This document discusses big data and the role of data scientists. It begins with an introduction to big data, noting that it refers to large and complex datasets that are difficult to process and analyze using traditional methods. It then outlines the key characteristics of big data including volume, velocity, variety, veracity, validity and volatility. The document also discusses challenges in big data such as fault tolerance, scalability and heterogeneity. It provides an overview of big data trends like NoSQL databases, cloud analytics and deep learning. Finally, it describes the role of data scientists in analyzing and interpreting big data to assist with decision making.

1. Big Data
&
Big DataTechnologies
Presenters
Swikar Bhandari
Yaju Shrestha
Yubraj Ghimire 7/12/20171

2. Overview
 Introduction to Big Data
 Characteristics of Big Data
 Challenges in Big Data
 Big DataTrends
 Data Scientist & their roles
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3. Introduction to Big Data
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 Information that can’t be processed or analyzed using
traditional processes or tools.
 Data sets that are so large and complex
 Data which are difficult to capture, store, process,
search and analysis
 ‘Big-data’ is similar to‘Small-data’, but bigger.

4. Characteristics of Big Data
Volume
• Data size
• Data is generated by machines, networks and human
interaction on systems like social media
• 2.5 Exabytes of data produced everyday which is equivalent
to 90 years of HD video
Velocity
• The pace of flow of data from sources like business,
machines, network and human interaction with social medias
or mobiles
• The data flow is massive and continuous
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5. Characteristics of Big Data
Variety
• Data heterogeneity: Structured and Unstructured data
• Many sources and types of data both structured and
unstructured.
• Data comes in the form of emails, photos, videos,
monitoring devices, PDFs, audio, etc
Veracity
• Uncertainty of accuracy and authenticity of data
• Biases, noise and abnormality in data.
• Data that is being stored, and mined meaningful to the
problem being analyzed or not.
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6. Characteristics of Big Data
Validity
• The issue of validity meaning is the data correct and accurate
for the intended use.
• Valid data is key to making the right decisions
Volatility
• How long is data valid and how long should it be stored.
• Data need to determine at what point is data no longer
relevant to the current analysis.
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7. Challenges in Big Data
 Fault tolerance: ability to handle failures
 Scalability : ability to handle data with time
 Heterogeneity: ability to handle various kinds of data
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8. Big Data in Information System
 Unstructured data handling capability
 Real time data processing
 Predictive analytics and in-memory analytics
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9. Big Data Trends
 NoSQL database: for handling unstructured data
 Cloud based analytics: migrating data to cloud platform
 Deep learning: algorithms are used for mining data
 In memory analytics: speed up analytical processing.
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10. Data Scientist
 Person that analyses and interprets data to assist in
decision making.
 The people who understand how to fish out answers to
important business questions from today's tsunami of
unstructured information
 A hybrid of data hacker, analyst, communicator, and
trusted adviser
.
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11. Roles and Skills Of Data Scientist
 Use technologies that make taming big data possible,
including Hadoop, and related open-source tools, cloud
computing, and data visualization.
 Make discoveries while swimming in pool of data
 Bring structure to large quantities of formless data and make
analysis possible
 Write code
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12. Roles and Skills Of Data Scientist
 Communicate what they’ve learned and suggest its
implications for new business directions
 Fashion their own tools and even conduct academic-style
research
 Be creative in displaying information visually and making the
patterns they find clear and compelling
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13. THANK YOU
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