a presentation about emerging technology

1. BIG DATA ANALYTICS FOR ENHANCING
THE REAL ESTATE MARKET OF OMAN
Submitted By:
HAGER BELAL GABAALLAH
Presentation

2. ABSTRACT
Artificial intelligence is progressing rapidly with new highly developed
innovations in the present world. It is very useful for some applications like
deep learning, machine learning, neural networks, robotics, big data, bitcoin.
In this scenario, computer systems are designed to best perform small tasks
like facial identification, automated transport system self-driving car,
involvement in dangerous jobs, computerized methods, reduced human
efforts, time-saving, and other small duties of presentation. The first goal of
artificial intelligence is to highly develop and more complex systems.
2

3. PROJECT
BACKGROUND
Recently, a great deal of interest has been noted in data, and it is considered
as a new oil of the 21st century and the main driver of Industry 4.0.
Looking at the development in data, it found that data went through three
stages with business intelligence (BI). In the first stage, most data was
structured from sources that included legacy systems and stored in a
relational database and data integration involved the Extraction,
Transformation, and Loading (ETL) mechanism which data warehouse was
the foundation of this operation. Besides, for analyzing data Online
Analytical Processing (OLAP) was used for data analytics included
reporting tools and statistical methods.
In the second stage, the web became another source of data, as well as for
more accurate analysis of customer needs, and here unstructured data
appeared that need advanced methods of analysis like web analytics and
web intelligence. In the third stage, the mobile and sensor-based content
played a big role in the increasing number of data, which in turn led to the
definition of new insights through knowing the accurate details of the data
(Santos et al., 2017). Information and communication technology (ICT)
contributed greatly to the evolution of data.
3

4. PROBLEM
STATEMENT
Usually, data was produced from a single source using traditional
databases where most of the data used in the public sector were
structured data such as transaction data. But there are other
sources of data such as the Internet, and Social media that are
usually not used because it is unstructured or semi-structured
data.
4

5. QUESTION
OF THE STUDY
5
o What are the advantages that the real estate market achieves when using big data analytics?
o What are the challenges that the real estate market face when using big data analytics?
o Is there a significant effect of big data analytics on the roles of the real estate profession in
the future?
o Is there a significant effect of big data analytics on the quality characteristics of official
statistics for the real estate market?
o How to develop an efficient big data analytics tool?

6. OBJECTIVE
OF THE STUDY
6
o To investigate on the effect of big data analytics on improving
the real estate market.

7. IMPORTANCE
OF THE STUDY
7
o The project sought to achieve the integration between real
estate data of the Housing Ministry (Oman) and real estate
data of the OpenSooq website to facilitate decision-making
processes and development strategies related to the real estate
market of Oman by the proposed web-based system called Tam
leek Home system

8. AIM
8
o Developing an integrated real estate market system can merge
multi-source heterogeneous real estate data into a single view
system to get better big data patterns and gain key business
insights

9. OBJECTIVES
9
o To produce reliable official statistics to keep users well informed on the real estate
market and assist in good policy and decision-making.
o To help the investors to get the best rental property and reducing real estate market
volatility.
o To help the realtors to understand the customer’s needs of the property to offer the
property in a better way based on the data.
o To help the buyers/sellers to identify the various real estate market trends.
o To diagnose aspects of change about the skills and tasks required by the data science
professionals dealing with big data.

10. INTRODUCTION TO
ARTEFACT
10
o A project artifact was a scraping system that aimed to collect real
estate data in Oman from different sources to provide a visual
representation in the form of an intelligence dashboard that can be
used to meet the client’s need, and for academic, scientific, and
research purposes later.

11. LITERATURE
REVIEW
o What is the effect of big data analytics on enhancing the real
estate market? some studies have focused on the problem of
data sources in the official statistics which storage of large
volumes of data and different dataset were the big issues
(Struijs, Braaksma, and Daas, 2014);(Cox, Kartsonaki and
Keogh, 2018);(Little, 2015). According to Domo's (2020)
report by the end of 2020, approximately 1.7 megabytes of
data were created every second for every person in the world
which equals 2.5 million terabytes every day, and It is
expected that the number will increase in 2025 to reach 175
zettabytes. Besides, more than 90% of the data has been
created in the last 2 years in the world
11

12. BIG DATA
12
o Big Data is composed of two keywords which are ‘Big’ and
‘Data’. Big refers to something very large or so huge, and Data
refers to information or set of values that may be quantitative
(numeric) or qualitative (non-numeric). In terms of technology,
Big Data is a large volume of data that could be structured,
semi-structured, or non-structured data that grows rapidly,

13. CONCLUSION
13
Big data became the center of research in the last two decades due to the significant
rise in the generation of data from various sources such as mobile phones,
computers, and GPS sensors. Various tools and techniques such as web scraping,
data cleaning, and filtering are applied to big databases to extract useful information
which is then used to visualize and draw results from unstructured data.
This paper reviewed the existing concept of big data and the tools available for big
data analytics, along with discussing the challenges that exist in managing big data
and their possible solutions. Furthermore, the applications of big data in two novel
and integrated fields of smart real estate and disaster management were explored.

14. REFERENCES
14
o Akter, S., Wamba, S.F., Gunasekaran, A., Dubey R., Childe, S.J. (2016). How to improve firm performance using big
data analytics capability and business strategy alignment? International Journal of Production Economics, 182, 113-131
o Álvarez Santos, J., Miguel-Dávila, J.A., Nieto Antolín, M. (2016). The innovation strategies for managing a specific
paradox: exploration/exploitation. Total Quality Management & Business Excellence, 1-19.
o Andriopoulos, C., Lewis, M.W. (2009). Exploitation-Exploration Tensions and Organizational Ambidexterity: Managing
Paradoxes of Innovation. Organization Science, 20(4), 696-717
o Athuahene-Gima, K. (2005). Resolving the capahility rigidity paradox in new product innovation. Journal of Marketing,
69(4), 61-83.
o Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120.
o Barney, J. B. (2001). Resource-based theories of competitive advantage: A ten-year retrospective on the resource-based
view. Journal of Management, 27(6), 643650.

15. THANK YOU!
Q A