Submit a talk on data

Submit a talk on data

Submit talks on data engineering, data science, machine learning, big data and analytics through the year – 2019

##This space is open for submitting proposals on data engineering, data science, machine learning, big data and analytics through the year in 2019.

We will host data events round the year, in 2019. Talks for these conferences will be selected from here. Submit a proposal any time.

##Should you have queries, write to us on fifthelephant.editorial@hasgeek.com or call us on 7676332020

Hosted by

The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more

Chandulal Kavar

@chandukavar

From Application Developer to Big Data Engineer

Submitted Mar 13, 2018

In this talk, I will talk about my journey from working as an App Dev to a Data Engineer at ThoughtWorks. This transition helped me to change my mindset around Big Data as well as problem-solving techniques required for distributed computing problems. I will also cover how one API over other will affect the performance and memory usage. Furthermore, I will show some of these techniques through some examples.

Outline

  1. What people do when they start exploring Big Data?
  2. Why people quit?
  3. Mindset Change
    • Silo Computing vs Distributed Computing
    • Log vs Logging
    • Data quality in Big Data
  4. Problem Solving Techniques for Distributed computing problems
  5. Choosing one API over Other
  6. How to introduce new Big Data tool or framework

Speaker bio

I am a Data Engineer at Thoughtworks, designing and building data-intensive and scalable Data Platforms. I love to solve the problems that run on Big Data processing frameworks. I am a blogger too, you can find my blogs on medium @chandukavar

Slides

https://www.slideshare.net/secret/4SBoUnrZXY45qI

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Hosted by

The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more