiveness and add value to their organizations.
The document discusses facts about the growth of big data and how data is generated from many sources. It notes that every person and object generates data, an average person now processes more data than people in history, and data is doubling every two years. It also provides examples of how companies are using big data to personalize experiences, optimize operations, and drive higher sales and conversions.
Big Data is the process of harnessing massive Data – structured or unstructured via the means of sensors, actuators, embedded software’s, & network grids.
This document discusses big data, providing definitions and outlining its key characteristics of volume, velocity, and variety. It describes processes involved like integrating disparate data stores and employing Hadoop MapReduce. Sources of big data are identified as mobile devices, sensors, social media, etc. Tools used include distributed servers, storage, and databases. Statistics on data generated by companies like Facebook and Twitter are provided. Applications of big data include improving science, healthcare, finance, and security. Advantages include access to vast information, while disadvantages include costs and privacy issues.
Big data is a term for datasets that are so large or complex that traditional data processing applications are inadequate. Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualization, querying, updating and information privacy.
Lets ideate and discuss more:
www.extentia.com/contact-us
Big Data Analytics Trends and Industry Predictions to Watch For in 2021Way2Smile
The fact that big data is going to change the face of major industries is widely accepted. But, what Data analytics trends should we watch out for? Let's find out!
Learn More at : https://bit.ly/2BOj4hD.
This document introduces social data day London and discusses the growth of social media. It notes that 1.7 billion people are on social networks, representing 67% of internet users. Social media engagement occupies 13 minutes of every UK internet hour. The document discusses how social media has fueled a data and analytics revolution by creating vast amounts of user data and interactions outside of traditional business silos. It frames social media data as big, fast, complex and unstructured. Examples are given of companies using social listening and analytics to improve marketing, product development and customer loyalty. The challenges of analyzing social media data due to its scale, noise and lack of structure are also mentioned.
Why Big Data is the foundation for Digital Transformation ?Koray Sonmezsoy
ClickZ Live Hong Kong 4-6 Aug 2015
http://www.clickzlive.com/hongkong/agenda-day1.php
Digital transformation is top-of-mind for executives across many industries. Often when thinking of digital transformation, marketers are thinking about how to amplify their digital presence through website enhancements, mobile design and social platforms. While those are certainly key tactics in a robust digital strategy, they are initiatives that must be informed by and based on data.
This document provides an overview of digital transformation and big data. It discusses key trends driving digital transformation like digitalization, social media, and mobility. It also covers what big data is, various sources of big data, how insights can be gained from big data analysis, and some of the ethical considerations around big data. The document outlines approaches for analyzing big data, including dealing with false correlations and overfitting models to vast amounts of data.
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.
The Past - the History of Business IntelligencePhocas Software
Learn the history of business intelligence in this three part series. In part one, we discuss how business intelligence software used to be (the past).
Web Scraping reveals top tech trends and company’s media mentions in 2017PromptCloud
To understand the tech landscape and its coverage in 2017, we deployed our in-house web crawler to extract the article titles from two popular outlets and performed text mining on the dataset to uncover the top buzzwords, companies and products.
This presentation, by big data guru Bernard Marr, outlines in simple terms what Big Data is and how it is used today. It covers the 5 V's of Big Data as well as a number of high value use cases.
This document discusses cybersecurity challenges in the era of big data. It defines big data as datasets that are too large for traditional database tools to capture, store, manage, and analyze. Many sectors now deal with terabytes to petabytes of data. The document notes that data has become "the new oil" and raises important questions around privacy, security, ownership and governance of large datasets. Proper data protection laws and authorities are needed to balance the benefits of big data with these challenges.
This infographic document provides sources for statistics about big data, including facts that will shock about analytics and big data, how the big data universe is beginning to explode, facts that prove the need for smarter CRM systems in business, and powerful facts about big data and analytics. The document lists 4 URLs as sources for further information on big data facts and statistics.
The mountain of Big Data is growing, presenting immense opportunities for businesses ready to summit its peak, but the journey requires careful preparation. Integra helps businesses equip their network infrastructure to handle big requirements for Big Data—with fully-symmetrical Ethernet solutions designed to deliver low-latency, high-bandwidth connectivity between organizational peers, the cloud, and the servers where your data is stored. Our infographic, "Summiting the Mountain of Big Data" will help you understand how big "Big Data" really is; who's producing, consuming, managing and storing all that data; the business advantages you can capture by tapping into its power; and how you can prepare your organization to meet its demands—resulting in Big Gains from Big Data.
The document discusses big data, analytics, and their applications. It defines big data as large, complex datasets that are difficult to manage with traditional databases. Big data is characterized by its volume, velocity, and variety. Examples are given of how retailers, telecom companies, and e-retailers use big data analytics to gain insights. The document also outlines approaches to analytic development and discusses how various organizations use big data analytics in practice.
SME Breakfast Seminar - Keynote Session - The Data LandscapeNathean Technologies
This document summarizes a data management breakfast briefing hosted by Nathean Technologies. The agenda included presentations on the data landscape, achieving successful reporting projects, a case study, and the agile approach. It discusses how the data landscape is changing with trends in mobile, social, and big data. Mobile devices and social media are generating more varied data sources in real-time. Big data involves analyzing large, diverse, and fast-moving data to provide business value. Organizations must adapt their IT strategies and develop new skills to leverage these changes.
Index:
1) The Importance of Data
2) What is Big Data Concept
3) Big Data vs. Cloud Computing
4) The basic idea behind Big Data
5) Why do we use Big Data
6) Top 10 companies using Big Data
7) What kind of data is Big Data
8) Is Privacy a value
9) Future of Big Data by 2020
Data science and its potential to change business as we know it. The Roadmap ...InnoTech
The document summarizes a presentation on data science and its potential to change business. It discusses how organizations can increase their data science maturity and capabilities to gain more value from data. As data volumes continue growing exponentially, data science can help organizations move from simple reporting to predictive analytics in order to make real-time decisions. The presentation examines how data science is an emerging field that incorporates techniques from many areas and how organizations can assess their analytics maturity.
CPA ONE 2016 - Big data: big decisions or big fallacyLaurie Desautels
Laurie Desautels presented on "Big data: big decisions or big fallacy" at CPA Canada's national conference in September 2016. The presentation discussed what big data is, the language of analytics, lessons learned, and implications for accountants. Big data refers to large volumes of structured, unstructured and semi-structured data that is growing exponentially. Analytics can extract insights from data to help organizations make more informed decisions. Finance functions are spending more time on data analysis and generating business insights. Both human judgment and machine learning algorithms will play important roles in decision-making. Organizations must apply the right analytics approaches to different types of decisions.
Great Bigdata eBook giving a perspective of Bigdata Analytics Predictions for 2016. Learn about the milestones, landmarks and futures of this fast growing arena.
The document outlines an agenda for a Big Data breakfast event hosted by Rocket Fuel, including welcome remarks, a panel discussion on big data and AI, and a presentation by the CEO of Rocket Fuel on how the company uses big data and artificial intelligence for digital media. The event features speakers from Rocket Fuel and other companies discussing topics like the growth of big data, applications of big data in marketing, and how big data is changing the advertising industry.
Big data is a term for datasets that are so large or complex that traditional data processing applications are inadequate. Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualization, querying, updating and information privacy.
Lets ideate and discuss more:
www.extentia.com/contact-us
Big Data Analytics Trends and Industry Predictions to Watch For in 2021Way2Smile
The fact that big data is going to change the face of major industries is widely accepted. But, what Data analytics trends should we watch out for? Let's find out!
Learn More at : https://bit.ly/2BOj4hD.
This document introduces social data day London and discusses the growth of social media. It notes that 1.7 billion people are on social networks, representing 67% of internet users. Social media engagement occupies 13 minutes of every UK internet hour. The document discusses how social media has fueled a data and analytics revolution by creating vast amounts of user data and interactions outside of traditional business silos. It frames social media data as big, fast, complex and unstructured. Examples are given of companies using social listening and analytics to improve marketing, product development and customer loyalty. The challenges of analyzing social media data due to its scale, noise and lack of structure are also mentioned.
Why Big Data is the foundation for Digital Transformation ?Koray Sonmezsoy
ClickZ Live Hong Kong 4-6 Aug 2015
http://www.clickzlive.com/hongkong/agenda-day1.php
Digital transformation is top-of-mind for executives across many industries. Often when thinking of digital transformation, marketers are thinking about how to amplify their digital presence through website enhancements, mobile design and social platforms. While those are certainly key tactics in a robust digital strategy, they are initiatives that must be informed by and based on data.
This document provides an overview of digital transformation and big data. It discusses key trends driving digital transformation like digitalization, social media, and mobility. It also covers what big data is, various sources of big data, how insights can be gained from big data analysis, and some of the ethical considerations around big data. The document outlines approaches for analyzing big data, including dealing with false correlations and overfitting models to vast amounts of data.
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.
The Past - the History of Business IntelligencePhocas Software
Learn the history of business intelligence in this three part series. In part one, we discuss how business intelligence software used to be (the past).
Web Scraping reveals top tech trends and company’s media mentions in 2017PromptCloud
To understand the tech landscape and its coverage in 2017, we deployed our in-house web crawler to extract the article titles from two popular outlets and performed text mining on the dataset to uncover the top buzzwords, companies and products.
This presentation, by big data guru Bernard Marr, outlines in simple terms what Big Data is and how it is used today. It covers the 5 V's of Big Data as well as a number of high value use cases.
This document discusses cybersecurity challenges in the era of big data. It defines big data as datasets that are too large for traditional database tools to capture, store, manage, and analyze. Many sectors now deal with terabytes to petabytes of data. The document notes that data has become "the new oil" and raises important questions around privacy, security, ownership and governance of large datasets. Proper data protection laws and authorities are needed to balance the benefits of big data with these challenges.
This infographic document provides sources for statistics about big data, including facts that will shock about analytics and big data, how the big data universe is beginning to explode, facts that prove the need for smarter CRM systems in business, and powerful facts about big data and analytics. The document lists 4 URLs as sources for further information on big data facts and statistics.
The mountain of Big Data is growing, presenting immense opportunities for businesses ready to summit its peak, but the journey requires careful preparation. Integra helps businesses equip their network infrastructure to handle big requirements for Big Data—with fully-symmetrical Ethernet solutions designed to deliver low-latency, high-bandwidth connectivity between organizational peers, the cloud, and the servers where your data is stored. Our infographic, "Summiting the Mountain of Big Data" will help you understand how big "Big Data" really is; who's producing, consuming, managing and storing all that data; the business advantages you can capture by tapping into its power; and how you can prepare your organization to meet its demands—resulting in Big Gains from Big Data.
The document discusses big data, analytics, and their applications. It defines big data as large, complex datasets that are difficult to manage with traditional databases. Big data is characterized by its volume, velocity, and variety. Examples are given of how retailers, telecom companies, and e-retailers use big data analytics to gain insights. The document also outlines approaches to analytic development and discusses how various organizations use big data analytics in practice.
SME Breakfast Seminar - Keynote Session - The Data LandscapeNathean Technologies
This document summarizes a data management breakfast briefing hosted by Nathean Technologies. The agenda included presentations on the data landscape, achieving successful reporting projects, a case study, and the agile approach. It discusses how the data landscape is changing with trends in mobile, social, and big data. Mobile devices and social media are generating more varied data sources in real-time. Big data involves analyzing large, diverse, and fast-moving data to provide business value. Organizations must adapt their IT strategies and develop new skills to leverage these changes.
Index:
1) The Importance of Data
2) What is Big Data Concept
3) Big Data vs. Cloud Computing
4) The basic idea behind Big Data
5) Why do we use Big Data
6) Top 10 companies using Big Data
7) What kind of data is Big Data
8) Is Privacy a value
9) Future of Big Data by 2020
Data science and its potential to change business as we know it. The Roadmap ...InnoTech
The document summarizes a presentation on data science and its potential to change business. It discusses how organizations can increase their data science maturity and capabilities to gain more value from data. As data volumes continue growing exponentially, data science can help organizations move from simple reporting to predictive analytics in order to make real-time decisions. The presentation examines how data science is an emerging field that incorporates techniques from many areas and how organizations can assess their analytics maturity.
CPA ONE 2016 - Big data: big decisions or big fallacyLaurie Desautels
Laurie Desautels presented on "Big data: big decisions or big fallacy" at CPA Canada's national conference in September 2016. The presentation discussed what big data is, the language of analytics, lessons learned, and implications for accountants. Big data refers to large volumes of structured, unstructured and semi-structured data that is growing exponentially. Analytics can extract insights from data to help organizations make more informed decisions. Finance functions are spending more time on data analysis and generating business insights. Both human judgment and machine learning algorithms will play important roles in decision-making. Organizations must apply the right analytics approaches to different types of decisions.
Great Bigdata eBook giving a perspective of Bigdata Analytics Predictions for 2016. Learn about the milestones, landmarks and futures of this fast growing arena.
The document outlines an agenda for a Big Data breakfast event hosted by Rocket Fuel, including welcome remarks, a panel discussion on big data and AI, and a presentation by the CEO of Rocket Fuel on how the company uses big data and artificial intelligence for digital media. The event features speakers from Rocket Fuel and other companies discussing topics like the growth of big data, applications of big data in marketing, and how big data is changing the advertising industry.
Big data 1 4 vint-sogeti-on-big-data-1-of-4-creating clarity with big dataRick Bouter
This document discusses the rise of Big Data and its importance for organizations. It notes that digital data is fueling a new industrial revolution. Big Data represents the combination of transactions, interactions, and observations. The growth of digital data from various sources is expanding exponentially. To gain competitive advantages, organizations must implement total data management and analyze all available data, not just samples. This will allow them to better understand customer behavior, detect fraud, and make improved business decisions. The document outlines several Big Data challenges that organizations face and questions for the reader regarding their Big Data profile and management.
Since 2005, when the term “Big Data” was launched, Big Data has become an increasingly topical theme. In terms of technological development and business adoption, the domain of Big Data has made powerful advances; and that is putting it mildly.
In this initial report on Big Data, the first of four, we give answers to questions concerning what exactly Big Data is, where it differs from existing data classification, how the transformative potential of Big Data can be estimated, and what the current situation (2012) is with regard to adoption and planning.
VINT attempts to create clarity in these developments by presenting experiences and visions in perspective: objectively and laced with examples. But not all answers, not by a long way, are readily available. Indeed, more questions will arise – about the roadmap, for example, that you wish to use for Big Data. Or about governance. Or about the way you may have to revamp your organization. About the privacy issues that Big Data raises, such as those involving social analytics. And about the structures that new algorithms and systems will probably bring us.
http://www.ict-books.com/books/inspiration-trends
Big data for the next generation of event companiesRaj Anand
Only on rare occasions do we consider the amount of data that our every action produces. It’s pretty overwhelming just to think about every interaction on every app on every device in our bag or pocket, in every environment and every location.
But then there’s more. We also use access cards, transportation passes and gym memberships. We have hobbies, we travel, buy groceries, books and maybe warm beverages on rainy days. We are part of multiple communities. Looking around billions of people are doing the same. Our every action produces data about us. This is big.
We believe taking an interest in this wealth of data will be the key to success for next generation Event Companies.
We are living in a fast changing world, where it’s ever more important to foresee trends and seize opportunities. A global perspective is not a strategic advantage anymore it is a necessity.
Event companies are facilitators , they create common grounds for brands and audiences, by thoughtfully connecting goals and means. Having a deep understanding of customer behaviour, group psychology, digital habits, brand interaction, communication, and awareness through unlocking the power of big data will ensure next generation event companies thrive on strategy.
Big data comes from a variety of sources such as sensors, social media, digital pictures, purchase transactions, and cell phone GPS signals. The volume of data created each day is vast, with over 2.5 quintillion bytes created in the last two years alone. Big data has four characteristics - volume, variety, velocity and value. It refers to both the large amount of data and the different types of structured and unstructured data. This data is generated and moves around at high speeds. While big data brings value, it can be difficult to analyze and extract useful insights from due to its scale and complexity. Technologies like Hadoop, HDFS, and MapReduce help process and analyze big data across large clusters of servers in a
This document discusses best practices for using Hadoop as an enterprise data hub. It provides an overview of how big data is driving new analytical workloads and the need for deeper customer insights. It discusses challenges with analyzing new sources of structured, unstructured and multi-structured data. It introduces the concept of a Hadoop enterprise data hub and data refinery to simplify access to new insights from big data. Key components of the data hub include a data reservoir to capture raw data from various sources, a data refinery to cleanse and transform the data, and publishing high value insights to data warehouses and other systems.
This document discusses the future of big data and new approaches for processing large and complex datasets. It defines big data as collections of data that are too large for traditional database systems to handle due to volume, velocity and variety. The document outlines sources of big data like social media, mobile devices, and networked sensors. It also describes frameworks like Hadoop and NoSQL databases that can analyze petabytes of distributed data in parallel. The conclusions state that new big data systems will extend and possibly replace traditional databases as more data becomes available from various sources.
This document contains information about a group project on big data. It lists the group members and their student IDs. It then provides a table of contents and summaries various topics related to big data, including what big data is, data sources, characteristics of big data like volume, variety and velocity, storing and processing big data using Hadoop, where big data is used, risks and benefits of big data, and the future of big data.
In this presentation, Paul Ballew, D&B's Chief Data and Analytics Officer, explains the three levels of insight needed to gain an informed perspective for smarter decisions involving big data.
Big data comes from a variety of sources such as sensors, social media, digital pictures, purchase transactions, and cell phone GPS signals. The volume of data created each day is vast, with 2.5 quintillion bytes created daily, 90% of which has been created in just the last two years. Big data is characterized by its volume, variety, velocity and value. It requires new tools like Hadoop and MapReduce to store and analyze data across distributed systems. When dealing with big data, once complex modeling can sometimes be replaced by simple counting techniques due to the large amount of data available. Companies are beginning to generate value from big data through new insights and business models.
Notes from the Observation Deck // A Data Revolution gngeorge
Notes from the Observation Deck will provide you with an examined look at the interesting phenomena and trends taking place around us today. We present them to you with the hope of sparking broader conversations, debates and ideas. Please use this as a resource for knowledge, inspiration and enjoyment.
Data foundation for analytics excellenceMudit Mangal
The document discusses predictive analytics and business insights. It covers what data analytics is and its challenges, the importance of data foundation and governance, security issues with data, and a retail use case. The future of data analytics is also discussed, with more structured, human interaction, and machine data expected to be analyzed. Establishing a robust data foundation is key to enabling trusted reporting and analytics.
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1. Andrea Gigli – StartupSaturday.it - #bigdataSS
The Big One – Big Data for Business and Social Innovation
13 Dicembre 2014 – Impact Hub Firenze
http://about.me/andrea.gigli @andrgig
2. We spend our day producing Data
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“We create as much information
in two days now as we did from
the dawn of man through 2003”
(2003) Eric Schmidt, former CEO at Google
2
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The Big One – Big Data for Social and Business Innovation – 13 Dicembre 2014
3. Data are everywhere…
3
The Big One – Big Data for Social and Business Innovation – 13 Dicembre 2014
4. Data are everywhere…
4
The Big One – Big Data for Social and Business Innovation – 13 Dicembre 2014
5. everywhere…
5
Human
Resources
Company
Customer
Relations
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The Big One – Big Data for Social and Business Innovation – 13 Dicembre 2014
6. … and everything is connected
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The Big One – Big Data for Social and Business Innovation – 13 Dicembre 2014
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Internet
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7. Power Law is the rule
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Costo della Tecnologia Potenza di Calcolo
The Big One – Big Data for Social and Business Innovation – 13 Dicembre 2014
8. BIG DATA Sensors/RFID/Devices
Click stream
User generated cnts
Social networks
Sentiment analysis
Spatial coordinates
Business data feeds
Video/Audio/Imgs
Speech to text
Product/Service logs
SMS/MMS
…
GimmeMore!
8
WEB Web logs
A/B testing
Offer history
Dynamic pricing
Dynamic funnels
Search marketing
Behavioral
targeting
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The Big One – Big Data for Social and Business Innovation – 13 Dicembre 2014
CRM
Customer segmentation
Offer details
Customer touches
Support contacts
….
ERP
Production Costs
Supply chain records
Purchase records
Payment records
Complexity
Dimension
9. Data are becoming Big
9
The Big One – Big Data for Social and Business Innovation – 13 Dicembre 2014
Volume
MB GB
TB
PB
Velocity
Variety
10. Why you should care about Big Data
10
“In God we trust, all
others bring data”
W. Edwards Deming
The Big One – Big Data for Social and Business Innovation – 13 Dicembre 2014
11. Are Data really useful?
11
2011, LaValle et al., “Big
Data, Analytics and the Path
from Insights to Value”, MIT
Sloan Management Review
The Big One – Big Data for Social and Business Innovation – 13 Dicembre 2014
12. What can you ask to Big Data?
What happened?
Why did it happen?
What will happen?
What is the best than
can happen and how?
12
Data Information Knowledge
Email, Logs, Medical
Records, Surveys,
Sport Performance,
Web Pages, Social
Network Activities,
Sensor Data,
Financials, Shopping
Charts….
Cleaning,
Wrangling,
Joining,
Debugging,
Analysis,
Visualization,
Reporting
The Big One – Big Data for Social and Business Innovation – 13 Dicembre 2014
Human &
Organizations
Activities, Biology,
Finance, Internet,
Production
systems, Service
delivery…
13. Kinds of Data Intelligence
13
J. & J. Kolb, The Big Data Revolution
The Big One – Big Data for Social and Business Innovation – 13 Dicembre 2014
14. Joining Data Intelligence, Knowledge & Strategy
Raw
Data
Predict & Act
14
The Big One – Big Data for Social and Business Innovation – 13 Dicembre 2014
Competitive Hedge
Analytical Maturity
What happened?
What is going
to happen?
What is the best that
it can happen?
Clean
Data
Generic
Predictive
Analytics
Standard
Reports
Predictive
Modeling
Optimization
Why did it
happen?
Experience & React
Advanced
Reports &
Analytics
15. (some) Opportunities behind Big Data
15
Smarter Healthcare Multi-channel sales Finance
The Big One – Big Data for Social and Business Innovation – 13 Dicembre 2014
Homeland Security
Telecom
Manufacturing
Traffic Control
Trading Analytics Fraud and Risk
LogAnalysis
Search Quality
Retail: Churn, NBO
16. Now it’s time to enjoy #bigdataSS
16
The Big One – Big Data for Social and Business Innovation – 13 Dicembre 2014