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Big Data @ Xtream IT

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Information about Big Data @ Xtream IT
Data & Analytics

Published on September 24, 2014

Author: XtreamIT

Source: slideshare.net

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1. Website URL: http://xtreamit.com

2. BIG DATA Javed Sikander javed.sikander@xtreamit.com Ravi Teja Kankanala ravi@xtreamitlabs.com in.linkedin.com/in/ravitejakankanala/ @ravi_teja SEA OF DIGITAL FACTS Faizeen Khandaker faizeen.khandaker@xtreamit.com

3. Your unstructured or semi-structured data Real Time Analytics UNSECURED DATA FEEDS Social networks Data repositories Web feeds: RSS,RDF etc. Log files, Sensors Other data sources

4. Know your data THE 4 V’S OF BIG DATA

5. Source: Google Volume 40 zettabytes 6 Billion People Have cell phones World population 7 billion Most companies in the U.S. have at least 100 terabytes of data stored VOLUME SCALE OF DATA It’s estimated that 2.5 quintillion bytes of data are created each day

6. Velocity Source: Google The New York Stock Exchange captures 1TB of trade information during each trading session Modern cars have close to 100 sensors that monitor items such as fuel level and tire pressure By 2016 it is projected there will be 18.9 billion network connections almost 2.5 connections per person on earth VELOCITY Analysis of Streaming Data

7. 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 DATA 30 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

8. Veracity Source: Google 1 in 3 business leaders Don’t trust the information they use to make decisions VERACITY UNCERTAINITY OF 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 Source: Google

9. Online Retail Sales Growth US online and web influenced retail sales are forecast to become more than half of all sales by end of 2014 Source: Forrester Research Web-Influenced retail sales forecast.

10. 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.

11. The number of Internet connected devices is expected to increase by 20% in 2014 to more than 16 billion. The total market for IoTsolutions will be valued at almost $7.1 trillion by 2020. Internet of things

12. Business value Social media data: Win customer hearts Web clickstreamdata: 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 Present Solutions Limited end to end solutions from a variety of data ranging from unstructured data to structured data making use of predictive analytics. Our Approach We use advanced technologies such as Apache Spark, Impala and Solras 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. Addressing Big Data Challenges at XtreamIT

13. Case Study: Mystery Shopping

14. 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

15. Introducing Back Office Reporting Suite

16. 1.5 million mystery shoppers – How can we identify the alpha Mystery Shoppers ?

17. How can we leverage data from around the world to benefit the in-house team and our customers ?

18. How do we improve the scarcity of Mystery Shoppers in certain locations around the world ?

19. Which locations can drive increased sales and bring in more profit ?

20. Table representation of your data.

21. Solution Architecture Leveraging HadoopEco System

22. 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.

23. Thank You

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