BIG Data & Hadoop Applications in Real Estate

Slide ‹#›© 2015 BlueCamphor Technologies (P) Ltd. www.skillspeed.com
Applications of BIG Data in
Real Estate

Introduction to Big Data
Big data is the term for a collection of data sets so
large and complex that it becomes difficult to
process using on-hand database management
tools or traditional data processing applications
Systems / Enterprises generate huge amount of
data from Terabytes to Petabytes
Understanding Big Data can give you innovative
solutions to various queries.

Applications of BIG Data in Real Estate
• Accurate Management of Large Scale Projects
• Smart Search via Lifestyle Scores & Trends
• Detecting Ideal Zones for Development
• Intelligent Homes

BIG Data Applications in Real Estate
Accurate Management of Large Scale Projects
Large scale projects involve high budgets, complex construction cycles, exhaustive inventory
management and mass labor inputs. How does one manage all this effectively?
BIG Data enables the accurate reporting of every aspect of the project ranging from labor
performance & construction quality to asset maintenance & budget spirals. This ensures that the
project is in tandem with the required deadlines and specifications. However, the most important
application of BIG Data would be that it can predict future shortcomings & delays as well as
provides solutions as to how they can be evaded.
Get Started with BIG Data & Hadoop
Smart Search via Lifestyle Scores & Trends
Today, property websites assign lifestyle scores and generate price-demand heat-maps for
specific areas. They can also accurately predict the value of properties in that area within the
next few months or years.
BIG Data makes this possible by permitting the tracking of property value trends, real-time rental
& purchase demand as well as the growth of lifestyle establishments in the locality.

BIG Data Applications in Real Estate
Detecting Ideal Zones for Development
Based on property trends & area development, BIG Data can instantly infer the best zones in a
particular city or state for infrastructural or real estate development. This is also very
advantageous to a buyer as he can make a sound investment.
Governments can also use this data to allocate resources in accordance with developmental
forecasts.
Intelligent Homes
Sample this, your sleep patterns are analyzed and just when you wake up, the coffee maker starts the brewing
process and your bath-tubs starts filling up. Or, when there is a case of break-in or any other hazard, the local
authorities automatically get notifies. All this and more, without even touching a single switch, is being made
possible via devices powered by BIG Data.
These devices detect your behavior pattern and automatically alter the entire functioning of your home to suit your
needs.

Examples of Big Data Applications in Real Estate
Liberty Building Forensics Group
 They’ve utilized BIG Data for the construction optimization of 500+ projects worldwide, including a Walt Disney
Project. Delays & operational hassles often occur on large-scale construction projects, these can result in budget
spirals. LBFG tracks the performance & competency of labor, equipment, materials and deadlines to ensure that
the project wraps up without any delays or hassles.
Housing.com
 They’re the first real estate portal in India to provide price-demand heat-maps, lifestyle ratings for areas,
demand supply maps and predictions on property prices in the near future. All this, powered by BIG Data.

© 2015 BlueCamphor Technologies (P) Ltd.
How Are Insights Derived from BIG
Data?
Say Hello to Hadoop Development :)

Introduction to Hadoop
Apache Hadoop is a framework that allows the distributed processing of large data sets across clusters of
commodity computers using a simple programming model.
It is an Open-Source Data Management technology with extensive storage and distributed processing.
Hadoop
Characteristics
Flexible
Reliable
Economical
Scalable Get Started with BIG Data & Hadoop

Why Should You Learn Hadoop?
• Hadoop is a modern BIG Data processing framework which utilizes distributed computing clusters.
• It can process, manage and store unstructured data with absolute ease.
• Due to its scalability & effectiveness, companies are heavily adopting Hadoop.
• It has become the standard for storing, processing and analyzing big data.
• BIG Data & Hadoop professionals are in extremely high demand.
• This is the first step to becoming a data scientist or data architect.

Reports – 2015
Here are some of the other Reports that convey the same message:
• “It is expected that Hadoop and Big Data Analytics will grow to around $13.9 billion from 2012 to 2017.”
(Markets and Markets Research Report)
• “The Data market currently with the fastest growth are Hadoop and NoSQL software and services.”
(Technology Research Organization, Wikibon)
• “The Big Data market will likely hit $23.8 billion with a 31.7% rise per year.” (IDC Report)
• “Almost 90% organizations have embarked on Hadoop related projects and thus Hadoop skills are in huge
demand.” (According to the Big Data Executive Survey 2013)
• “Companies hiring Hadoop professionals Analytics professionals obtain a 250 percent hike in their
salaries.” (According to Analytics Industry Report)
Gartner had predicted, “Hadoop will be in most advanced analytics products by 2015.” By far and large, this
prediction has turned out to be true. Hadoop is “The Technology” to harness Big Data

Predictions for 2015
According to the Forrester Report:
• A new data economy will arise, Hadooponomics. Due to its vast data prowess, enterprise adoption of
Hadoop will become compulsory. All those companies, which were unsure of adopting Hadoop till 2014,
are bound to adopt it in 2015
• The surge in demand for Hadoop job professionals will be fulfilled by Java professionals & other software
engineers who will upgrade their skills
• The creation of SQL-on-Hadoop options will further enhance usability & adoption
• Due to the introduction of Yarn (Version 2.0), the usage of Hadoop will go beyond analytics. It will
transform into an application platform giving birth to new frameworks in the Hadoop ecosystem
• New Hadoop sources will emerge from organizations like Oracle, HP, Tibco and SAP. Vendors such as Red
Hat, VMware and Microsoft will include Hadoop in their operating Systems

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Course Topics
Module 1
Introduction to Big
Data and Hadoop
Module 2
HDFS Internals, Hadoop
Configurations and
Data Loading
Module 3
Introduction to Map
Reduce
Module 4
Advanced Map Reduce
Concepts
Module 5
Introduction to Pig
Module 6
Advanced Pig and
Introduction to Hive
Module 7
Advanced Hive
Concepts
Module 8
Extending Hive and
HBase Introduction
Module 9
Advanced HBase and
Oozie Introduction
Module 10
Project Set-up
Discussion

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BIG Data & Hadoop Applications in Real Estate

BIG Data & Hadoop Applications in Real Estate

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