Joy Chakraborty


Joy is a Distributed System Architect, 17+ yrs of Application Software development experience, 10+ yrs of .NET and C# development experience, 5+ yrs of work experience in ASP .NET web application scaling and performance improvement, 4+ yrs of WCF experience with a special interest in distributed/parallel computing, currently working on Cloud, Big Data and Machine Learning technologies for last 4+ years. Also, he is actively part of various Software architectural organization and active open source contributor on big-data projects.

Practical Machine Learning using Apache Spark and Big-Data

Saturday, February 25th, 2017 at 11:30 am

Machine learning based intelligent, predictive and smart systems are now part of every application domain and provide a major competitive advantage for many organizations. This session will introduce the Machine Learning in the field of software engineering and discuss various aspects of machine learning driven application development. I will cover the basics of supervised and unsupervised machine learning along with discussing its practical usage in the software industry. I will also introduce and use Apache Spark as distributed processing framework and it’s machine learning library (MLlib) to design and develop a practical application using machine learning algorithms during this session. Apache Spark is a big-data computing framework which is essential for any industry scale machine learning application that manages big data. No prior knowledge of machine learning or Apache Spark is required to attend this session.

Designing and Architecting Distributed Analytics and Data Science applications using Microsoft’s Azure/Big-Data Technologies

Saturday, October 22nd, 2016 at 1:30 pm

Taking a tour of Microsoft Azure based Big-Data platform (one of the most promising technology in the industry at least for next few years) that unlocks the potential of creating new types of business applications that was not possible before. This session will take a look into the new features of Azure/HDInsight (which supports Hadoop, Spark, Hive, HBase and many other big-data technologies that runs on top of cloud based virtualized infrastructure), discuss the possible design scenarios in support of writing cross domain data analytics applications and finally writing few (more than one) different real world applications. Most of these technologies are portable and run in all major technological platforms (i.e. beyond Microsoft platform) seamlessly. I will also walk you through the Azure based Machine Learning Studio and Microsoft Cognitive Services to design and architect Data Science applications. You don’t need to be familiar with it to attend this session.

Designing and Architecting Distributed Data Platform using Microsoft’s BigData Technologies

Saturday, April 9th, 2016 at 11:30 am

Taking a tour of designing production scale Data Science Platform using Azure Cloud based Microsoft big-data and Machine-learning technologies. This session will present the industry’s best practices and patterns (with real-life examples) in designing and developing scalable and fault tolerant data platform. We will discuss multiple design choices (options) and the rationale behind choosing one over the others. I will also provide a high-level overview of current state (which has changed a lot since last code-camp) of various big-data technologies such as Hadoop, Spark, HBase, Hive running on top of Azure along with web based Machine Learning Studio running in Azure to design and architect Data Science applications. You don’t need to be familiar with it to attend this session.

Doing Data Analytics and Data Science using Microsoft’s BigData Platform

Saturday, October 10th, 2015 at 3:00 pm

Introducing the new capabilities of Microsoft technology based BigData platform (one of the most promising technology in the industry at least for next few years) that unlocks the potential of creating new types of business applications that was not possible before. This session will take a look into the new features of HDInsight (which supports Hadoop, Spark, Hive, Mahout, Storm, HBase and many other big-data technologies that runs on top of cloud based virtualized infrastructure), discuss the possible design scenarios in support of writing cross domain data analytics applications and finally writing few (more than one) different real world applications. Most of these technologies are portable and run in all major technological platforms (i.e. beyond Microsoft platform) seamlessly. You don’t need to be familiar with it to attend this session. It will give you a broad overview of these technologies and how they are rapidly changing the business needs in the market and computing industry that you might use directly or indirectly in near future.

Designing Data Analytics using Microsoft Cloud based BigData Solution – Zoom in Azure HDInsight

Saturday, March 21st, 2015 at 10:00 am

Learn the capabilities of Microsoft Cloud based BigData platform (a.k.a. Azure HDInsight) and various design choices that it provides, which can unlock the potential of creating new types of business applications that was not possible before. This session will take a deeper dive into Azure HDInsight (which supports Hadoop, Spark, Hive, Mahout, Storm, HBase and many other big-data technologies that runs on top of cloud based virtualized infrastructure), discuss the possible design scenarios in support of writing cross domain data analytics applications and finally writing few (more than one) different real world applications. Most of these technologies are portable and run in all major technological platforms (i.e. beyond Microsoft platform) seamlessly. Even if you are not familiar with cloud or big-data technologies and you don’t work on it, it will give you an high-level overview of these technologies and how they are rapidly changing the business needs in the market and computing industry that you might use directly or indirectly in near future.

Introduction to BigData and Hadoop in Microsoft platform

Sunday, June 22nd, 2014 at 2:00 pm

Learn about how to take advantage of Hadoop big data solution in Microsoft platform in solving problems that deals with massive amount of data and practically impossible to solve using traditional data processing and storage architecture. We will introduce the big data technologies and its related architecture that is applicable in all modern technological platforms (e.g. Microsoft and beyond). Then we will try to solve some real world big data problem using Hadoop from .Net environment. These techniques can be applicable to any other language in any other platform.

Architecting applications using Azure Service Bus

Saturday, November 23rd, 2013 at 11:30 am

Windows Azure Service Bus provides a hosted, secure, and widely available infrastructure for widespread communication, large-scale event distribution, naming, and service publishing. Developing medium-to-large scale enterprise system needs serious attention and consideration of Scalability, Security, Availability, Reliability, etc. quality attributes. In this session, I will walk through how to architect an enterprise level system using Azure Service Bus infrastructure that can address the quality attribute requirements such as scalability, security, availability, etc. We will also discuss what Azure Service Bus offers and how you can perform tradeoff in choosing between different elements in Azure Service Bus. For the demos, I will be using C# and WCF to use Azure Service Bus infrastructure but you don’t need to have prior WCF experience for attending this presentation.