big data @ xtream it
TRANSCRIPT
![Page 1: Big Data @ Xtream IT](https://reader035.vdocument.in/reader035/viewer/2022062220/556c5e29d8b42acc228b51d7/html5/thumbnails/1.jpg)
Website URL: http://xtreamit.com
![Page 2: Big Data @ Xtream IT](https://reader035.vdocument.in/reader035/viewer/2022062220/556c5e29d8b42acc228b51d7/html5/thumbnails/2.jpg)
BIG DATAJaved [email protected]
Ravi Teja [email protected] in.linkedin.com/in/ravitejakankanala/@ravi_tejaSEA OF DIGITAL FACTS
Faizeen Khandaker [email protected]
![Page 3: Big Data @ Xtream IT](https://reader035.vdocument.in/reader035/viewer/2022062220/556c5e29d8b42acc228b51d7/html5/thumbnails/3.jpg)
Real Time Analytics
Social networks
Data repositories
Web feeds: RSS,RDF etc.Log files, Sensors
Other data sources
UNSECURED DATA FEEDS
Your unstructured or semi-structured data
![Page 4: Big Data @ Xtream IT](https://reader035.vdocument.in/reader035/viewer/2022062220/556c5e29d8b42acc228b51d7/html5/thumbnails/4.jpg)
Know your data
THE 4 V’S OF BIG DATA
![Page 5: Big Data @ Xtream IT](https://reader035.vdocument.in/reader035/viewer/2022062220/556c5e29d8b42acc228b51d7/html5/thumbnails/5.jpg)
Source: Google
Volume40 zettabytes
6 Billion People
Have cell phones
World population
7 billion
Most companies in theU.S. have at least100 terabytes of data stored
VOLUMESCALE OF DATA
It’s estimated that2.5 quintillion bytesof data are created each day
![Page 6: Big Data @ Xtream IT](https://reader035.vdocument.in/reader035/viewer/2022062220/556c5e29d8b42acc228b51d7/html5/thumbnails/6.jpg)
Velocity
Source: Google
The New York Stock Exchange captures1TB of tradeinformationduring each trading session
Modern cars have close to 100 sensorsthat monitor itemssuch as fuel level and tire pressure
By 2016 it is projectedthere will be
18.9 billionnetwork connectionsalmost 2.5 connections per
person on earth
VELOCITYAnalysis of
Streaming Data
![Page 7: Big Data @ Xtream IT](https://reader035.vdocument.in/reader035/viewer/2022062220/556c5e29d8b42acc228b51d7/html5/thumbnails/7.jpg)
By the end of 2014, it is anticipated there will be 420 million wearable, wireless health monitors
400 million tweets are sent per day by about 200 million monthly active users
VARIETY
DIFFERENT FORMS OF
DATA30 billion pieces of content are shared on Facebook every month
4 billion+hours of video Are watched on YouTube each month
The value of data in healthcare 300 billion USD estimated to be
150 exabytes(161 billion gigabytes)
Source: Google
Variety
![Page 8: Big Data @ Xtream IT](https://reader035.vdocument.in/reader035/viewer/2022062220/556c5e29d8b42acc228b51d7/html5/thumbnails/8.jpg)
Source: Google
Veracity
VERACITY
UNCERTAINITYOF DATA
Poor data quality costs the US economy around$3.1 trillion a year
In one survey were unsure of
how much of their data was
inaccurate
1 in 3 business leadersDon’t trust the information they use to make decisions
Source: Google
![Page 9: Big Data @ Xtream IT](https://reader035.vdocument.in/reader035/viewer/2022062220/556c5e29d8b42acc228b51d7/html5/thumbnails/9.jpg)
US online and web influenced retail sales are forecast to become more than half of all sales by end of 2014
Online Retail Sales Growth
Source: Forrester Research Web-Influenced retail sales forecast.
![Page 10: Big Data @ Xtream IT](https://reader035.vdocument.in/reader035/viewer/2022062220/556c5e29d8b42acc228b51d7/html5/thumbnails/10.jpg)
US online and web –influenced retail sales are forecast to become more than half of all sale by end of 2014
• There is considerable growth in the online retail market.
• There is growth in alpha users of online social media.
• How can we identify more alpha users and leverage them to increase sales ?
What it means ?
Source: Forrester Research Web-Influenced retail sales forecast.
![Page 11: Big Data @ Xtream IT](https://reader035.vdocument.in/reader035/viewer/2022062220/556c5e29d8b42acc228b51d7/html5/thumbnails/11.jpg)
The number of Internet connected devices is expected to increase by 20% in 2014 to more than 16 billion. The total market for IoT solutions will be valued at almost $7.1 trillion by 2020.
Internet of things
![Page 12: Big Data @ Xtream IT](https://reader035.vdocument.in/reader035/viewer/2022062220/556c5e29d8b42acc228b51d7/html5/thumbnails/12.jpg)
Social media data: Win customer hearts
Web clickstream data: Show them the way
Server log data: fortify security and compliance
Machine and sensor data: gain insight from your equipment
Geo-location data: profit from predictive analytics
Business valueLimited end to end solutions from a variety of data ranging from unstructured data to structured data making use of predictive analytics.
Present SolutionsWe use advanced technologies such as Apache Spark, Impala and Solr as part of our platform to address day to day data needs.
We have an existing platform in place which gives data insights in real time.
Our team of data scientists understand what questions to ask and is able to extract meaningful information.
Our Approach
Addressing Big Data Challenges at XtreamIT
![Page 13: Big Data @ Xtream IT](https://reader035.vdocument.in/reader035/viewer/2022062220/556c5e29d8b42acc228b51d7/html5/thumbnails/13.jpg)
Case Study: Mystery Shopping
![Page 14: Big Data @ Xtream IT](https://reader035.vdocument.in/reader035/viewer/2022062220/556c5e29d8b42acc228b51d7/html5/thumbnails/14.jpg)
1.5 million mystery shoppers – How can we identify the alpha Mystery Shoppers ?
How can we leverage data from around the world to benefit the in-house team and our customers ?
How do we address the scarcity of Mystery Shoppers in certain locations around the world ?
Which locations can drive greater sales and bring in more profit ?
Mystery Shopping Industry
![Page 15: Big Data @ Xtream IT](https://reader035.vdocument.in/reader035/viewer/2022062220/556c5e29d8b42acc228b51d7/html5/thumbnails/15.jpg)
Introducing Back Office Reporting Suite
![Page 16: Big Data @ Xtream IT](https://reader035.vdocument.in/reader035/viewer/2022062220/556c5e29d8b42acc228b51d7/html5/thumbnails/16.jpg)
1.5 million mystery shoppers – How can we identify the alpha Mystery Shoppers ?
![Page 17: Big Data @ Xtream IT](https://reader035.vdocument.in/reader035/viewer/2022062220/556c5e29d8b42acc228b51d7/html5/thumbnails/17.jpg)
How can we leverage data from around the world to benefit the in-house team and our customers ?
![Page 18: Big Data @ Xtream IT](https://reader035.vdocument.in/reader035/viewer/2022062220/556c5e29d8b42acc228b51d7/html5/thumbnails/18.jpg)
How do we improve the scarcity of Mystery Shoppers in certain locations around the world ?
![Page 19: Big Data @ Xtream IT](https://reader035.vdocument.in/reader035/viewer/2022062220/556c5e29d8b42acc228b51d7/html5/thumbnails/19.jpg)
Which locations can drive increased sales and bring in more profit ?
![Page 20: Big Data @ Xtream IT](https://reader035.vdocument.in/reader035/viewer/2022062220/556c5e29d8b42acc228b51d7/html5/thumbnails/20.jpg)
Table representation of your data.
![Page 21: Big Data @ Xtream IT](https://reader035.vdocument.in/reader035/viewer/2022062220/556c5e29d8b42acc228b51d7/html5/thumbnails/21.jpg)
Solution ArchitectureLeveraging Hadoop Eco System
![Page 22: Big Data @ Xtream IT](https://reader035.vdocument.in/reader035/viewer/2022062220/556c5e29d8b42acc228b51d7/html5/thumbnails/22.jpg)
Other Big Data challenges addressed at XtreamIT
Mystery shopping
• We help Mystery Shopping clients make sense of all the data they collect so they can deliver meaningful insights to their customers in real time.
Retail Analytics
• We enable retailers to convert vast quantities of raw data into actionable information enabling them to optimize their business in real time.
Health Care Analytics
• With the healthcare industry undergoing transformation in data management, we enable service providers to reduce costs, improve coordination and patient outcomes and provide more with less.
![Page 23: Big Data @ Xtream IT](https://reader035.vdocument.in/reader035/viewer/2022062220/556c5e29d8b42acc228b51d7/html5/thumbnails/23.jpg)
Thank You