Date

July 26 - 27, 2016

Location

Bangalore

Remaining

150 Tickets

Speakers

15+ Professional Speakers

About the event

India Analytics Summit 2016 is coming to Bangalore for two days - July 26 - 27, 2016. Allowing excellent networking on top of intensive classes, case studies, demos and workshops that were offered. Previous iterations of India Analytics and Big data summit have allowed us to select and bring back only the finest speakers and top scoring classes to make sure that your Analytics & Big data Take - on Is unparalleled.

Trainings

Data Science with R Studio - 28 & 29 July, Bangalore

    

Agile

UNICOM provides a broad range of Agile training courses from basic one-day Introduction to Agile through to accredited training such as Certified ScrumMaster. Conferences include the UK's premier Agile event the annual Agile Business Conference and specific Agile in Public Sector and Finance Sector conferences.

Big Data

UNICOM provides events and training in these areas that enable organisations to make better decisions the address topical issues such as Big Data, Sentiment Analysis, Analytics and KPIs. Also available are training courses in specific technologies such as Hadoop.

Cloud

UNICOM has been a prominent provider of software and systems Development and Testing conferences and training. Its events and training including popular certifications such as ISTQB and Certified ScrumMaster and courses address upcoming challenges presented by moving to Agile, DevOps and Mobile environments. Conferences include SEPG Europe, Agile Business Conference, ALM Conference, TestExpo and Next Generation Testing Conference


X Workshop Abstract

Day-I :

Introduction to Data Science and Big Data
Business overview
Analytics in various industries
Different types of analytics
Statistical concepts
Statistical tools
Introduction to R Studio
Data Analytics process and methodology
Demo and Hands on

Day-II

Data loading with R
Data cleaning and preparation
Univariate statistics
Linear regression with R
Logistic regression with R
Clustering and Classification with R
Predictive Modeling
Visualization and Graphs
Mini project - Twitter sentiment Analysis with R

Conference or Event Schedule


X Topic Abstract

Recently there is considerable buzz around big data, machine learning and algorithm as part of the analytics applications across industries. However, there is a lot of other types of analytics activities that are evolving in their own right, and have their own excitement in terms of how they are helping organizations become more effective. Many of these fall under the generic label of “business analytics”. In this session, we will discuss the role these activities play, conditions for doing them effectively and types of organizational impact from them. Professionals in analytics industry, as well as consumers of analytics need to understand the role of business analytics in relation to big data and algorithms, and optimize use of both types of skills for optimal decision-making.

Speaker Profile

Ashish has over 20 years of experience in driving analytics and customer insights into strategic planning and decision-making in a wide range of organizations. The key business domains for which he has driven strategic planning include Customer Engagement (CRM), Sales & Marketing Effectiveness, Media Planning & Buying as well as Product Design & Development. Ashish has partnered closely with senior corporate leaders in major retailers, telecom, automotive, consumer good & technology companies. He currently heads eBay’s global center of excellence for analytics in Bangalore, with the aim of building cutting-edge capability to solve eBay’s hardest business problems as commerce and retail worlds converge between online and offline. Prior to eBay, his experience include key roles at major corporations like Microsoft and SABMiller, as well as consultancies like Young & Rubicam Group and Gallup Organization. He has a B.Tech. degree in Materials Engineering from IIT-Kanpur, MS from Rutgers University, and MBA from University of Iowa.


X Topic Abstract

Due to competitive pressure, OEM's are increasingly compressing the product launch time for their products worldwide. The ever evolving customer expectation is often very different across regions making it more challenging to deliver the 'best' quality for each specific market. With increased competition and pressure on margins, OEM's must differentiate themselves by improving launch quality performance and understanding their customer's needs clearly before they launch the product and service it across the product life cycle. This session examines how the automotive big data analytics can enable develop a business strategy that provides competitive advantage by improving launch quality and customer satisfaction

Speaker Profile

"Soumen De, is presently the EGM-Operational Excellence, GM International Quality at General Motors Technical Centre, Bangalore, India. He has BE (NIT) and MTech (IIT) in Electrical Engineering and MBA (IBS) as his educational background and has a work experience of two decades. His present role involves using multivariate data mining approaches and working with cross-functional teams tto identify high impact cost opportunity project/s in each of the business units of GM International. He has worked in driving innovation projects in GE R&D and GM R&D before moving to his present role in Quality function.

He has Six Sigma Black belt from GM, Project Management Professional from PMI, USA and Manager of Quality/Organizational Excellence from ASQ ,USA. He is the recipient of prestigious Charles McCuen Award at GM, which recognizes excellence in driving innovation in the organization. He has 20 patents (including filed and granted) in the area of data analytics and he has presented several papers in the data analysis and modelling. He is also the Honorary Vice President at the PMI, Bangalore India Chapter responsible for driving the Outreach initiatives of PMI"


X Topic Abstract

Over the past few years, thanks to advancements in computing technologies and availability of all types of data, the field of Business Intelligence & Analytics has really taken off and is redefining business models and competitive advantage across industries. In parallel, the GIC model has undergone a fundamental shift in the overall value proposition, moving from pure cost-arbitrage play to a much more integrated and strategic value provider. Taken together, most organizations today are investing heavily in building strong data and analytics capabilities in their GICs, taking advantage of the rich talent pool and synergies with other business processes. Mahesh Calavai and Pankaj Bagri represent one such organization, a $72 billion US retailer, Target, and will share their perspectives on what it takes to build such a capability at scale.

Speaker Profile

Mahesh is a Senior Director for Strategy and Innovation at Target. In his current role, he is responsible for various business function, insights and analytics for Target’s global supply chain. His team is involved in supply chain network planning, simulation, capacity optimization and various supply chain transformation efforts.He also leads Target’s innovation efforts, including the Accelerator Program in India.

With over 18 years of experience, Mahesh has worked in corporations and startups across diverse industries like supply chain, engineering, financial services and retail. Prior to joining Target, he has worked with various organizations like Capital One, Flour Corporation and Baan Company. Mahesh holds an undergraduate degree in Engineering from Bharathiar University and a Masters in Business Administration from University of California, Irvine.

Pankaj is aSenior Director for Business Intelligence & Analytics at Target. In his current role, he is responsible for various business insights and analytics for Target’s stores chain. His team is involved in Stores spend optimization, field Intelligence, shrinkage reduction and various transformation efforts.

Pankaj has 15+ years of experience, majorly in Analytics and Six Sigma, both in a GIC as well as in a third-party set up. Prior to joining Target, he has been associated with GenpactAnalytics CoE in various capacities for almost 8 years.Pankaj holds an MBA and a Ph.D., both from IIM Bangalore.


X Topic Abstract

Most studies today talk about the future of Business Intelligence from a 3-year or a 5-year perspective. But what about a larger timeframe of 10, 15 or even 20 years? Can we postulate, with a certain amount of confidence, how this is going to shape up? It is actually possible through a framework called Horizon Scanning that is largely been used by European Union scientists.

The presentation will highlight the expected evolution of five key components of Business Intelligence – Definition, Sourcing, Reporting, Form & Tools - over the next 5 years, the next 10 days and the next 15 years. Emerging and future technologies, expected changes in corporate adoption strategies and availability of data in new forms will be key considerations.

Speaker Profile

Coming Soon....


X Topic Abstract

Statistics evolved as a means of studying data in the mid 1700s -- a time when available data was exploding. During most of the history of statistics, our ability to handle large volumes of data was limited, making sampling essential. Our ability to exhaustively test possibilities was also limited, leading to a hypothesis driven approach.

Today, neither is a constraint. Most datasets can be cruched several times over on mobile devices. But while our ability to handle large scale data has improved, our skills in automating analysis are only now growing.

This talk shares some common analysis patterns that are fully automatable and consistently lead to interesting insights. We will share results from varied fields such as education, finance, infrastructure, poultry, transportation, etc and talk about principles governing these datasets. We will also discuss the directions automated analysis is moving towards.

Speaker Profile

Coming Soon....

Panel Discussion - Building a Data Science Team From Nothing


X Topic Abstract

There is no value in big data without big analytics. In fact it just costs money to collect and store big data unless business value is derived from it. Big data analytics is the mechanism to leverage value from big data.

There are three trends that impacts the leveraging of value from big data. First is evolution of big data and its management. Big data is characterized by large volumes of data that consists of structured, human language text, multi-structured data such as from RFID, JSON, and streaming data from sources such as Web applications, social media, machine logs, and sensors. These data have to be collected, stored, and delivered for processing. This is complex especially when the data is used in a way that is different from its origin. Unlike structured data management systems where the usage determines the data model the trend with unstructured data is late binding. The second is the evolution in data engines. There are different technologies such as cloud, in-memory, no-SQL, MPP, computational clusters, and array machines that are tailored for specific kinds of operations. There are also many software systems that are tailored for specific applications. The third trend is the large number of advanced techniques for analyzing big data. There are techniques such as predictive analytics, text analytics, data mining, natural language processing, statistical analysis, and machine learning techniques such as neural nets. Such techniques are needed for operations on unlabeled and uncategorized data. The intent is to automatically detect patterns in data and generalize the learnt patterns for use on future data. Analytics on big data is generally about uncovering hidden patterns, hitherto unknown correlations, trends, customer preferences and other useful business information from large volumes of different types of data. There is also value in combining multiple analytic techniques for a given problem. This is called multi-genre analytics.

A computational infrastructure is needed that combines these three trends and provides a working architecture for harnessing big data. In this talk we present such architecture and validate it through use cases.

Speaker Profile

Coming Soon....


X Topic Abstract

Session will be about current big data Industry challenges, solutions, what will be future challenges and how customer are trying to solve them.

The presenter will also show how HPE has prepared to handle these challenges using proper technology and Tools in place.

Speaker Profile

Ravi has over 14 years of experience in designing & Architecting Data Warehousing, Data Analytics and customer insights solutions. Ravi has worked and helped in planning and decision-making on Data warehousing , implementing big data analytics to larger organizations worldwide. The key activities where currently Ravi involved is Architecting, Designing, Customer Engagement, Sales & Product Marketing as well. Ravi has been working with senior leaders of major e-retailers, telecom, Finance & Technology companies. He currently leads HPE Big Data Platform practices in India as Regional Presales, Prior to this role he was part of Vertica Engineering team where he did various tools integration, Product QA , product implementation , Solution Designing & Supported large databases. Prior to that , he worked with HCL Technologies where he worked upon various database technologies and EDW solutions. He has Master’s Degree in Computer Application from Meerut University.


X Topic Abstract

Data analytics as a concept is not new. It has been finding it's way in terms of application across different industry verticals for multiple decades now in some form or the other. Certain industries, like BFSI, have been carrying the flag in terms of leverage in decision management. With the advancement in technology, proliferation of data, network & awareness, and progressive thinking, the popularity of the concept has accelerated over the last few years. Since, data analytics now cuts across the verticals horizontally, the industries which have been relatively laggard in adoption can benefit from the ones which are the early adopters.

For example, the thought process of application of 'business-integrated' analytical streams of 'Descriptive', 'Predictive', and 'Prescriptive' analytics to customer lifecycle of 'Acquire', 'Engage', and 'Retain', widely adopted in consumer facing businesses like consumer banking, now is making it's entry into sectors like Retail and Pharma. Concepts of 'RFM', 'Association', and 'Customer value', popular in retail and CPG, is now being readily adopted in banking and insurance analytics. Concepts of machine learning and AI are now creating new avenues for enabling businesses to re-think, re-orient, and change the traditional ways of doing business and reap the benefits of incremental impact and competitive edge.

The presentation will cover through variety real examples, how data analytics as a discipline can act as a catalyst to drive leverage of best practices across industry verticals.

Speaker Profile

Satyamoy is a seasoned analytics professional with deep Financial Industry experience. His past experiences include 12+ years in managerial and leadership roles in large multinational fortune 50 organizations like Citigroup and GE. He is passionate about creating business value, driven by analytical innovations and connecting content to context, through the right leverage of 'Business Knowledge', 'Data Science' and 'Technology'. Satyamoy is also passionate about coaching and developing talent. He is leveraging the same in driving the build and launch of Analyttica's flagship product TreasureHunt® an Analytics training solution. He is a recipient of several project and client excellence awards and trained in different levels of corporate leadership and executive development programs.

Satyamoy is an MS in Industrial Engineering and has also done is executive general management from IIM Bangalore.


X Topic Abstract

This presentation will focus on elucidating the role of Business Analytics in the realm of Clinical Trials executed by Pharma and Biotech companies the world over. The perspective will be provided from past, present and future scenarios.

1. Historically, the focus will be specifically on how the field of Statistics helped derive the right interferences on Trial Outcomes. The emphasis will be on hypothesis testing and the various statistical models used in the process.

2. From the present day scenario, the focus will be on descriptive and visual analytics especially the impact that Spotfire is having on the field of Pharma

3. There is immense potential for analytics in the Clinical Development Space in future. They are

a. Risk Based Monitoring
b. Patient Recruitment and Retention
c. Site Selection
d. Clinical Development Performance Review

Speaker Profile

Shankar has more than 20 years of experience in the field of IT Services with a specific focus on the Life Sciences Industry. He has anchored the setup of Large Offshore Development Centers and delivered complex programs in the Life Sciences R&D space which include Clinical Data Management, Biostatistics, Regulatory Affairs and PharmacoVigilance. Prior to entering the Life Sciences Industry, Shankar has worked as a consultant in the US for some of the prestigious names like Microsoft (Seattle) and Apple (Cupertino).

As an Executive Director and General Manager for Chiltern Clinical Research Clinical Analytics Division, Shankar has end to end responsibility for Business Functions within India. Chiltern Clinical Analytics division provides IT services around visual analytics, statistical analysis, stats programming and data validation. This group has one of the largest talent pool in Biostats analytics within India and has been in this business for more than 10 years.

Apart from being a six sigma black belt and a certified scrum master, Shankar holds a PGDGM from the prestigious Narsee Monjee University, Mumbai. He is a prominent speaker in the CRO forums like DIA, PhUSE, IASCT etc.


X Topic Abstract

Analytics-driven embedded systems are here!

We'll show this in action by classifying human activity in real-time using sensor data from a smartphone accelerometer. The demo will show a complete workflow:

– pre-processing with digital filtering and frequency analysis,

– exploring different classification algorithms (such as decision trees, support vector machines, or neural networks), and

– automatically generating C/C++ from MATLAB to deploy a streaming classification algorithm for embedded sensor analytics.

The ability to create analytics that process massive amounts of business and engineering data is enabling designers in many industries to develop intelligent products and services. We'll show you how to use analytics to describe and predict a system's behavior, and further combine analytics with embedded control systems to automate actions and decisions.

Speaker Profile

Coming Soon....


X Topic Abstract

Enterprise intelligence exists in multiple places - implicitly with the teams, in structured and transactional databases, in unstructured data repositories, and scattered with vendors, suppliers, partners and policy makers. This talk focuses on one major source of enterprise intelligence, namely unstructured data repositories, which include internal documents, emails, voice files, images, videos, system logs, raw sensor data, physical documents, etc. We discuss Unified Framework to collate, preprocess, ingest, analyze and leverage unstructured data repositories, substantiated by concrete examples drawn from multiple industry verticals. We will also compare and contrast our work with existing frameworks for unstructured data analytics.

Speaker Profile

Dr. Sreerama KV Murthy received a PhD in Data Mining and Machine Learning in 1995 from the prestigious Johns Hopkins University. Prior to that, Dr. Murthy completed a Master's thesis in Next Generation Expert Systems from IIT-Madras Computer Science.

Automatically building mega-catalogs from Hubble Space Telescope images was Dr. Murthy’s PhD thesis. The software he designed is used till date in scores of countries. His paper on the topic continues to be a top-cited paper in the area of Decision Trees and Machine Learning.

In the past 25 years, Dr. Murthy worked for world-class research labs such as Siemens Corporate Research - Princeton, IBM Research - Delhi; and National Center for Software Technology (now CDAC, Mumbai). He also has been instrumental in setting up three startup companies that drove innovation in AI & data mining in the areas of vocational skilling, healthcare and supply chain management.

Dr. Murthy currently is the CEO of Quadratyx, a company that offers corporate training, proprietary elearning and consulting services in Big Data, Machine Learning, Text & Image Mining and Predictive Analytics. Quadratyx helps dozens of customers in India and abroad, and also performs advanced research in Big Data & Predictive Analytics.

Dr. Murthy has 8 issued US patents, over a dozen patent-pending innovations, and scores of international publications, all in the area Data Science. His team has done seminal work in learning analytics. Dr. Murthy has been a Principal Advisor & Mentor for the International School of Engineering since its inception.

Representative experience:

- Training CXOs about the business value and risks associated with data analytics (HDFC Bank, Axis Bank, Kotak Mahindra Bank, Micromax, AT&T, Microsoft, Edelweiss, DRDO, Progress Software, etc.)
- Price impact prediction (Johnson & Johnson)
- Fertilizer Demand Forecasting (Coromandel International)
- Big Data Infrastructure design and implementation (Axis Bank)
- Advanced Analytics models for Delinquency prediction (HDFC Bank, National Bank of Oman)
- Attrition & Retention Analytics (Mahindra Finance)
- Predictive Dealer Scoring (Tata Steel)
- Personalized vocational skilling on a mass scale using e-learning & data mining (Maruti Suzuki, Commonwealth of Learning, Enable India)
- Unstructured survey text mining for decision support (American Bureau of Shipping)
- Clinical trial protocol mining (Novartis)
- Teaching Carnegie Mellon University-certified courses in Big Data Analytics
- Media content analysis and protection
- Image analytics for automated measurements
- Sales recommendations to the CPG industry


X Topic Abstract

Azure Machine Learning provides an easy-to-use and powerful set of data management, data transformations, and machine learning tools. These powerful cloud-based tools make the power of predictive analytics readily accessible in any organization. R and Python language scripts integrate with built-in Azure ML modules, extending the platform and providing powerful data visualization. Models and data visualizations, running in Azure ML, are made easily available by publishing as web services.

Speaker Profile

Coming Soon....


X Topic Abstract

Machine learning has been the engine of growth for the internet search engines, social media and ecommerce giants. Which customers to cater to, which segments to retreat from have been decided based upon models and simulations. While the ideas are not completely unknown to banks, we are yet to see broad based activity (like BI has become now) excluding some digital banks or a few other outliers.

We shall explore the challenges and concerns banks are having w.r.t. using machine learning for business decisions. We shall explore some use cases related to targeting new customers, introducing new products, reducing operational costs related to customer servicing as application of machine learning based intelligent decision making

Speaker Profile

Suman has earlier worked in risk analytics in retail banking and in the front office of global markets with large global banks. He later moved to analytics and continued with it due to his deep interest in the topic. His interest areas are prediction and optimisation and with new found interest around machine learning and IoT.


X Workshop Abstract

Day-I :

Introduction to Data Science and Big Data
Business overview
Analytics in various industries
Different types of analytics
Statistical concepts
Statistical tools
Introduction to R Studio
Data Analytics process and methodology
Demo and Hands on

Day-II

Data loading with R
Data cleaning and preparation
Univariate statistics
Linear regression with R
Logistic regression with R
Clustering and Classification with R
Predictive Modeling
Visualization and Graphs
Mini project - Twitter sentiment Analysis with R


X Workshop Abstract

Day-I :

Introduction to Data Science and Big Data
Business overview
Analytics in various industries
Different types of analytics
Statistical concepts
Statistical tools
Introduction to R Studio
Data Analytics process and methodology
Demo and Hands on

Day-II

Data loading with R
Data cleaning and preparation
Univariate statistics
Linear regression with R
Logistic regression with R
Clustering and Classification with R
Predictive Modeling
Visualization and Graphs
Mini project - Twitter sentiment Analysis with R

Sponsors

Benefits of sponsorship

This is a great opportunity to strategically brand your organization. As a sponsor, you will receive a tremendous amount of visibility and numerous other benefits at the conference.

Sponsorship Levels

Platinum Sponsor (Limited to 2)

Gold Sponsor (Limited to 3)

Knowledge Partner (Limited to 1)

Silver Sponsor (Limited to 4)

Bronze Sponsor (Limited to 4)

Conference Bag Sponsor (Limited to 1)

Track Sponsor (Limited to 2)

A-La-Carte (Open)

       

Instant Sponsorship

Instant Sponsorship $500  View details



X

INSTANT SPONSORSHIP

Instant Sponsorship includes:

 Logo/link on UNICOM website

 Logo on presentation screens throughout conference

 2-day Conference Pass

Past Sponsors

Testimonials

Event Speakers

Ravi Gupta

Presales

HPE

Soumen De

EGM Operational Excellence

GENERAL MOTORS

Tamal Chowdhury

Senior Director

Oracle

Abhishek Narain

Technical Evangelist

Microsoft

Maheshwaran Calavai

Senior Director - Analytics and Innovation

Target

Pankaj Bagri

Senior Director - Business Intelligence & Analytics

Target

Satyamoy Chatterjee

SVP, Head of Client Solutions

Analyttica

Shankar Arun

Executive Director and General Manager

Chiltern

Amit Doshi

Senior Application Engineer

MathWorks India

S Anand

Chief Data Scientist

Gramener

Abhay Sharma

Communication Sector Leader - Cognitive Solutions

IBM

Srinivas G.R

VP & Head - Business Solutions & Analytics

Brillio

Dr. Sreerama K Murthy

CEO & Chief Data Scientist

Quadratyx

Ramesh Bhashyam

Chief Technical Officer

Teradata R&D Labs

Ashish Singru

Sr. Director India Analytics Center

eBay

Suman Mandal

Vice President Data & Analytics Solutions, AsiaPac, ME & Africa

Polaris Financial Technology Limited

Event Price list (26 - 27 July)

Any One Day

Standard : Rs 8,999
(Till 26th July)

Both Days

Standard : Rs 15,999
(Till 26th July)

Workshop

Standard : Rs 18,000
(Till 27th July)

X Workshop Abstract

Day-I :

Introduction to Data Science and Big Data
Business overview
Analytics in various industries
Different types of analytics
Statistical concepts
Statistical tools
Introduction to R Studio
Data Analytics process and methodology
Demo and Hands on

Day-II

Data loading with R
Data cleaning and preparation
Univariate statistics
Linear regression with R
Logistic regression with R
Clustering and Classification with R
Predictive Modeling
Visualization and Graphs
Mini project - Twitter sentiment Analysis with R

Event FAQS

India Analytics Summit 2016 is open to anyone who has an interest in the Analytics and works in the technology/telecoms industry or any related field.

No

Yes, all conference attendees must register in advance to attend the event.

As this is predominantly an event for the IoT Industry, if you are interested in attending. Please note that there will be a charge to attend as a student(can avail special discount as a student).

Yes you can, please contact contact@unicomlearning.com with what you would like to be changed and we can assist.

Please fill the below details of your colleague and send us an email block the seats. Name
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Event Location

Hotel Novotel Bengaluru Techpark
Opposite RMZ Ecospace Business Park,
Marathahalli Sarjapur Outer Ring Road,
Bengaluru, Karnataka 560103
Phone:080667 05000

contact@unicomlearning.com

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Unicom Address

A.V.Bureaux,
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Phone : +91 80 4161 3433

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"Confirm your CANCELLATION in writing up to 15 working days before the event and receive a refund less a 10% service charge. Regrettably, no refunds can be made for cancellations received less than 15 working days prior to the event.

However, SUBSTITUTIONS are welcome at any time and is done at no extra cost. The organisers reserve the right to amend the programme if necessary.

INDEMNITY: Should for any reason outside the control of UNICOM Training & Seminars (P) ltd (hereafter called UNICOM), the venue or the speakers change, or the event be cancelled due to industrial action, adverse weather conditions, or an act of terrorism, UNICOM will endeavour to reschedule, but the client hereby indemnifies and holds UNICOM harmless from and against any and all costs, damages and expenses, including attorneys fees, which are incurred by the client. The construction validity and performance of this Agreement shall be governed by all aspects by the laws of India to the exclusive jurisdiction of whose court the Parties hereby agree to submit."