Challenges of Big data

1. Big Data Challenges and applications
Presented by
Javaria Naeem

2. Big data is useful for modern community and it’s a huge
challenging task for maintaining and getting relevant
information from the big data for data scientist. On the one
hand, it solves problems, we can get worthful information
from the data but on the other hand it’s difficult to handle
complex and huge data. This paper describes what are the
challenges which data scientist has to face while using big
data, how they manage huge data and how to overcome
these challenges. Moreover, in this paper features of the
big data will be discussed. The main goal of this paper is to
present the information to the users that how data can be
handled. Handling huge data is not an easy task. So, this
paper will prove to be a big help for the researchers.
Abstract

3. • Lack of knowledge Professionals. To run these modern
technologies and large Data tools, companies need
skilled data professionals.
• Lack of proper understanding of Massive Data. ...
• Data Growth Issues. ...
• Integrating Data from a Spread of Sources. ...
• Securing Data.
Problems which occur during research

4. Introduction
• Big data is used for analyzing mode, patterns, actions or behaviors anything which relates to people
or customer.
• Big data analytic gives accurate analysis that helps us in making precise decision and better
performance.
• Big data are gathered in two forms which is structured and unstructured data
• We get unstructured data from social media (Facebook, Instagram, etc). While, structured data
sources can come from internal database of organization.
• it is crucial to use tools and the frameworks effectively for the organizations and analysis of datasets
• Big Data can be explained using 10V’s model.

5. Velocity
Variety
Veracity
Volume
Variablity
Validity
Vulnerability
Volatility
Visualization
Value
10 V’s of Big
Data

6. There three main steps of Big Data analysis
• Initialization
• Implementation
• Evaluation
Research Model

7. Storage
C H A L L E N G E S
Heterogeneity
Quality of
Data
Timeliness
Privacy
Visualization
Scalability
Fault
Tolerance

8. Big Data Applications
• In this paper, I mentioned few applications
• Smart Transportation
• One of the crucial applications which we need is intelligent Transportation. Now a days, traffic
condition in big cities is severe and streets are crowded. To monitor this traffic condition various
sensing technologies are present and these technologies are divided into two parts: road sensors
and motor vehicle sensors. These sensors have network communication through Wifi, Bluetooth
and GSM(Global system for mobile application.
• Financial Market Trading
• Market is also a big source of data. Massive financial data is generating in every other second for
stock and trades. This data is not only massive in amount but also dynamic. It changes after every
second. Data generated by the financial market is useful for the organizations.
• Crowd Control
• Crowd control is crucial for the team who has to response in emergency cases and for the police
too. For e.g., Sport games, Festivals, National days. People come out from the houses to join events
in huge amount in order to control this there should be applications through which police and other
teams can response in time if their emergency case comes out

9. • Social Network Analysis
• Social Network Analysis is an application of a graphical theory for understanding and
organizing social networks. Everyday social media is generating massive data which is hard to
organize it with methods like mining and algorithms. It is very helpful to analyze association
between entities, suggestion of products, violence detection, connection prediction and so on
• Health Care
• Now a days, its crucial to keep data in digital form in hospitals. This massive data can be
patients’ old illness record, x-rays, blood test results, surgery records, policies of heath record,
medical equipment record and hospital staff record etc. This data may be in the form of
unstructured data or structured data by this data doctors can analyze the person’s health on
the basis of which he can move to the advance treatments. So, treatment can be done in less
time which can improve the health quality
• Education
• Now, universities and schools started to store data in digitized form which is beneficial for the
student and the institutions. By storing data of students, it can easily find out how many
students are in studying in a year even we can find out the problems of students which can be
solved with sentiment and behavior analysis. Moreover, by analyzing the record of student’s
suitable subject can be proposed to them

10. Results
Big data analysis is time taking process that’s the reason applications cannot get results in a second from big
data. However, real-time applications need to produce result in real-time. In this paper we discussed various
domains that could get advantage from big data like rescue or emergency applications, decision making
applications, crowd control applications etc. While building application we would face various challenges like
storage, security, data transferring etc. for overcoming these challenges we need an effective solution. We can
get perfect application if we get successful in overcoming challenges.

11. Thank You