Date

February 09 - 10, 2017

Location

Bangalore

Capacity

100 Tickets

Speakers

14+ Professional Speakers

About the event

This Summit - amongst UNICOM annual events- brings together industry professionals, companies and individuals from the field of Big Data and Analytics. We recognize that this core sector in business and technology is currently the big wave. Besides being a key focus area, arguably, in future, this alone is likely to be the differentiator between successful organizations.

India Analytics and Big Data Summit 2017 is coming to Bangalore for two days – February 09th & 10th . 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 conference is unparalleled.

This conference will provide an opportunity to discuss and delineate the latest advancements in Data Analytics and big Data, focusing on the development and use of innovative solutions for the businesses. Attendees will hear from a variety of industry expertise, leading research and development organizations and top most academicians.

Internet of Things: Link your World" - Exploring the latest happening in IoT Industry and how the Internet of Things will offer businesses and consumers.

With a theme of "Enough talking about Big Data, Learn how to DO IT at India Analytics and Big Data Summit" - the conference this year will focus on talking about Analytics ,IoT and Big data from a general context and getting deeper into the Big data mind-set and imbibing Analytics and Big data in our life. Following are the tracks identified within the theme:

- Best in class methodologies to institutionalise big data analytics in your organisation
- What is your role in driving a cultural shift to a data driven decision making?
- Draw actionable consumer insights based on your data analytics capacity
- Integrate analytics with marketing strategy & CRM to build a loyal, long lasting relationship with your clients
- IoT in Home Automation & Wearable Devices
- IoT Analytics & Security

The event is co- located with the two Prestigious All India Contest

(1) Analytics & Big Data Olympiad - The 3rd edition of the annual corporate quiz contest on Analytics, Analytics Olympiad 2017 is back!!. Purpose of this contest is to identify India's most knowledgeable Analytics Professionals. This year, the format has changed with a different list of topics. Will you bring laurel to your organization and to yourself?

Over 5000 IT professionals from 1000+ companies in India and abroad would be participating, with experience ranging from 6 months to 25 years and professionals in Analytics

Click Here to Read More

Pre-conference Workshops

Business Analytics in Action - 2 Days Workshop (7 - 8 February, 2017)

Business Analytics is a set of methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information. This is used to enable more effective strategic, tactical and operational insights that is focused on the analysis of data using statistics and provides necessary insights and prediction. It helps the users perform deep-dive understanding and provide descriptive, predictive and prescriptive analytics and drive decision-making.



Big data Analytics using Spark (9 - 10 February, 2017)

Big Data/Hadoop Introduction
What is Big Data and Data science
Introduction to Distributed computing and Hadoop
Hadoop Architecture – HDFS/MapReduce
Anatomy of a Hadoop cluster,
Hive - Architecture Demo, Hands on



Fog Computing for Big data from IoT (8 February, 2017)

Post-conference Workshops

Machine Learning with BigData (13 - 15 February, 2017)

The art and science of making sense of data is a highly sought after skill in today’s data driven world.Data science isn’t just for data scientists. In massively connected data driven world, it is imperative that the workforce of today and tomorrow is able to understand what data is available and use scientific methods to analyze and interpret it.



Big Data & Hadoop Developer (16 - 18 February, 2017)

Big enterprises around the world have found Hadoop to be a game changer in their Big Data management, and as more companies embrace this powerful technology the demand for Hadoop Developers is also growing. By learning how to harness the power of Hadoop 2.0 to manipulate, analyse and perform computations on Big Data, you will be paving the way for an enriching and financially rewarding career as an expert Hadoop developer.




X Workshop Abstract

Background
Business Analytics is a set of methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information. This is used to enable more effective strategic, tactical and operational insights that is focused on the analysis of data using statistics and provides necessary insights and prediction. It helps the users perform deep-dive understanding and provide descriptive, predictive and prescriptive analytics and drive decision-making.

Business Analytics is the growing area and not enough expertise. Companies are finding huge value in Business Analytics. It is used to run the business effectively and is instrumental in growing the business. Companies are ready to invest significant amount of money in setting up the business analytics platform either by using existing tools/package or building their own. The skills needed to use the business analytics platform effectively is not adequately available.

Expertise is needed at various levels to use the business analytics platform, perform business analytics, provide insights, reporting and driving data-driven decisions. While the work involved is challenging and interesting, the salary offered by many companies are very good. Organizations are searching for employees that have strong analytical and business skills. While this combination seems to be rare among today's professionals, yet is in incredibly high demand and because of which organizations are ready to pay the right salary for right talent.

Business Analytics include identifying KPIs, measurement strategy, data analysis, complex statistical model and analysis, data mining and deep understanding of cause-and-effect models. Business analytics can drive key decision making in the organization and help executive decision makers in building strategy, predictive analysis, forecasting, risk analysis, identify and prevent fraud, market analysis, etc.

What are Business Analytics?
By analytics we mean the extensive use of data, statistical and quantitative analysis, to understand the data and building explanatory and predictive models and fact-based management to drive decisions and actions. The analytics may be input for human decisions or may drive fully automated decisions.

Competing on analytics?
When companies in industries offer similar products and use comparable technology, high performance business processes are among the last remaining points of differentiation. Many of the previous bases for competition are no longer available. Unique geographical advantage doesn’t matter in global competition, and protective regulation is largely gone. Proprietary technologies are rapidly copied, and breakthrough innovation in products or services increasingly difficult to achieve. What’s left as a basis of competition is to execute your business with maximum efficiency and effectiveness, and to make the smartest business decisions possible. Thus, analytical competing is the mean to ensure business sustenance, and future-growth for organization. There are five stages of Analytic Competition that organizations practice, based on which the companies grow and make this as a competitive advantage by giving better value to the consumers, reducing cost and adding new avenues of revenues.

1. Analytically Impaired
2. Localized Analytics
3. Analytical Aspirations
4. Analytical Companies
5. Analytics Competitors

Business analytics enables organizations to accurately manage and react to changing situations around them, and bridge the gaps between information across the organizations. There are a number of benefits of using business analytics to organizations across their functions. Following are some of the benefits of business analytics:

- Improving the decision making process (quality & relevance)
- Speeding up of decision making process
- Promoting and fostering a culture of data & fact-based decision making and accountability
- Better alignment with strategy
- Realizing cost efficiency
- Responding to user needs for availability of data on timely basis
- Improving competitiveness
- Producing a single, unified view of enterprise information
- Synchronizing financial and operational strategy
- Increase revenues
- Sharing information with a wider audience

The next level of business analytics is to help people with drill-down capabilities to analyze data from multiple angle to find out more information which otherwise is difficult to think about and find. With that comes meaningful insights – to help people take business decisions.

Data Scientists use these skills are able to provide insights into discrete data sets, build complex model and present them in Scorecard format and use the same in executive reviews to lead data-driven discussion and decisions. Some of the impactful use of this is in the areas of Management Information Systems, Financial Service, Marketing Research, Process Improvements, Six Sigma, Process Excellence, Scorecard, Dashboard, End-to-End Product Management, etc.

The training is hands-on and provides opportunity to learn different types of Business Analytics approach, applications, etc. and help them to prepare for explaining and teaching others. Participants should not expect lot of theory, statistical formulas, models, etc., instead they will be shared some real-life data/problems or simulated data and will be working thru building the business Intelligence reports, scorecard and dashboard. Participants will learn data analysis and quantitative modeling skills to solve business problems and achieve better business performance. Additionally, they will gain knowledge of how to solve team-based, real-world business problems.

Course Outline

1. Background
a. Overview of Business Analytics
b. Competing on Analytics
c. Getting started with Business Analytics

2. Measurements & Data
a. Identifying Business Metrics and KPI
b. Sources of Data
c. Types of Data
d. Measurement Strategy
e. Measurement System Analysis
f. Data Gathering & Data Mining
g. Data Quality Management, Consistency and Integrity
h. Handling Large volume, variety and velocity of data (Big Data)

3. Tool
a. Working with Data in Excel
b. Getting Started with R Programming

4. Statistics Foundation
a. Statistical thinking and definition of statistics
b. Correlation and Correlation Coefficient – Linear Regression
c. Sampling and Sampling Methods
d. Measures of Central Tendency, Dispersion, Shape
e. Cause-effect Analysis
f. Regression Analytics
g. Hypothesis Testing

5. Analytics
a. Analytics vs Analysis
b. Descriptive Analytics
c. Predictive Analytics
d. Prescriptive Analytics
e. Machine Learning
f. Unstructured data collection and analysis

6. Visualization & Reporting
a. Telling Stories with Data
b. Building Scorecard
c. Creating Effective Dashboards
d. Using Excel for Data Visualization, Analytics and Reporting
e. Automated Monitoring, Threshold & Alerting

7. Business Analytics in Action
a. Hands-on group assignment
b. Analytics for Mobile Apps
c. Social Monitoring
d. Service Quality Monitoring
e. Human Resource Analytics
f. User Online Behavior Analytics
g. Retail Customer Analytics
h. Specific Examples of Business Analytics in Action from Microsoft, Reliance Jio and NICE

8. Conclusion
a. Starting with Business Analytics
b. Career Options
c. Success with Business Analytics

Speaker Profile

Mukesh Jain is Educationist, Author, Coach and Techno-Biz Leader with 21 yrs of experience working with legendary people like Bill Gates, Satya Nadella and Mukesh Ambani. He have built & led multiple Global Teams and delivered Analytics driven Innovative Products that used by Millions of people worldwide.

He have led R&D and built products like Outlook, OWA, Hotmail, Messenger, MSN, Bing, Advertising, Mobile Apps, e-commerce, Open Source Big data Analytics, Financial Analytics - Actimize, IoT, etc. in companies like Microsoft, Reliance Jio, NICE, ATOS, Syntel and Datamatics in USA, Japan, China & India.

He is Advisor to KJ Somaiya Engg College, Vanguard Business School, MGM Engg College, JSPM Engg College, Simplilearn & EduPristine. He helped build curriculum, conducted faculty development workshops and students training in the areas of Big Data, Business Analytics, Product Management, Software Engineering, Software Testing, Excel, Digital Marketing, Lean Management and Six Sigma.

He is the recipient of multiple awards, including Microsoft’s most prestigious “Gold Star” award 3 years in a row, Asia-Pacific Leadership Award, Management Excellence, Outstanding Mentor, Solution Excellence, Microsoft-Yahoo People Excellence Award, ASQ Quality Laureate, Quality of Service Award, QAI Agile Project Management Leadership Award, iSixSigma Best Six Sigma Black Belt, etc.

He is currently, the Vice President (R&D) & Head of NICE in Pune. He has setup NICE in Pune and is leading multiple R&D teams in areas of Machine Learning & Big Data based large scale Analytics Platform in Financial and Experience domains that are used by 85% of Fortune 100 companies. In Pune, he attracted and hired 380 engineers in a year and expend to 540 highliy capable R&D teams by 2016.

Prior to NICE, he was Vice President & Head at Reliance Jio (4G) for 2.5 yrs leading Advertising Business, Mobile Advertising RTB Platform, Social Media Analytics & Big Data Analytics Platform. He developed the strategy and built one of the largest Big Data Analytics Platform in India providing real-time dashboard, detailed scorecard, predictive & prescriptive analytics for all the Jio Mobile app data.

He worked at Microsoft for 13.5 years (mostly in USA) as R&D Engineering Director leading large global engineering teams. In 2011, he moved to India to setup Microsoft R&D center in Bangalore and provided strategic & technical leadership for Microsoft-Yahoo! Alliance leading engineering teams in Analytics & Advertising. He had honor of successfully leading and executing Microsoft’s 1st Six Sigma project in 2001. He created and led “Day-In-A-Life” program across Office. He built and rolled out Microsoft wide Business Analytics program (Business QoS), now used by all Microsoft Online Services.

He is a seasoned coach, mentor, author and speaker. He regularly speak at international conferences, business schools & engineering colleges (IITs, IIMs, BITS Pilani, NITs, …) on a variety of topics (Leadership, Personal Excellence, Agile, Product Engineering, DevOps, Smart Cities, Internet of Things (IoT), Big Data, Business Analytics, Cloud, Google Analytics, Social Media, Digital, Mobile, Design of Experiments (DoE), Experimentation, Digital Marketing, Advertising, Product Management, SEO, Project Management, Six Sigma & Lean). He have made presentations at international confernces like IEEE, WorldHRD, iSixSigma, PMI, SEPG, SPIN, QAI, NASSCOM, UNICOM, Agile, BZMedia, Better Software, IdeaBytes, etc.

He has done B.E. in Computer Science and Executive Managmeent program from IIT Bombay. Microsoft Certified Standards Professional, MCAS, MOS, Statistical Process Control, Licenced TSP Coach, PSP Engineer, Lean, Six Sigma Master Black Belt, CQIA, CSQA, CSTE, CQA, CTFL, MOF & ITIL

He is author of books “Delivering Successful Projects” and “Web Performance Improvement”. He is now writing books on “Effective Business Analytics for SoLoMo” and “Personal Excellence”.

He can be reached at http://www.linkedin.com/in/MukeshJainCoach, mdjain@hotmail.com


X Workshop Abstract

The art and science of making sense of data is a highly sought after skill in today’s data driven world.Data science isn’t just for data scientists. In massively connected data driven world, it is imperative that the workforce of today and tomorrow is able to understand what data is available and use scientific methods to analyze and interpret it. Data science is now recognized as a highly-critical growth area with impact across many sectors including science, government, finance, health care, telecom, manufacturing, advertising, retail, and others. Launch your data science career with this practical workshop. Build a solid foundation in machine learning using R and start exploring data-related careers.

TOP 9 REASONS TO ATTEND

- Understand the art and science of discovering patterns and making intelligent predictions from big data.

- Define machine learning, why it matters, and discuss its relationship to analytics, data science, and big data.

- Machine learning fundamentals, the importance of algorithms, and machine learning as a service.

- Basics of R platform, programming language concepts, common and useful R commands, and applying machine learning methods.

- Doing machine learning - Understanding the steps in the machine learning pipeline, from data acquisition and feature generation, to training and model selection.

- Practically learn the most commonly used machine learning methods, covering both supervised and unsupervised learning.

- Develop understanding of which algorithm to choose based on the analytics challenge and the data you have.

- Be able to appreciate the trade-offs involved in choosing particular techniques for particular problems.

- Discover how to understand, interpret and convey the results of data science life cycle.

AGENDA

The workshop has a strong focus on gaining hands-on experience implementing algorithms and building predictive models on real datasets. By the end of the 3 days, participants will be ready to implement the machine learning algorithms using data science on your own data, and immediately generate value.

The workshop will take participants through the conceptual and applied foundations of the subject. Topics covered include:

- R for Statistical Analysis and Machine Learning
- Machine learning theory, types of learning
- Techniques, models and methods
Labs are developed to practically learn how to use the R programming language and packages for applying the main concepts and techniques of data science and machine learning.

Day 1:

Data Science and Machine Learning – Context, Toolkit and Industry Practices

- A data-driven digital world, introduction to Data Science and component parts of Data Science
- Enterprise Big Data platform architectures, Hadoop ecosystem and Apache Spark
- Data Science Toolkit and Life Cycle – A strategy to approach data analytics problems
- Fundamentals of Machine Learning for Data Science
- R for Statistical Analysis and Machine Learning
- Basics of R Programming

Day 2:

R Programming and Applications of Machine Leaning Models
- Pre-processing and Machine Learning Workflow
- Guest Speaker slot
- Model Selection: Training, Validating and Testing
- Regression Models

Day 3:

Advanced Predictive Methods and Capstone Project
- Classification Models
- Ensemble Methods
- Capstone Project


X Workshop Abstract

Big enterprises around the world have found Hadoop to be a game changer in their Big Data management, and as more companies embrace this powerful technology the demand for Hadoop Developers is also growing. By learning how to harness the power of Hadoop 2.0 to manipulate, analyse and perform computations on Big Data, you will be paving the way for an enriching and financially rewarding career as an expert Hadoop developer.

Who can attend?

- Architects and developers who design, develop and maintain Hadoop-based solutions.
-Data Analysts, BI Analysts, BI Developers, SAS Developers and related profiles who analyze Big Data in Hadoop environment.
-Consultants who are actively involved in a Hadoop Project.
-Experienced Java software engineers who need to understand and develop Java Map Reduce applications for Hadoop 2.0.

Complete course outline:

Key Take aways:
From the course:

-Understand Big Data and the various types of data stored in Hadoop.
- Understand the fundamentals of MapReduce, Hadoop Distributed File System (HDFS), YARN, and how to write MapReduce code.
-Learn best practices and considerations for Hadoop development, debugging techniques and implementation of workflows and common algorithms.
-Learn how to leverage Hadoop frameworks like ApachePig™, ApacheHive™, Sqoop, Flume, Oozie and other projects from the Apache Hadoop Ecosystem.
-Understand optimal hardware configurations and network considerations for building out, maintaining and monitoring your Hadoop cluster.
-Learn advanced Hadoop API topics required for real-world data analysis.
-Understand the path to ROI with Hadoop.

From the workshop:

-High quality training from an industry expert
-24 hours of comprehensive training
-Earn 24 PDUs
-Course Completion Certificates
-50% interactive and hands-on training exercises using HDFS, Pig, Hive, HBase, key MapReduce components and features, and more.


X Workshop Abstract

Agenda
Day 1

Big Data/Hadoop Introduction
What is Big Data and Data science
Introduction to Distributed computing and Hadoop
Hadoop Architecture – HDFS/MapReduce
Anatomy of a Hadoop cluster,
Hive - Architecture Demo, Hands on

Python ( Pre-req for Spark) - Introduction to Python
- Programming concepts
- Demo and Hands on Exercises Spark - Introduction to Spark
- Spark Installation
- Spark Architecture
- RDD's
- Lazy evaluation
- Transformations and Actions
- Sample programs
- Demo and Hands on
- Spark- SQL
- Datasets, DataFrames

Day 2

Recap of Day1 Spark ..contd
Loading data from different type of files
- Txt,Json,Parquet,CSV Spark -Hive integration Spark – MlLib
- Introduction to Machine learning
- MlLib Api's
- Statistical Modeling using API's
- K-Means Clustering
- Regression and Classification SparkR
- SparkR Dataframses
- R Machine learning algorithms Spark Streaming
- Understanding Dstreams
- Running Streaming examples Demo and Hands on
Q&A and conclusion

Pre-conference & Post Conference Workshops


X Workshop Abstract

Background
Business Analytics is a set of methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information. This is used to enable more effective strategic, tactical and operational insights that is focused on the analysis of data using statistics and provides necessary insights and prediction. It helps the users perform deep-dive understanding and provide descriptive, predictive and prescriptive analytics and drive decision-making.

Business Analytics is the growing area and not enough expertise. Companies are finding huge value in Business Analytics. It is used to run the business effectively and is instrumental in growing the business. Companies are ready to invest significant amount of money in setting up the business analytics platform either by using existing tools/package or building their own. The skills needed to use the business analytics platform effectively is not adequately available.

Expertise is needed at various levels to use the business analytics platform, perform business analytics, provide insights, reporting and driving data-driven decisions. While the work involved is challenging and interesting, the salary offered by many companies are very good. Organizations are searching for employees that have strong analytical and business skills. While this combination seems to be rare among today's professionals, yet is in incredibly high demand and because of which organizations are ready to pay the right salary for right talent.

Business Analytics include identifying KPIs, measurement strategy, data analysis, complex statistical model and analysis, data mining and deep understanding of cause-and-effect models. Business analytics can drive key decision making in the organization and help executive decision makers in building strategy, predictive analysis, forecasting, risk analysis, identify and prevent fraud, market analysis, etc.

What are Business Analytics?
By analytics we mean the extensive use of data, statistical and quantitative analysis, to understand the data and building explanatory and predictive models and fact-based management to drive decisions and actions. The analytics may be input for human decisions or may drive fully automated decisions.

Competing on analytics?
When companies in industries offer similar products and use comparable technology, high performance business processes are among the last remaining points of differentiation. Many of the previous bases for competition are no longer available. Unique geographical advantage doesn’t matter in global competition, and protective regulation is largely gone. Proprietary technologies are rapidly copied, and breakthrough innovation in products or services increasingly difficult to achieve. What’s left as a basis of competition is to execute your business with maximum efficiency and effectiveness, and to make the smartest business decisions possible. Thus, analytical competing is the mean to ensure business sustenance, and future-growth for organization. There are five stages of Analytic Competition that organizations practice, based on which the companies grow and make this as a competitive advantage by giving better value to the consumers, reducing cost and adding new avenues of revenues.

1. Analytically Impaired
2. Localized Analytics
3. Analytical Aspirations
4. Analytical Companies
5. Analytics Competitors

Business analytics enables organizations to accurately manage and react to changing situations around them, and bridge the gaps between information across the organizations. There are a number of benefits of using business analytics to organizations across their functions. Following are some of the benefits of business analytics:

- Improving the decision making process (quality & relevance)
- Speeding up of decision making process
- Promoting and fostering a culture of data & fact-based decision making and accountability
- Better alignment with strategy
- Realizing cost efficiency
- Responding to user needs for availability of data on timely basis
- Improving competitiveness
- Producing a single, unified view of enterprise information
- Synchronizing financial and operational strategy
- Increase revenues
- Sharing information with a wider audience

The next level of business analytics is to help people with drill-down capabilities to analyze data from multiple angle to find out more information which otherwise is difficult to think about and find. With that comes meaningful insights – to help people take business decisions.

Data Scientists use these skills are able to provide insights into discrete data sets, build complex model and present them in Scorecard format and use the same in executive reviews to lead data-driven discussion and decisions. Some of the impactful use of this is in the areas of Management Information Systems, Financial Service, Marketing Research, Process Improvements, Six Sigma, Process Excellence, Scorecard, Dashboard, End-to-End Product Management, etc.

The training is hands-on and provides opportunity to learn different types of Business Analytics approach, applications, etc. and help them to prepare for explaining and teaching others. Participants should not expect lot of theory, statistical formulas, models, etc., instead they will be shared some real-life data/problems or simulated data and will be working thru building the business Intelligence reports, scorecard and dashboard. Participants will learn data analysis and quantitative modeling skills to solve business problems and achieve better business performance. Additionally, they will gain knowledge of how to solve team-based, real-world business problems.

Course Outline

1. Background
a. Overview of Business Analytics
b. Competing on Analytics
c. Getting started with Business Analytics

2. Measurements & Data
a. Identifying Business Metrics and KPI
b. Sources of Data
c. Types of Data
d. Measurement Strategy
e. Measurement System Analysis
f. Data Gathering & Data Mining
g. Data Quality Management, Consistency and Integrity
h. Handling Large volume, variety and velocity of data (Big Data)

3. Tool
a. Working with Data in Excel
b. Getting Started with R Programming

4. Statistics Foundation
a. Statistical thinking and definition of statistics
b. Correlation and Correlation Coefficient – Linear Regression
c. Sampling and Sampling Methods
d. Measures of Central Tendency, Dispersion, Shape
e. Cause-effect Analysis
f. Regression Analytics
g. Hypothesis Testing

5. Analytics
a. Analytics vs Analysis
b. Descriptive Analytics
c. Predictive Analytics
d. Prescriptive Analytics
e. Machine Learning
f. Unstructured data collection and analysis

6. Visualization & Reporting
a. Telling Stories with Data
b. Building Scorecard
c. Creating Effective Dashboards
d. Using Excel for Data Visualization, Analytics and Reporting
e. Automated Monitoring, Threshold & Alerting

7. Business Analytics in Action
a. Hands-on group assignment
b. Analytics for Mobile Apps
c. Social Monitoring
d. Service Quality Monitoring
e. Human Resource Analytics
f. User Online Behavior Analytics
g. Retail Customer Analytics
h. Specific Examples of Business Analytics in Action from Microsoft, Reliance Jio and NICE

8. Conclusion
a. Starting with Business Analytics
b. Career Options
c. Success with Business Analytics

Speaker Profile

Mukesh Jain is Educationist, Author, Coach and Techno-Biz Leader with 21 yrs of experience working with legendary people like Bill Gates, Satya Nadella and Mukesh Ambani. He have built & led multiple Global Teams and delivered Analytics driven Innovative Products that used by Millions of people worldwide.

He have led R&D and built products like Outlook, OWA, Hotmail, Messenger, MSN, Bing, Advertising, Mobile Apps, e-commerce, Open Source Big data Analytics, Financial Analytics - Actimize, IoT, etc. in companies like Microsoft, Reliance Jio, NICE, ATOS, Syntel and Datamatics in USA, Japan, China & India.

He is Advisor to KJ Somaiya Engg College, Vanguard Business School, MGM Engg College, JSPM Engg College, Simplilearn & EduPristine. He helped build curriculum, conducted faculty development workshops and students training in the areas of Big Data, Business Analytics, Product Management, Software Engineering, Software Testing, Excel, Digital Marketing, Lean Management and Six Sigma.

He is the recipient of multiple awards, including Microsoft’s most prestigious “Gold Star” award 3 years in a row, Asia-Pacific Leadership Award, Management Excellence, Outstanding Mentor, Solution Excellence, Microsoft-Yahoo People Excellence Award, ASQ Quality Laureate, Quality of Service Award, QAI Agile Project Management Leadership Award, iSixSigma Best Six Sigma Black Belt, etc.

He is currently, the Vice President (R&D) & Head of NICE in Pune. He has setup NICE in Pune and is leading multiple R&D teams in areas of Machine Learning & Big Data based large scale Analytics Platform in Financial and Experience domains that are used by 85% of Fortune 100 companies. In Pune, he attracted and hired 380 engineers in a year and expend to 540 highliy capable R&D teams by 2016.

Prior to NICE, he was Vice President & Head at Reliance Jio (4G) for 2.5 yrs leading Advertising Business, Mobile Advertising RTB Platform, Social Media Analytics & Big Data Analytics Platform. He developed the strategy and built one of the largest Big Data Analytics Platform in India providing real-time dashboard, detailed scorecard, predictive & prescriptive analytics for all the Jio Mobile app data.

He worked at Microsoft for 13.5 years (mostly in USA) as R&D Engineering Director leading large global engineering teams. In 2011, he moved to India to setup Microsoft R&D center in Bangalore and provided strategic & technical leadership for Microsoft-Yahoo! Alliance leading engineering teams in Analytics & Advertising. He had honor of successfully leading and executing Microsoft’s 1st Six Sigma project in 2001. He created and led “Day-In-A-Life” program across Office. He built and rolled out Microsoft wide Business Analytics program (Business QoS), now used by all Microsoft Online Services.

He is a seasoned coach, mentor, author and speaker. He regularly speak at international conferences, business schools & engineering colleges (IITs, IIMs, BITS Pilani, NITs, …) on a variety of topics (Leadership, Personal Excellence, Agile, Product Engineering, DevOps, Smart Cities, Internet of Things (IoT), Big Data, Business Analytics, Cloud, Google Analytics, Social Media, Digital, Mobile, Design of Experiments (DoE), Experimentation, Digital Marketing, Advertising, Product Management, SEO, Project Management, Six Sigma & Lean). He have made presentations at international confernces like IEEE, WorldHRD, iSixSigma, PMI, SEPG, SPIN, QAI, NASSCOM, UNICOM, Agile, BZMedia, Better Software, IdeaBytes, etc.

He has done B.E. in Computer Science and Executive Managmeent program from IIT Bombay. Microsoft Certified Standards Professional, MCAS, MOS, Statistical Process Control, Licenced TSP Coach, PSP Engineer, Lean, Six Sigma Master Black Belt, CQIA, CSQA, CSTE, CQA, CTFL, MOF & ITIL

He is author of books “Delivering Successful Projects” and “Web Performance Improvement”. He is now writing books on “Effective Business Analytics for SoLoMo” and “Personal Excellence”.

He can be reached at http://www.linkedin.com/in/MukeshJainCoach, mdjain@hotmail.com


X Workshop Abstract

Agenda
Day 1

Big Data/Hadoop Introduction
What is Big Data and Data science
Introduction to Distributed computing and Hadoop
Hadoop Architecture – HDFS/MapReduce
Anatomy of a Hadoop cluster,
Hive - Architecture Demo, Hands on

Python ( Pre-req for Spark) - Introduction to Python
- Programming concepts
- Demo and Hands on Exercises Spark - Introduction to Spark
- Spark Installation
- Spark Architecture
- RDD's
- Lazy evaluation
- Transformations and Actions
- Sample programs
- Demo and Hands on
- Spark- SQL
- Datasets, DataFrames

Day 2

Recap of Day1 Spark ..contd
Loading data from different type of files
- Txt,Json,Parquet,CSV Spark -Hive integration Spark – MlLib
- Introduction to Machine learning
- MlLib Api's
- Statistical Modeling using API's
- K-Means Clustering
- Regression and Classification SparkR
- SparkR Dataframses
- R Machine learning algorithms Spark Streaming
- Understanding Dstreams
- Running Streaming examples Demo and Hands on
Q&A and conclusion


X Workshop Abstract

Round Table Discussion

Participants join a table to discuss one or more of the Conference themes - Each table has a "Topic Guru" to facilitate the discussion.


X Workshop Abstract

The art and science of making sense of data is a highly sought after skill in today’s data driven world.Data science isn’t just for data scientists. In massively connected data driven world, it is imperative that the workforce of today and tomorrow is able to understand what data is available and use scientific methods to analyze and interpret it. Data science is now recognized as a highly-critical growth area with impact across many sectors including science, government, finance, health care, telecom, manufacturing, advertising, retail, and others. Launch your data science career with this practical workshop. Build a solid foundation in machine learning using R and start exploring data-related careers.

TOP 9 REASONS TO ATTEND

- Understand the art and science of discovering patterns and making intelligent predictions from big data.

- Define machine learning, why it matters, and discuss its relationship to analytics, data science, and big data.

- Machine learning fundamentals, the importance of algorithms, and machine learning as a service.

- Basics of R platform, programming language concepts, common and useful R commands, and applying machine learning methods.

- Doing machine learning - Understanding the steps in the machine learning pipeline, from data acquisition and feature generation, to training and model selection.

- Practically learn the most commonly used machine learning methods, covering both supervised and unsupervised learning.

- Develop understanding of which algorithm to choose based on the analytics challenge and the data you have.

- Be able to appreciate the trade-offs involved in choosing particular techniques for particular problems.

- Discover how to understand, interpret and convey the results of data science life cycle.

AGENDA

The workshop has a strong focus on gaining hands-on experience implementing algorithms and building predictive models on real datasets. By the end of the 3 days, participants will be ready to implement the machine learning algorithms using data science on your own data, and immediately generate value.

The workshop will take participants through the conceptual and applied foundations of the subject. Topics covered include:

- R for Statistical Analysis and Machine Learning
- Machine learning theory, types of learning
- Techniques, models and methods
Labs are developed to practically learn how to use the R programming language and packages for applying the main concepts and techniques of data science and machine learning.

Day 1:

Data Science and Machine Learning – Context, Toolkit and Industry Practices

- A data-driven digital world, introduction to Data Science and component parts of Data Science
- Enterprise Big Data platform architectures, Hadoop ecosystem and Apache Spark
- Data Science Toolkit and Life Cycle – A strategy to approach data analytics problems
- Fundamentals of Machine Learning for Data Science
- R for Statistical Analysis and Machine Learning
- Basics of R Programming

Day 2:

R Programming and Applications of Machine Leaning Models
- Pre-processing and Machine Learning Workflow
- Guest Speaker slot
- Model Selection: Training, Validating and Testing
- Regression Models

Day 3:

Advanced Predictive Methods and Capstone Project
- Classification Models
- Ensemble Methods
- Capstone Project


X Workshop Abstract

Big enterprises around the world have found Hadoop to be a game changer in their Big Data management, and as more companies embrace this powerful technology the demand for Hadoop Developers is also growing. By learning how to harness the power of Hadoop 2.0 to manipulate, analyse and perform computations on Big Data, you will be paving the way for an enriching and financially rewarding career as an expert Hadoop developer.

Who can attend?

- Architects and developers who design, develop and maintain Hadoop-based solutions.
-Data Analysts, BI Analysts, BI Developers, SAS Developers and related profiles who analyze Big Data in Hadoop environment.
-Consultants who are actively involved in a Hadoop Project.
-Experienced Java software engineers who need to understand and develop Java Map Reduce applications for Hadoop 2.0.

Complete course outline:

Key Take aways:
From the course:

-Understand Big Data and the various types of data stored in Hadoop.
- Understand the fundamentals of MapReduce, Hadoop Distributed File System (HDFS), YARN, and how to write MapReduce code.
-Learn best practices and considerations for Hadoop development, debugging techniques and implementation of workflows and common algorithms.
-Learn how to leverage Hadoop frameworks like ApachePig™, ApacheHive™, Sqoop, Flume, Oozie and other projects from the Apache Hadoop Ecosystem.
-Understand optimal hardware configurations and network considerations for building out, maintaining and monitoring your Hadoop cluster.
-Learn advanced Hadoop API topics required for real-world data analysis.
-Understand the path to ROI with Hadoop.

From the workshop:

-High quality training from an industry expert
-24 hours of comprehensive training
-Earn 24 PDUs
-Course Completion Certificates
-50% interactive and hands-on training exercises using HDFS, Pig, Hive, HBase, key MapReduce components and features, and more.

Conference or Event Schedule


X Topic Abstract

This session will address how analytics has evolved as a differentiator for business decisions in enterprises across industries globally. This session will cover examples of successful application of analytics resulting in improving revenues, profits and customer experience.

Speaker Profile

Sandeep Devagiri heads the Data Science Practice at Brillio. He has over 9 years of experience in Analytics with significant exposure to CRM, Marketing Analytics, Business Modeling and Analysis for Consumer Banking, Insurance, Remittances, Retail, Media and Online Domains. He is a keen planner with track record of understanding business processes of client organizations, formulating business models and strategies aimed at enhancing processes and functions of the client organizations. Sandeep has hands on exposure in the conceptualization of processes and procedures as per established credit policies, risk culture and control environment guidelines for the Banking, Retail and Financial Services. He has built multiple real time analytical applications, by using not just traditional transactional /demographic databases but also unstructured data from paid and free data sources. Sandeep has done his MS in Medical Image Processing from University of Aberdeen, UK and his BE (Biomedical Engineering) from Osmania University, Hyderabad, India.


X Topic Abstract

Natural Language Generation is positioned as one of the next generation of disruptors in the data consumption space. Rather than have analysts interpret data, we remove the gatekeepers and use machine learning to summarise insights and convert them into textual narratives and stories.

Today, this technology is nascent, but very much a reality. Weather forecasts, financial research, stock market data, sales data, medical research -- all of these have seen applications of automated narratives. Recent research includes an experiment which showed that users sometimes preferred computer-generated weather forecasts to human-written ones, in part because the computer forecasts used more consistent terminology.

This talk shares some of the successful examples of natural language generation, techniques behind these, and how you can incorporate narratives into your data analysis.

Speaker Profile

Anand is CEO and co-founder of Gramener, a data science company. He leads a team of data enthusiasts with skills in analysis, design, programming and statistics. He studied at IIT Madras, IIM Bangalore and LBS, and worked at IBM, Infosys, Lehman Brothers and BCG. He and his team explore insights from data and communicate these as visual stories. These visual analyses and dashboards are built on the Gramener Visualisation Server -- Gramener's flagship product.


X Topic Abstract

Key data and architectural challenges in implementing Big Data and IoT Projects across industrie scuh as Retail, Healthcare, Agri and Industrial IoTsectors.

Speaker Profile

Marutish Varanasi is a Big Data and IoT professional with more than 20 years of work experience across industries such as Retail, Healthcare, Agri, Industrial IoT and Utilities.

Round Table Discussion

Participants join a table to discuss one or more of the Conference themes - Each table has a "Topic Guru" to facilitate the discussion.


X Topic Abstract

How to market to the millennium generation in today’s data driven world. The millennials are a hyper connected lot, more informed and extremely diverse. Equipped with the purchasing power, this lot is relentless in information consumption, and demands a personalized experience in every interaction. Being always connected and interacting on multiple channels, it’s imperative for organizations that serve them to be customer centric and deliver seamless customer experience across different channels.

Data Science and Advanced Machine learning techniques can be used to handle huge data volumes and provide real time, relevant and personalized content; to ensure that they keep coming back for more. Also, the need is to go beyond human driven hypothesis testing, towards optimized and self-learning systems which can track, collect, process and deliver enhanced customer experience at all times.

Speaker Profile

Akhilesh Ayer is the Head of the Research and Analytics (R&A) unit and the Head of Marketing at WNS. He is responsible for running WNS’ R&A business while enabling the analytics agenda in client organizations. He was part of the formative team that set up the Research practice at GE's Analytics Center of Excellence that later became Genpact Analytics. He led the growth of the practice by enabling global clients to solve their strategic priorities using R&A.

Akhilesh was previously the Chief Operating Officer for India of McGladrey Capital Markets, a leading mid-market M&A investment bank and was responsible for establishing its presence in India and advising companies on their M&A strategy and transactions.

He was also leading the analytics team supporting the firm's bankers globally. Prior to that, his stints include CRISIL Advisory (now Standard & Poor's) on their financial restructuring and analytics assignments for the energy and water sector; and a boutique European consulting firm overseeing the firm's consulting business.

In addition to running the R&A business, as the Head of Marketing, Akhilesh is responsible for driving the marketing strategy, enabling growth and managing the WNS brand. He also heads WNS DecisionPointTM, an industry leading thought leadership platform that provides deep insights into emerging themes based on rigorous data analysis and custom research studies.

Akhilesh is an Engineer who also holds a Masters in Business Administration.


X Topic Abstract

The latest advances in natural language understanding has created a massive paradigm shift in dealing with text related data problems. Deep learning has created a revolution in the NLU space and corporations are leveraging it in various ways. The technology barrier is significantly reduced with open source technologies that are easy to configure and use. Several open source tools are available in the machine learning domain for traditional natural language processing to deep learning. Helpful implementation tips will be provided along with evaluating the technologies and tools.

Speaker Profile

Dr. Nishant Chandra is a R&D Scientist in the office of Chief Data Scientist at AIG and leads the group in India. His primary responsibility is to develop natural language and machine learning models for the insurance industry. Prior to AIG, Dr. Chandra has worked in insurance, telecommunication, R&D, and technology companies in US and India. He developed and implemented natural language predictive models that are deployed in top banks and telecom companies resulting in $100M impacts across value chain. Dr. Chandra has five patents and several publications in international conferences. He has also been a reviewer and speaker for IEEE conferences. He received his Ph.D. from Mississippi State University. 12:30PM – 01:30PM


X Topic Abstract

Analytics and BI solutions have been a staple of Enterprise decision making and intelligence crunching capability for more than two decades. The current landscape of Digital transformation, with its accompanying disruptive opportunities and challenges, calls for a major shift towards 'Systems of Insight'. While intuitively, the shift sounds logical and evolutionary, the design and implementation approaches have radical differences. This talk will shed light on approach implications, new capability build needs at Organizational; strategic and tactical implementation differences. It will draw on key experiences and thought leadership work of the speaker in Digital Transformation initiatives with major Clients in BFSI, Telecom, Education and emerging tech Start Ups.

Speaker Profile

Ajit Paul brings an unique mix of business technology consulting and implementation experience, of 25 yrs, working with CXOs in India and global for Digital Transformation initiatives. These have been in the domains of Banking, Financial Services, Telecom and Retail sectors. He has been the recipient of the International Aegis Graham Bell award for innovation in Cloud Services, Panel member with World Economic Forum, Indian Army and State Bank of India. Academically, he is an Electronics Engineer with Advanced Management qualifications from MIT Sloan and Enterprise Architecture credentials.

Currently, Ajit functions as a Digital Transformation Advisor with Stanford SEED Program, IIM Bangalore, MNCs in Education and BFSI domains, Board member with Start-ups in Big Data Analytics, Healthcare and NGO sectors.


X Topic Abstract

Processing semantic web data using Hadoop is an ideal solution as it seems they are created for each other. In this paper, as an extension of an existing framework that deals with processing semantic web data using Hadoop tools, I propose indexing based solution for full text searching on literal value of objects.

Study Area : Semantic Web, Parallel computing, Query processing, IR

Keywords : Semantic web based on Hadoop, MapReduce and SPARQL, Semantic web index based full text search

Speaker Profile

CAREER OBJECTIVE:
To be associated with a progressive institute which will provide me a dynamic work sphere to demonstrate my skills.

EDUCATION QUALIFIACATION:
Ph.D (CSE ) from JNTU Kakinada , Andhra Pradesh in March ,2015 in Software Engineering .Thesis Title “An Efficient Risk analysis in Requirement Engineering using modified goal risk model” under guidance of Dr P V Kumar, Professor, CSE Department, Osmania University, Hyderabad (June 2010-March 2015).

M.Tech (CSE) from JNTU Hyderabad in Nov 2009 in First Class.

B.Tech (CSE) from Andhra University, Visakhapatnam, Andhra Pradesh May 1998 in First Class with distinction.

SSC and HSC from Bombay Board, Mumbai, Maharashtra in First Class

WORK EXPOSURE:
Having more than Sixteen years experience in teaching students from various Engineering Colleges.

Ratified by JNTU Hyderabad as Assoc Professor in CSE Department from Sri Indu College of Engineering and Technology, Hyderabad in 23 March 2010. Ratified by JNTU Hyderabad as Assoc Professor in CSE Department from TKR College of Engineering and Technology, Hyderabad in 26 June 2011.

Ratified by Osmania University as Assoc Professor in CSE Dept in May 4 2012.

Ratified by JNTUK as Assistant Professor in CSE Dept (Information available at www.jntuk.edu)

Chief Editor of International journal of Research in Computer Science (www.ijorcs.org) ISSN(online):2246-8265 ISSN (print):2249-8257 DOI:10.7815/ijorcs.2249-8265.

Editorial board member of International Journal of Computer and communication Engineering research (www.ijccer.org) ISSN(Online): 2321-4198 ISSN(Print) 2321-418X

Having more than 18 citations for Published Research Papers


X Topic Abstract

Traditional loans are based on banking history leaving a large segment of people ineligible. These however, represent a highly untapped segment representing large purchasing potential. How do you deem if someone is trustworthy when you have no information to base your decision on? This session will detail methods of evaluating people and extending loans irrespective through leveraging technology and data in today’s digital world

Speaker Profile

Driven by identifying patterns, deriving insights and problem solving, data science and Vanitha was a natural fit. She has been instrumental in Oxigen’s evolution to a data-driven organization backed by a decade of experience in gleaning actionable insight and scalable data science solutions. She and her team enable key business decisions through the solutions they develop. When they’re not working they are analysing random trivia usually over chai.


X Topic Abstract

For the media and entertainment industry, which relies heavily on audience analysis, the more the data available, the merrier. Take programmatic advertising, for instance. Thanks to big data, it has changed the face of online advertising. Today the process of media buying is automated and targeted at a specific audience and demographics. Unlike earlier, when the buying happened manually through human interaction and took time, media buyers today use RTB (real-time bidding) for online display, social media advertising, mobile and video campaigns.

In video on demand context, big data is helping the trail one leaves while switching channels, this valuable information helps broadcasters identify audience preferences, thereby allowing for relevant content. It is no wonder then that broadcasters are developing ways to leverage big data to understand and connect with audiences.

Speaker Profile

Won the Entrepreneur of the year 2013 by TiE.

He is responsible to design, plan, strategies, identify new possibilities and opportunities, drive the relationships for Zenga TV as the MD & CTO. See possible opportunities for alliance.

Specialties: Great connection, Age on my side, with god's grace have had great success already, was the youngest CTO of Asia Pac at the age of 21.

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

S Anand

CEO & Co - Founder

Gramener

Dr. Nishant Chandra

Chief Data Scientist

AIG

Renny I John

Global Delivery Leader

IBM

Marutish Varanasi

Head Big Data Analytics & Data Sciences

Marvelogic Consultancy Services

Ajit Paul

Digital Advisor

Stanford Institute for Innovation in Developing Economies (SEED)

Soumen De

EGM, Operational Excellence

General Motors

Sandeep Devagiri

Head, Data science

Brillio

Dr Venkatesh Sharma

Assistant Professor

University of Ethiopia

Shabir Momin

MD & CTO

ZengaTV.com

Vanitha Vivian D’silva

Head-Data Science and Analytics

Oxigen Services India Pvt Ltd

Akhilesh Ayer

Head of Research and Analytics

WNS

Analytics & Big Data Olympiad 2017

Analytics & Big Data Olympiad is an initiative of India Analytics and Big Data Summit 2016 and UNICOM to run India's most prestigious Corporate Quiz on Analytics.

Event & Workshop Price list (07th to 10th)

Conference
(09th 0r 10th)

Super Early Bird : Rs 4,999
(Till 09th December 2016)
Early Bird : Rs 6,999
(Till 09th January 2017)
Standard : Rs 8,999
(Till 09th February 2017)

Conference
(09th & 10th)

Super Early Bird : Rs 8,999
(Till 09th December 2016)
Early Bird : Rs 12,999
(Till 09th January 2017)
Standard : Rs 14,999
(Till 09th February 2017)

Business Analytics in Action - 2 Days Workshop
(07th - 08th)

Standard : Rs 20,000
(Till 07th February 2017)

Big Data Analytics Using Spark - 2 Days Workshop
(09th - 10th)

Standard : Rs 15,999
(Till 09th February 2017)

Machine Learning With Big Data - 3 Days Workshop
(13th - 15th)

Standard : Rs 23,999
(Till 13th February 2017)

Big Data & Hadoop Developer - 3 Days Workshop
(16th - 18th)

Standard : Rs 23,999
(Till 16th February 2017)

Event FAQS

India Analytics and Big Data Summit in Bangalore is open to anyone who has an interest in Big Data & Analytics or any related field.

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

As this is predominantly an event for the IT Industry and Open Source Community, 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 asking to block the seats.

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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 : +91-8042023134

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Disclaimer and Indemnity

"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."