Date

January 20 - 21, 2017

Location

Pune

Capacity

100 Tickets

Speakers

8+ Professional Speakers

About the event

India Analytics and Big data Summit 2017 is coming to Pune for two days on Jan 20 - 21, 2017, allowing excellent networking opportunities 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.

We explore how data analytics impacts businesses, also considering its connections with predictive analytics and the new area of real-time analytics. There are also interactive panels for attendees to engage with the presenters and bring their issues to the panellists.

We cover the topics that matter most to today’s big data & analytics leaders along with creativity-enhancing inspiration & innovative action points and takeaways.

Technology Olympiad 2017

Technology Olympiad 2017 is an initiative of India Analytics, IOT & Big Data Summit 2017 and UNICOM to run India's most prestigious Corporate Quiz on Technology and IoT.

Pre-conference Workshop

Business Analytics in Action - 2 Days Workshop (18 - 19 January, 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 - 3 Days Workshop (17 - 19 January, 2017)


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

Coming Soon....

Pre-conference Workshop


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

Coming Soon....

Conference or Event Schedule


X Topic Abstract

Opportunities & Challenges of Big Data Analytics in Renewable Energy

1. Renewable energy sources viz. Wind & solar power are transforming the energy landscape in India. With the government plan of installing 100 GW of Solar Power & 60GW of wind power by 2022, the need to identify the methodology to maximise the wind/solar farms generation, optimise the operations and enable integration to the grid becomes extremely relevant.

2. Further, the investors look forward to achieve the IRR (Internal Rate of Return), based on which their complete investments have been planned and financial & risk calculations done for the 20-25 years of assets life. Any reduction in power output/energy feeding into the grid results in lowering of their EBITDA, which is not acceptable to them.

3. Big Data analytics can play a crucial role in achieving this objective, as the sensors installed in wind turbines/solar panels generates huge amount of data, which can be analysed in real/near real time to give the desired operational performance parameters. Analytical models enable wind/solar energy companies to gain deeper insights into the variable nature of wind and solar, and more accurately forecast the amount of energy that can be redirected into the power grid or stored.

4. Big data analytics mainly falls into three categories viz. power forecasting, condition based monitoring/predictive maintenance, overall wind/solar farm performance & reliability analysis. SCADA based sensor data from wind/solar parks, transactional ERP systems and metering data at pooling stations forms the main source of data for these applications. However, end-to-end analytics presents several challenges, such as high rate data provided by sensors, heterogeneity of the data collected, multiple database systems, varying level of automation at power plant level, need to integrate systems to obtain 360 degree view of wind/solar farm assets and remote locations of these assets.

5. With the development of big data technologies in the field of data storage & retrieval, real time processing, analytical modelling and visualisation, there is an immense scope to provide value to the developers, generators, utilities & end users.

Speaker Profile

Vinay Gupta is Heading the Data Analytics & Business Excellence Division of Suzlon Energy Limited. His focus areas include Wind farm Operational Analytics, M2M analytics, Real time assets monitoring, Predictive Modelling, and IoT Networks.

Prior to this appointment, he was in Wind World India Limited (earlier Enercon India Limited) in the similar role of Head Analytics & Operational Excellence. He had initiated and successfully implemented various analytical & digital transformational initiatives to optimise the wind farm performance.

Earlier, as Colonel in Army, he had played a pivotal role in establishing the first Centre for Data Analytics in Indian Army, developing analytics driven Military Equipment Management system and deploying real time video surveillance of border areas in North East sector. Five innovations by him in Military Technical operations and supply chain were featured in ‘Compendium of Best Practices’ published by Indian Army.


X Topic Abstract

1. What is data analytics
2. Types of data analysis
3. Process of data analysis
4. Open source tools for data analysis
5. Use cases of these tools

Speaker Profile

Ghanasham Lavand has 12 years of experience as a Software Engineer and Entrepreneur. He is building a product recommendation system using Data Analytics and Artificial Intelligence. Previously he has worked on large scale systems in the U.S. at Walmart, HP and Morgan Stanley. He closely follow technology trends and startups. He enjoys running and watching movies.


X Topic Abstract

This talk focuses on how machine learning techniques can be fruitfully applied to various problems in financial services industry. Applications of churn modeling, clustering as well as recommender systems as applied to various problems in retail broking will be discussed. If time permits we will also touch upon use of machine learning for financial markets prediction, which is a base for some highly successful global quant funds

Speaker Profile

Dr Aniruddha Pant has been head of data analytics and strategic quantitative activities in large and medium sized organizations. He has worked extensively in data analytics and machine learning as applied to Banking, Financial Services and Insurance. Overall experience of 20+ years in application of advanced mathematical techniques to various academic and enterprise problems. 12+ years of experience in building and leading medium sized group specializing in high-end quantitative analysis work.

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

We have done extensive work on using both Druid and Apache HAWQ for complex computations required in certain big data analytics use cases. We present an overview of the complex computations, an overview of both Druid and Apache HAWQ and the data partitioning strategies for both systems. We also discuss comprehensive benchmark results comparing the pros and cons of using both platforms.

Speaker Profile

Dr. Vijay Srinivas Agneeswaran has a Bachelor’s degree in Computer Science & Engineering from SVCE, Madras University (1998), an MS (By Research) from IIT Madras in 2001, a PhD from IIT Madras (2008) and a post-doctoral research fellowship in the LSIR Labs, Swiss Federal Institute of Technology, Lausanne (EPFL). He has joined as Director of Technology in the data sciences team of SapientNitro. He has spent the last ten years creating intellectual property and building products in the big data area in Oracle, Cognizant and Impetus. He has built PMML support into Spark/Storm and realized several machine learning algorithms such as LDA, Random Forests over Spark. He led a team that designed and implemented a big data governance product for a role-based fine-grained access control inside of Hadoop YARN. He and his team have also built the first distributed deep learning framework on Spark. He is a professional member of the ACM and the IEEE (Senior) for the last 10+ years. He has four full US patents and has published in leading journals and conferences, including IEEE transactions. His research interests include distributed systems, data sciences as well as Big-Data and other emerging technologies. He has been an invited speaker in several national and International conferences such as O'Reilly's Strata Big-data conference series. He lives in Bangalore with his wife, son and daughter and enjoys researching history and philosophy of Egypt, Babylonia, Greece and India.

Analytics and Big Data - Part 1 - Click Here for More Info

It will help participants to develop a sense of understanding on life cycle of analytics project and few big data concepts. Also, you will be demonstrated configuration of virtual box and setting up single node cluster.

Topics Covered
What is Big Data & Why Hadoop?
Big Data Characteristics, Challenges with traditional system


X Trainer Profile

PROFESSIONAL SUMMARY
Technology Architect having 12 yrs of in-depth technical experience in managing, analyzing Small, Medium & Large databases. Expertise in design and providing architect solution for various business applications related to Bigdata, data warehouse, data analysis, data integration, data cleansing and data profiling on heterogeneous databases like MS SQL, Oracle, Vertica and Hadoop. Involved in DB operations & support projects, database applications, data Integration, design and development of data visualization solutions, automated testing, web applications (C# .Net), web services and Unix scripting. Groomed more than 200+ associates in Bigdata technology & tools by conducting trainings. Extensive work exposure as solution architect and data analyst in Investment banking domain on various applications involved in Anti-Money Laundering (FCCM), Portfolio and Order management (Charles River), Instruments and Securities Management (PRIDE). Present role involves providing Architecture solution for Bigdata in Anti-Money Laundering domain using Hortonworks platform.

Analytics and Big Data - Part 2 - Click Here for More Info

Topics Covered
Hadoop Overview &it’s Ecosystem
Anatomy of Hadoop Cluster, Installing and Configuring Hadoop Hands-On Exercise
HDFS – Hadoop Distributed File System Name Nodes and Data Nodes
Hands-On Exercise Map Reduce Anatomy
How Map Reduce Works?
The Mapper & Reducer
Input Formats & Output Formats
Data Type & Customer Writable


X Trainer Profile

PROFESSIONAL SUMMARY
Technology Architect having 12 yrs of in-depth technical experience in managing, analyzing Small, Medium & Large databases. Expertise in design and providing architect solution for various business applications related to Bigdata, data warehouse, data analysis, data integration, data cleansing and data profiling on heterogeneous databases like MS SQL, Oracle, Vertica and Hadoop. Involved in DB operations & support projects, database applications, data Integration, design and development of data visualization solutions, automated testing, web applications (C# .Net), web services and Unix scripting. Groomed more than 200+ associates in Bigdata technology & tools by conducting trainings. Extensive work exposure as solution architect and data analyst in Investment banking domain on various applications involved in Anti-Money Laundering (FCCM), Portfolio and Order management (Charles River), Instruments and Securities Management (PRIDE). Present role involves providing Architecture solution for Bigdata in Anti-Money Laundering domain using Hortonworks platform.


X Trainer Profile

PROFESSIONAL SUMMARY
Technology Architect having 12 yrs of in-depth technical experience in managing, analyzing Small, Medium & Large databases. Expertise in design and providing architect solution for various business applications related to Bigdata, data warehouse, data analysis, data integration, data cleansing and data profiling on heterogeneous databases like MS SQL, Oracle, Vertica and Hadoop. Involved in DB operations & support projects, database applications, data Integration, design and development of data visualization solutions, automated testing, web applications (C# .Net), web services and Unix scripting. Groomed more than 200+ associates in Bigdata technology & tools by conducting trainings. Extensive work exposure as solution architect and data analyst in Investment banking domain on various applications involved in Anti-Money Laundering (FCCM), Portfolio and Order management (Charles River), Instruments and Securities Management (PRIDE). Present role involves providing Architecture solution for Bigdata in Anti-Money Laundering domain using Hortonworks platform.


X Trainer Profile

PROFESSIONAL SUMMARY
Technology Architect having 12 yrs of in-depth technical experience in managing, analyzing Small, Medium & Large databases. Expertise in design and providing architect solution for various business applications related to Bigdata, data warehouse, data analysis, data integration, data cleansing and data profiling on heterogeneous databases like MS SQL, Oracle, Vertica and Hadoop. Involved in DB operations & support projects, database applications, data Integration, design and development of data visualization solutions, automated testing, web applications (C# .Net), web services and Unix scripting. Groomed more than 200+ associates in Bigdata technology & tools by conducting trainings. Extensive work exposure as solution architect and data analyst in Investment banking domain on various applications involved in Anti-Money Laundering (FCCM), Portfolio and Order management (Charles River), Instruments and Securities Management (PRIDE). Present role involves providing Architecture solution for Bigdata in Anti-Money Laundering domain using Hortonworks platform.

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

Atul Bengeri

Regional Manager - Strategic Projects & Smart Cities

Dell-EMC

Aniruddha Pant

Founder and CEO

AlgoAnalytics Financial Consultancy Pvt Ltd

Vinay Gupta

Head Data Analytics & Business Excellence

Suzlon Group

Vijay Srinivas Agneeswaran

Director of Technology

SapientNitro

Atul Khot

VP Engineering for Emerging Technologies

Webonise Lab

Ghanasham Lavand

Founder

lecapro.com

Event & Workshop Price list (18th - 21st)

Conference
(20th or 21st)

Super Early Bird : Rs 4,999
(Till 20th November 2016)
Early Bird : Rs 6,999
(Till 25th December 2016)
Standard : Rs 8,999
(Till 20th January 2017)

Conference
(20th & 21st)

Super Early Bird : Rs 8,999
(Till 20th November 2016)
Early Bird : Rs 12,999
(Till 25th December 2016)
Standard : Rs 14,999
(Till 20th January 2017)

Business Analytics in Action - 2 Days Workshop
(18th & 19th)

Standard : Rs 20,000
(Till 18th January 2017)

Big Data Analytics Workshop
(17 - 19 January)

Standard : Rs 25,000
(Till 17th January 2017)

Event FAQS

India Analytics and Big Data Summit in Pune is open to anyone who has an interest in Big Data & Analytics 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 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 block the seats.

Name
Email ID
Designation
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Company name

Event Location

Royal Orchid Central
Kalyani Nagar,
Marisoft Annexe Building,
Pune, Maharashtra 411014
Phone: 020 4000 3000

contact@unicomlearning.com

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Contact Us

Unicom Address

A.V.Bureaux,
2nd Floor, #99/A,
Green Glen Layout,
Bellandur,
Bangalore – 560103 ,
Karnataka, India.
Phone : +91-8042023134

contact@unicomlearning.com

Get Direction

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."