Big Data Lecture given at the University of Balamand by Fady Sayah Digi Web Founder.
Why Big Data Now?
Types of Databases
The 4 Vs of Big Data
Big Data Challenges
Big Data & Marketing
Big Data Impact on Social Media
Big Data & Hospitality
Big Data Scalable systems
BIg Data and Higher Education
Big Data Success Stories
You can view the presentation on this link.
NLP Project PPT: Flipkart Product Reviews through NLP Data Science.pptx
Big Data why Now and where to?
1. B a l a m a n d U n i v e r s i t y M a r c h 2 6 t h 2 0 1 9
P r e p a r e d b y F a d y S a y a h
F o u n d e r D i g i W e b
2. Twenty-Three years of experience in Internet, Mobile Applications and New Media Technologies.
International experience in Business Management, Business Development, Sales and Marketing for start-ups and established companies.
BA in Finance & Banking with advanced expertise in financial computing and e-banking
Lecturer in Several Universities & Professional events about Big Data, E-Marketing & Smart Cities
Member of the IOETI – International Organization of E-Travel Industry
Member of the E-marketing Association
Tri-lingual
3. Definition of Big Data between structured
and unstructured
A drive through the different
characteristics of Big Data
4. Every single bit of data has its own
challenge
Traditional V/S Modern Processing
Hotel Revenues in the Era of Big Data
6. Extremely large data sets that may be analysed computationally
to reveal patterns, trends, and associations, especially relating to
human behaviour and interactions.
8. Structured data has a high level of organization making it
predictable, easy to organize and very easily searchable using
basic algorithms.
Structured data is comprised of clearly defined data types
whose pattern makes them easily searchable
Structured data analytics is a mature process and technology
Unstructured data, on the other hand, is not organized in any
discernible manner and has no associated data model
Unstructured data has internal structure but is not structured
via pre-defined data models or schema.
Unstructured data analytics is an emerging industry with a lot
of new investment into R&D, but is not a mature technology.
9. Data generation underwent a sort of
revolution, driven primarily by the
ubiquity of the internet and the
cheaper computing power.
2.5 Exabyte of data is generated daily
Structured data usually resides in relational
databases (RDBMS).
Unstructured data has internal structure
but is not structured via pre-defined data
models or schema.
Data may be human- or machine-generated
as long as the data is created within an
RDBMS structure.
Big Data storage is done through primarily
what is known as NOSQL databases. “Not
Only Structured Query Language”
10. Big Data is typically characterized with four V's
11. The amount of
generated Data
The speed of Data
Generation
Variety of generated
Data
Trustworthy or Not
12. The challenges of big data management result from the expansion of all four
properties, rather than just the volume alone
40 Zettabytes by 2020
43 Trillion GB of by 2020
300 X more than 2005
6 Billion People have Cell Phones
Modern Cars have 100 Sensors
18.9 Billion Network Connections
NYSE 1 TB of Information during each
trading session
150 Exabyte of Data from
healthcare in 2011
30 Billion of Pieces of Content are
shared on FB per month from
420 Million Wearable Decvices
1 In 3 Business Leaders Don't Trust
the info they have
27% of respondents were unsure of
how much of their data was
inaccurate
Poor Data quality costs US Economy
$3.1 Tri/ Year
Scale Of Data Analysis of Data
Different Forms of Data Uncertainty of Data
13. Before going to battle, each general needs to study his opponents:
how big their army is, what their weapons are, how many battles
they’ve had and what primary tactics they use. This knowledge can
enable the general to craft the right strategy and be ready for
battle.
14. Lack of skills available
in the market for big
data technologies
The intricate aspects of
data transmission,
access and loading are
only part of the
challenge
Sequence of data
transformation,
extraction & migrations
are risks for data to
become
unsynchronized.
Extracting Information
from Big Data with
elimination of custom
coding for end users
The Uncertainty of Data
Management
The core elements of the big data platform is to handle the data in new ways as
compared to the traditional relational database.
integration of data, skill
availability, solution
cost, the volume of
data, the rate of
transformation of data,
veracity and validity of
data
15. Previous computer algorithms
are not able to effectively storing
big data
The traditional serial algorithm is
inefficient for the big data.
Affect the entire big
data storage and processing.
It is a challenge to implement
effective privacy protection in
complex circumstance.
16. What’s the one thing that all marketers must know?
The fact that data is king on today’s marketing
landscape.
17. Customer Value Analytics (CVA) based on Big Data is making it possible for leading marketers to deliver
consistent omnichannel customer experiences across all channels.
18. The marketing platform stack in many
companies is growing fast based on
evolving customer, sales, service and
channel needs not met with existing
systems today.
As a result, many marketing stacks
aren’t completely integrated at the
data and process levels.
Big data analytics provides the
foundation for creating scalable
Systems of Insight to help alleviate
this problem.
19. Social Media is more than a Daily Routine
The roots of social media stretch far deeper than you might imagine.
Although it seems like a new trend, sites like Facebook are the natural
outcome of many centuries of social media development.
The Most Exclusive Invite Only
Social Network Where You Will
Meet Amazing People Based on
Your Interests.
MySpace and LinkedIn gained
prominence, and sites like
Photobucket and Flickr facilitated
online photo sharing
The first blogging sites became
popular, creating a social media
sensation that’s still popular today
Facebook and Twitter both
became available to users
throughout the world. These sites
remain some of the most popular
social networks on the Internet
20. Big Data is useful in tracking
the performance of social
media campaigns and
finding out the gradual
changes in ROI.
Big Data aids in making
informed decisions to
better meet the future
needs and expectations of
consumers.
Big Data enables
personalization allowing
brands to approach their
customers in a more
personalized way based on
their choices and likes.
Social media marketers can
effectively use big data to
judge future buying
patterns and trends.
21. Big data can also help those
in the hotel industry to more
effectively target their
marketing content.
Big data can be revealing,
providing information about
services that customers use,
and also they request or ask
about.
It allows Hotels to carry out
predictive analysis, allowing
management to more
accurately anticipate levels of
demand for hotel rooms.
Big Data allow hotels to
understand what customers
like and where improvement
is needed.
Big Data can also be used to get a clearer idea of competitors and to see what other companies operating in
the hospitality sector are offering their customers
22. Data can also show the
characteristics that make some
students thrive in the face of
challenges while others fail.
Big Data could impact the success
of the university over a long-term
basis
The data collected could help
universities make changes to
boost retention.
Mining through data in strategic
ways allows colleges to make their
marketing increasingly relevant.
Big Data help identify and
understand the most popular or
necessary services
Big Data's advantage is how it can process substantial quantities of data at once and uncover patterns
Data is helpful for future lesson
planning and to improve
managerial efforts
23. Monitoring of
more than 5000
parameters of RR
engines through
Cloud
Computing
Enhancing
public
transportation
and commuter
routing
Provide
excellent
service and
ensure stable
growth of
income
1 more dollar
daily, means $80
Million increase in
the corporation’s
bottom line
annually
Big Data is everywhere around us and we constantly hear about it promising to disrupt multiple industries. Big Data
analytics can help deliver meaningful insights, helping any business succeed.
24.
25. Big data is an umbrella term with
many job titles and roles under it.
here are three types of Analytics
domain including:
Predictive Analytics
Prescriptive Analytics
Descriptive Analytics
Organisations today require big
data and analytics professionals
in a large number and this
demand is only rising.
A deficit of big data talent is
globally leaving big data analytics
as a ‘Hot’ job
Big Data field proves out to be an
attractive one for the professionals
looking for a sharp growth and
learning curve in their career.
26. Companies of all sizes are beginning to reap
the benefits of data analytics technology. So
why wait while you can start now.