The document discusses big data, defining it as extremely large data sets that can be analyzed computationally to reveal patterns. It notes that advances in storage, processing power, and data availability have enabled the rise of big data. The key aspects of big data are described as the four V's: volume, velocity, variety, and veracity. Examples of how big data is used include optimizing business processes by analyzing social media, web search, and sensor data, and better understanding customers by combining traditional data sets with social media, browser, and sensor information to create predictive models.
Big Data Information Architecture PowerPoint Presentation SlideSlideTeam
Feel enthralled by all the attention by our Big data information architecture PowerPoint presentation slide offers. While designing the perfect framework for a durable system, it could get tricky to represent all the data in a systematic manner. Manifesting complex ideas in a simplified manner doesn't always comes handy. That's the reason we have well-researched formats and designs for professional and prolonging solutions. Our team of experts makes sure that all the PPT slides are framed to work for the best of the client. Numerous icons and images are used here for visual engagement. We have covered up every viewpoint of data structure possible, including, data market forecast, financial aspects, social media approach and different comparisons used in data analysis for an out of box view. Our sole and intriguing PowerPoint slides are your gateway to progress and serves you in holding your viewer's consideration towards the concept of discernment and improves the quality and accuracy of the business processes. Discourage injudicious comments with our Big Data Information Architecture PowerPoint Presentation Slide. Ensure folks adhere to the decorum.
Slides for class session I taught at USC Annenberg on approaching big data for a non-technical audience so that they can learn the project planning skills to work with technical teams. The goal is to teach students the mindset they should when taking in mixed methods and applying to large datasets prior to selecting software packages and methodology. The slides take us through a previous use case and guidance moving forward from a process and cross-functional team perspective.
Big Data vs. Small Data...what's the difference?Anna Kuhn
What is big data? A 3-pg summary of the key differences between "big data" and "small data."
Includes comparison of data jargon, high level technologies, staffing / people, and the nature of the data itself.
Perfect for data-savvy marketers & agencies, and beginner-to-intermediate data and analytics professionals.
Big Data Information Architecture PowerPoint Presentation SlideSlideTeam
Feel enthralled by all the attention by our Big data information architecture PowerPoint presentation slide offers. While designing the perfect framework for a durable system, it could get tricky to represent all the data in a systematic manner. Manifesting complex ideas in a simplified manner doesn't always comes handy. That's the reason we have well-researched formats and designs for professional and prolonging solutions. Our team of experts makes sure that all the PPT slides are framed to work for the best of the client. Numerous icons and images are used here for visual engagement. We have covered up every viewpoint of data structure possible, including, data market forecast, financial aspects, social media approach and different comparisons used in data analysis for an out of box view. Our sole and intriguing PowerPoint slides are your gateway to progress and serves you in holding your viewer's consideration towards the concept of discernment and improves the quality and accuracy of the business processes. Discourage injudicious comments with our Big Data Information Architecture PowerPoint Presentation Slide. Ensure folks adhere to the decorum.
Slides for class session I taught at USC Annenberg on approaching big data for a non-technical audience so that they can learn the project planning skills to work with technical teams. The goal is to teach students the mindset they should when taking in mixed methods and applying to large datasets prior to selecting software packages and methodology. The slides take us through a previous use case and guidance moving forward from a process and cross-functional team perspective.
Big Data vs. Small Data...what's the difference?Anna Kuhn
What is big data? A 3-pg summary of the key differences between "big data" and "small data."
Includes comparison of data jargon, high level technologies, staffing / people, and the nature of the data itself.
Perfect for data-savvy marketers & agencies, and beginner-to-intermediate data and analytics professionals.
The Pros and Cons of Big Data in an ePatient WorldPYA, P.C.
PYA Principal Dr. Kent Bottles, who is also PYA Analytics’ Chief Medical Officer, presented “The Pros and Cons of Big Data in an ePatient World” at the ePatient Connections 2013 conference.
Five Trends in Analytics - How to Take Advantage Today - StampedeCon 2013StampedeCon
At the StampedeCon 2013 Big Data conference in St. Louis, ohn Lucker, Partner and Principal at Deloitte Consulting, discussed Five Trends in Analytics - How to Take Advantage Today. Lucker will discuss the latest advancements in the world of analytics and offer strategies for tapping into their potential. The topic areas include visualization and design, mobile analytics and strategy analytics.
Big Data Applications | Big Data Application Examples | Big Data Use Cases | ...Simplilearn
In this Big Data presentation, we will be discussing the Big data growth over the last few years followed by the various big data applications. We will look into the various sectors where big data is used such as weather forecast, healthcare, media and entertainment, logistics, travel & tourism and finally in the government & law enforcement sector.
We will be discussing how below industries are using Big Data presentation:
1. Weather forecast
2. Media and entertainment
3. Healthcare
4. Logistics
5. Travel n tourism
6. Government and law enforcement
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training
Big Data Applications & Analytics Motivation: Big Data and the Cloud; Centerp...Geoffrey Fox
Motivating Introduction to MOOC on Big Data from an applications point of view https://bigdatacoursespring2014.appspot.com/course
Course says:
Geoffrey motivates the study of X-informatics by describing data science and clouds. He starts with striking examples of the data deluge with examples from research, business and the consumer. The growing number of jobs in data science is highlighted. He describes industry trend in both clouds and big data.
He introduces the cloud computing model developed at amazing speed by industry. The 4 paradigms of scientific research are described with growing importance of data oriented version. He covers 3 major X-informatics areas: Physics, e-Commerce and Web Search followed by a broad discussion of cloud applications. Parallel computing in general and particular features of MapReduce are described. He comments on a data science education and the benefits of using MOOC's.
People are sometimes intimidated by big data because it seems overwhelming and they’re much more familiar with using statistics on survey data or analyzing opinions from focus group data. But here are nine examples from companies like Netflix, Ceasars Entertainment, Walmart, eBay, and UPS, that could have conducted survey or focus group research have instead used big data to accomplish big things.
Big Data for beginners, the main points you need to know. Simple answers to: What is Big Data? What are the benefits of Big Data? What is the future of Big Data?
Small data vs. Big data : back to the basicsAhmed Banafa
Small data is data in a volume and format that makes it accessible, informative and actionable.
The Small Data Group offers the following explanation:
Small data connects people with timely, meaningful insights (derived from big data and/or “local” sources), organized and packaged – often visually – to be accessible, understandable, and actionable for everyday tasks.
Fundamentals of Big Data in 2 minutes!!Simplify360
In today’s world where information is increasing every second, BIG DATA takes up a major role in transforming any business.
Learn the fundamentals of big data in just 2 minutes!
Content:
Introduction
What is Big Data?
Big Data facts
Three Characteristics of Big Data
Storing Big Data
THE STRUCTURE OF BIG DATA
WHY BIG DATA
HOW IS BIG DATA DIFFERENT?
BIG DATA SOURCES
BIG DATA ANALYTICS
TYPES OF TOOLS USED IN BIG-DATA
Application Of Big Data analytics
HOW BIG DATA IMPACTS ON IT
RISKS OF BIG DATA
BENEFITS OF BIG DATA
Future of big data
BIG Data & Hadoop Applications in Social MediaSkillspeed
Explore the applications of BIG Data & Hadoop in Social Media via Skillspeed.
BIG Data & Hadoop in Social Media is a key differentiator, especially in terms of generating memorable customer experiences.
Herein, we discuss how leading social networks such as Facebook, Twitter, Pinterest, LinkedIN, Instagram & Stumble Upon utilize Hadoop.
To get more details regarding BIG Data & Hadoop, please visit - www.SkillSpeed.com
What is the impact of Big Data on Analytics from a Data Science perspective.
Presented at the Big Data and Analytics Summit 2014, Nasscom by Mamatha Upadhyaya.
The Pros and Cons of Big Data in an ePatient WorldPYA, P.C.
PYA Principal Dr. Kent Bottles, who is also PYA Analytics’ Chief Medical Officer, presented “The Pros and Cons of Big Data in an ePatient World” at the ePatient Connections 2013 conference.
Five Trends in Analytics - How to Take Advantage Today - StampedeCon 2013StampedeCon
At the StampedeCon 2013 Big Data conference in St. Louis, ohn Lucker, Partner and Principal at Deloitte Consulting, discussed Five Trends in Analytics - How to Take Advantage Today. Lucker will discuss the latest advancements in the world of analytics and offer strategies for tapping into their potential. The topic areas include visualization and design, mobile analytics and strategy analytics.
Big Data Applications | Big Data Application Examples | Big Data Use Cases | ...Simplilearn
In this Big Data presentation, we will be discussing the Big data growth over the last few years followed by the various big data applications. We will look into the various sectors where big data is used such as weather forecast, healthcare, media and entertainment, logistics, travel & tourism and finally in the government & law enforcement sector.
We will be discussing how below industries are using Big Data presentation:
1. Weather forecast
2. Media and entertainment
3. Healthcare
4. Logistics
5. Travel n tourism
6. Government and law enforcement
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training
Big Data Applications & Analytics Motivation: Big Data and the Cloud; Centerp...Geoffrey Fox
Motivating Introduction to MOOC on Big Data from an applications point of view https://bigdatacoursespring2014.appspot.com/course
Course says:
Geoffrey motivates the study of X-informatics by describing data science and clouds. He starts with striking examples of the data deluge with examples from research, business and the consumer. The growing number of jobs in data science is highlighted. He describes industry trend in both clouds and big data.
He introduces the cloud computing model developed at amazing speed by industry. The 4 paradigms of scientific research are described with growing importance of data oriented version. He covers 3 major X-informatics areas: Physics, e-Commerce and Web Search followed by a broad discussion of cloud applications. Parallel computing in general and particular features of MapReduce are described. He comments on a data science education and the benefits of using MOOC's.
People are sometimes intimidated by big data because it seems overwhelming and they’re much more familiar with using statistics on survey data or analyzing opinions from focus group data. But here are nine examples from companies like Netflix, Ceasars Entertainment, Walmart, eBay, and UPS, that could have conducted survey or focus group research have instead used big data to accomplish big things.
Big Data for beginners, the main points you need to know. Simple answers to: What is Big Data? What are the benefits of Big Data? What is the future of Big Data?
Small data vs. Big data : back to the basicsAhmed Banafa
Small data is data in a volume and format that makes it accessible, informative and actionable.
The Small Data Group offers the following explanation:
Small data connects people with timely, meaningful insights (derived from big data and/or “local” sources), organized and packaged – often visually – to be accessible, understandable, and actionable for everyday tasks.
Fundamentals of Big Data in 2 minutes!!Simplify360
In today’s world where information is increasing every second, BIG DATA takes up a major role in transforming any business.
Learn the fundamentals of big data in just 2 minutes!
Content:
Introduction
What is Big Data?
Big Data facts
Three Characteristics of Big Data
Storing Big Data
THE STRUCTURE OF BIG DATA
WHY BIG DATA
HOW IS BIG DATA DIFFERENT?
BIG DATA SOURCES
BIG DATA ANALYTICS
TYPES OF TOOLS USED IN BIG-DATA
Application Of Big Data analytics
HOW BIG DATA IMPACTS ON IT
RISKS OF BIG DATA
BENEFITS OF BIG DATA
Future of big data
BIG Data & Hadoop Applications in Social MediaSkillspeed
Explore the applications of BIG Data & Hadoop in Social Media via Skillspeed.
BIG Data & Hadoop in Social Media is a key differentiator, especially in terms of generating memorable customer experiences.
Herein, we discuss how leading social networks such as Facebook, Twitter, Pinterest, LinkedIN, Instagram & Stumble Upon utilize Hadoop.
To get more details regarding BIG Data & Hadoop, please visit - www.SkillSpeed.com
What is the impact of Big Data on Analytics from a Data Science perspective.
Presented at the Big Data and Analytics Summit 2014, Nasscom by Mamatha Upadhyaya.
Big Data - The 5 Vs Everyone Must KnowBernard Marr
This slide deck, by Big Data guru Bernard Marr, outlines the 5 Vs of big data. It describes in simple language what big data is, in terms of Volume, Velocity, Variety, Veracity and Value.
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.
There are some things that are so big that they have implications for everyone, whether we want it or not. Big Data is one of those things, and is completely transforming the way be do business and is impacting most other parts of our lives. Big Data refers to our ability to make use of the ever-increasing volumes of data.
There are some things that are so big that they have implications for everyone, whether we want it or not. Big Data is one of those things, and is completely transforming the way be do business and is impacting most other parts of our lives. Big Data refers to our ability to make use of the ever-increasing volumes of data.
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.
Abstract:
Big Data concern large-volume, complex, growing data sets with multiple, autonomous sources. With the fast development of networking, data storage, and the data collection capacity, Big Data are now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences. This paper presents a HACE theorem that characterizes the features of the Big Data revolution, and proposes a Big Data processing model, from the data mining perspective. This data-driven model involves demand-driven aggregation of information sources, mining and analysis, user interest modeling, and security and privacy considerations. We analyze the challenging issues in the data-driven model and also in the Big Data revolution.
2. Roadmap
1. Introduction
2. The Difference – Big Data Analytics
3. Datafication
4. Small Data Vs Big Data Vs Lots of Data
5. The four ‘V’s of Big Data
6. Turning Big Data into Value
7. How is Big Data actually used?
8. Big Data around the globe
3. Introduction: What is Big Data?
• Big Data is completely transforming the way we do business and is
impacting most part of our lives.
• The extremely large data sets can be analyzed computationally to reveal
patterns, trends, and associations, especially relating to human behavior
and interactions.
• The basic idea behind the phrase 'Big Data' is that everything we do is
increasingly leaving a digital trace (or data), which we (and others) can use
and analyse.
Introduction The Difference – Big
Data Analytics
Datafication Small Data Vs Big Data
Vs Lots of Data
The four ‘V’s of Big Data Turning Big Data into
Value
How is Big Data actually
used?
Big Data around the
globe
4. Introduction: What is Big Data?
• Key enablers for the
appearance and growth of ‘Big-
Data’ are:
Increase in storage
capabilities
Increase in processing power
Availability of data
Introduction The Difference – Big
Data Analytics
Datafication Small Data Vs Big Data
Vs Lots of Data
The four ‘V’s of Big Data Turning Big Data into
Value
How is Big Data actually
used?
Big Data around the
globe
5. Introduction: What is Big Data?
• Big Data therefore refers to our ability to make use of the ever-increasing
volumes of data.
Eric Schmidt,
Executive Chairman, Google
From the dawn of civilization until 2003,
humankind generated five exabytes of data. Now
we produce five exabytes every two days…and the
pace is accelerating.
Introduction The Difference – Big
Data Analytics
Datafication Small Data Vs Big Data
Vs Lots of Data
The four ‘V’s of Big Data Turning Big Data into
Value
How is Big Data actually
used?
Big Data around the
globe
6. Introduction: What is Big Data?
• Lots of data is being collected
and warehoused. Such as:
Web data, e-commerce
purchases at department/
grocery stores
Bank/Credit Card
transactions
Social Network
Introduction The Difference – Big
Data Analytics
Datafication Small Data Vs Big Data
Vs Lots of Data
The four ‘V’s of Big Data Turning Big Data into
Value
How is Big Data actually
used?
Big Data around the
globe
7. The Difference - Big Data Analytics
• Here is the difference
between Traditional
Analytics (BI) and Big
Data Analytics.
Introduction The Difference – Big
Data Analytics
Datafication Small Data Vs Big Data
Vs Lots of Data
The four ‘V’s of Big Data Turning Big Data into
Value
How is Big Data actually
used?
Big Data around the
globe
8. Datafication
• Sensor Data: We are increasingly surrounded by sensors that collect and share data. Take
your smart phone, it contains a global positioning sensor to track exactly where you are
every second of the day.
• Activity Data: Simple activities like listening to music or reading a book are now generating
data. Digital music players and eBooks collect data on our activities. Your smart phone
collects data on how you use it and your web browser collects information on what you are
searching for.
• Conversation Data: Just think of all the conversations we have on social media sites like
Facebook or Twitter. Even many of our phone conversations are now digitally recorded.
Introduction The Difference – Big
Data Analytics
Datafication Small Data Vs Big Data
Vs Lots of Data
The four ‘V’s of Big Data Turning Big Data into
Value
How is Big Data actually
used?
Big Data around the
globe
9. Datafication
• Photo and Video Image data: We upload and share 100s of thousands of them on social
media sites every second.
• The IOT data: We now have smart TVs that are able to collect and process data, we have
smart watches, smart fridges, and smart alarms. The Internet of Things, or Internet of
Everything connects these devices
Introduction The Difference – Big
Data Analytics
Datafication Small Data Vs Big Data
Vs Lots of Data
The four ‘V’s of Big Data Turning Big Data into
Value
How is Big Data actually
used?
Big Data around the
globe
10. Small Data Vs Big Data Vs Lots of Data
• Small data is data in which we have a sense of where it coming from and how much there
will be. For example companies large and small know their customer base and can design
database systems to accommodate this data. Big data is data from sources in which we have
no way to estimate how large it will be, how much it will grow and how much it will change.
• There is a vast difference between “having a lot of data” and “doing big data.” When you
have a large data set that is fast moving, ever changing, and includes unstructured data, and
when you are using distributed storage and in-memory analytics, then we are talking big
data!
Example: When you want to do something other than store and fetch images; when you begin
to look inside the images and draw correlations to other data types like electronic health
records (EHRs) or a Twitter feed or weather data, that’s when you have a Big Data challenge.
Introduction The Difference – Big
Data Analytics
Datafication Small Data Vs Big Data
Vs Lots of Data
The four ‘V’s of Big Data Turning Big Data into
Value
How is Big Data actually
used?
Big Data around the
globe
11. The four ‘V’s of Big Data
With the datafication comes big data, which is often described using the four Vs:
• Volume
• Velocity
• Variety
• Veracity
Introduction The Difference – Big
Data Analytics
Datafication Small Data Vs Big Data
Vs Lots of Data
The four ‘V’s of Big Data Turning Big Data into
Value
How is Big Data actually
used?
Big Data around the
globe
12. The four ‘V’s of Big Data
• Volume refers to the vast amounts of data generated every second. We are not talking
Terabytes but Zettabytes or Brontobytes. If we take all the data generated in the world
between the beginning of time and 2008, the same amount of data will soon be generated
every minute.
• Velocity refers to the speed at which new data is generated and the speed at which data
moves around. Just think of social media messages going viral in seconds. Technology
allows us now to analyse the data while it is being generated (sometimes referred to as in-
memory analytics), without ever putting it into databases.
Introduction The Difference – Big
Data Analytics
Datafication Small Data Vs Big Data
Vs Lots of Data
The four ‘V’s of Big Data Turning Big Data into
Value
How is Big Data actually
used?
Big Data around the
globe
13. The four ‘V’s of Big Data
• Variety refers to the different types of data we can now use. In the past we only focused on
structured data that neatly fitted into tables or relational databases, such as financial data. In
fact, 80% of the world’s data is unstructured (text, images, video, voice, etc.) With big data
technology we can now analyse and bring together data of different types such as messages,
social media conversations, photos, sensor data, video or voice recordings.
• Veracity refers to the messiness or trustworthiness of the data. With many forms of big data
quality and accuracy are less controllable (just think of Twitter posts with hash tags,
abbreviations, typos and colloquial speech as well as the reliability and accuracy of content)
but technology now allows us to work with this type of data.
Introduction The Difference – Big
Data Analytics
Datafication Small Data Vs Big Data
Vs Lots of Data
The four ‘V’s of Big Data Turning Big Data into
Value
How is Big Data actually
used?
Big Data around the
globe
14. Turning Big Data into Value
The datafication of our world gives us unprecedented amounts of data in terms of Volume,
Velocity, Variety and Veracity. The latest technology such as cloud computing and distributed
systems together with the latest software and analysis approaches allow us to leverage all types
of data to gain insights and add value.
Introduction The Difference – Big
Data Analytics
Datafication Small Data Vs Big Data
Vs Lots of Data
The four ‘V’s of Big Data Turning Big Data into
Value
How is Big Data actually
used?
Big Data around the
globe
15. Turning Big Data into Value
Value
Volume
Velocity
Variety
Veracity
The ‘Datafication’ of
our World:
• Activities
• Conversations
• Words
• Voice
• Social Media
• Browser logs
• Photos
• Videos
• Sensors
Analysing
Big Data:
Text analytics
Sentiment
analysis
Face
recognition
Voice analytics
Movement
analytics
Introduction The Difference – Big
Data Analytics
Datafication Small Data Vs Big Data
Vs Lots of Data
The four ‘V’s of Big Data Turning Big Data into
Value
How is Big Data actually
used?
Big Data around the
globe
16. How is Big Data actually used?
Example 1
Understand and Optimize Business Processes:
Big data is increasingly used to optimize business processes. Retailers are able to optimize their
stock based on predictive models generated from social media data, web search trends and
weather forecasts. Another example is supply chain or delivery route optimization using data
from geographic positioning and radio frequency identification sensors.
Introduction The Difference – Big
Data Analytics
Datafication Small Data Vs Big Data
Vs Lots of Data
The four ‘V’s of Big Data Turning Big Data into
Value
How is Big Data actually
used?
Big Data around the
globe
17. How is Big Data actually used?
Example 2
Better understand and target customers:
To better understand and target customers, companies expand their traditional data sets with
social media data, browser, text analytics or sensor data to get a more complete picture of their
customers. The big objective, in many cases, is to create predictive models. Using big data,
Telecom companies can now better predict customer churn; retailers can predict what products
will sell, and car insurance companies understand how well their customers actually drive.
Introduction The Difference – Big
Data Analytics
Datafication Small Data Vs Big Data
Vs Lots of Data
The four ‘V’s of Big Data Turning Big Data into
Value
How is Big Data actually
used?
Big Data around the
globe
18. How is Big Data actually used?
Example 3
Improving Health:
The computing power of big data analytics enables us to find new cures and better understand
and predict disease patterns. We can use all the data from smart watches and wearable devices
to better understand links between lifestyles and diseases. Big data analytics also allow us to
monitor and predict epidemics and disease outbreaks, simply by listening to what people are
saying, i.e. “Feeling rubbish today - in bed with a cold” or searching for on the Internet, i.e.
“cures for flu”.
Introduction The Difference – Big
Data Analytics
Datafication Small Data Vs Big Data
Vs Lots of Data
The four ‘V’s of Big Data Turning Big Data into
Value
How is Big Data actually
used?
Big Data around the
globe
19. How is Big Data actually used?
Example 4
Improving and Optimizing Cities and Countries:
Big data is used to improve many aspects of our cities and countries. For example, it allows
cities to optimize traffic flows based on real time traffic information as well as social media
and weather data. A number of cities are currently using big data analytics with the aim of
turning themselves into Smart Cities, where the transport infrastructure and utility processes
are all joined up. Where a bus would wait for a delayed train and where traffic signals predict
traffic volumes and operate to minimize jams.
Introduction The Difference – Big
Data Analytics
Datafication Small Data Vs Big Data
Vs Lots of Data
The four ‘V’s of Big Data Turning Big Data into
Value
How is Big Data actually
used?
Big Data around the
globe
20. Big Data around the globe
Creates over 30 billion pieces of content per day. Stores 30 petabytes of data.
Produces over 90 million tweets per day.
Introduction The Difference – Big
Data Analytics
Datafication Small Data Vs Big Data
Vs Lots of Data
The four ‘V’s of Big Data Turning Big Data into
Value
How is Big Data actually
used?
Big Data around the
globe
21. Big Data around the globe
• Era of Big data analytics has just begun and the businesses are witnessing a transformation
into big data economy.
• Companies gaining edge by collecting, analysing and understanding information.
Introduction The Difference – Big
Data Analytics
Datafication Small Data Vs Big Data
Vs Lots of Data
The four ‘V’s of Big Data Turning Big Data into
Value
How is Big Data actually
used?
Big Data around the
globe