Vivek Aanand Ganesan

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Profile: I am currently serving as Chief Technology Advisor to Innovaccer Inc., a leading data science and data anaytics company. I work on bulding data science applications at Innovaccer. I am privileged to be working with some of the best minds in the data science industry and be a part of Innovaccer's exciting growth. I I am an experienced big data architect and data scientist with proven expertise in building scalable big data solutions and high performance analytics systems. I also guide product development for data shop, Innovaccer's game-changing big data analytics platform. In my previous roles, I have done data architecture, performance improvement, and analytics implementa...

mongodb bigdata collaborative filtering recommendation engines big data data engineering hadoop data pipeline pipeline nosql recommendation engine hackathon bigdatagods tutorical mongodb tutorial program kickoff

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Vivek Aanand Ganesan

Présentations

Introduction to Data Engineering

Recommendation Engines Program Kickoff

Mongodb hackathon 01

Collaborative filtering getting_started

Mongodb hackathon 02

Collaborative filtering common_problems_and_solutions

Big data pipelines

J’aime

Building Large-Scale Stream Infrastructures Across Multiple Data Centers with Apache Kafka

Kinesis vs-kafka-and-kafka-deep-dive

How to Become a Thought Leader in Your Niche

Feature Engineering

Credit Suisse: Multi-Domain Enterprise Reference Data

Best Practices for Building a Data Lake with Amazon S3 - August 2016 Monthly Webinar Series

AWS March 2016 Webinar Series Building Your Data Lake on AWS

October 2014 Webinar: Cybersecurity Threat Detection

Building Micro-Services with Scala

Microservices in Scala: Spray

Lambda Architecture with Spark Streaming, Kafka, Cassandra, Akka, Scala

Analysis of ‘Unstructured’ Data

ApacheCon NA 2015 Spark / Solr Integration

Developing Real-Time Data Pipelines with Apache Kafka

Introduction to the graph technologies landscape

Big Data Analytics with Scala at SCALA.IO 2013

How to start with cross-sell analysis