1. Big DATA
Prepared By
Mohammed Amr

2. What is Big Data.
Evolution of Big Data.
Turning Big Data into Value.
How is Big Data Actually Used(Use Cases).
Q&A.

3. The basic Idea behind the term “Big Data” is that every activity we do is
increasingly leaving a digital trace (or Data), such as social media likes ,
feeds , comments and conversations, blogs, sensors, radios, shopping sites
and purchase preferences, searching on the web, places we go, photos,
videos , smart devices and the internet of everything.
Utilizing this digital activity data results in storing huge volumes of data.
These colossal amounts of data can be utilized for analysis and henceforth
insight discovery by businesses to enhance and expand their business
approaches relying on a factual information obtained through customers’
daily digital activities.
Big Data therefore refers to the ability to make use of this ever increasing
volumes of data to the benefit of businesses .

4.  In 1999 , the first use of the term “Big Data”.
 In 2005 , Hadoop – the most recognized Big Data Framework - is developed.
 In 2014 , 88 % of executives responding to an international survey by GE
say that Big Data analysis is a top priority.
 Nowadays with the digitalized virtual world, everything is datafied, meaning
put in the form of data.
 With that datafication of activities comes Big Data, which is often described
using the four Vs.
 Volume: refers to vast amounts of data generated every second.
 Velocity: refers to the speed of data generation and movement.
 Variety: refers to the different types of data we can use.
 Veracity: refers to the messiness or trustworthiness of data.

5.  The datafication of our world gives us unprecedented amounts of data in
terms of Volume , Velocity , Variety and Veracity.
 The latest technology , software and analysis mechanisms allow us to
leverage all types of data to gain insights and add value.

6.  Better understand and target customers.
◦ To better understand and target customers, companies expand their
traditional datasets with social media data , browser text analytics or
sensor data to get a more complete picture of their customers.
◦ Using Big Data, telecom companies can now better predict customer
churn, retailers can predict what products will sell, and car insurance
companies understand well how their customer will drive.
◦ Using predictive analytics as part of Big Data adoption, financial
institutions specially banks can anticipate an ROI on a new product
offering , a service or a specific promotion. Additionally , banks can
further enhance customer experience through analyzing his voice and
viewpoints about the bank’s products and services.

7.  Understand and Optimize Business Processes.
◦ Big Data is also used to optimize business processes through the
customers feeds on the process of opening a credit application and the
timeliness of the credit processing until imbursement.
◦ Banks uses Big data to estimate the ROI of a marketing campaign that
will help in the feasibility study and business case of a new product
offering , channel /service launch , in order to increase the cross sell ratio
based on customer feeds and views.
 Big Data adoption can offer better opportunities of market research and a
complete cycle of customer relationship management.
 It is time to report Big Data initiative is an on-balance sheet asset within
the bank financial statement.

8. Q&A

9. Thank You