Make a submission

Accepting submissions till 15 Jun 2019, 01:00 PM

NIMHANS Convention Centre, Bengaluru

The eighth edition of The Fifth Elephant will be held in Bangalore on 25 and 26 July. A thousand data scientists, ML engineers, data engineers and analysts will gather at the NIMHANS Convention Centre in Bangalore to discuss:

  1. Model management, including data cleaning, instrumentation and productionizing data science.
  2. Bad data and case studies of failure in building data products.
  3. Identifying and handling fraud + data security at scale
  4. Applications of data science in agriculture, media and marketing, supply chain, geo-location, SaaS and e-commerce.
  5. Feature engineering and ML platforms.
  6. What it takes to create data-driven cultures in organizations of different scales.

Highlights:

1. Meet Peter Wang, co-founder of Anaconda Inc, and learn about why data privacy is the first step towards robust data management; the journey of building Anaconda; and Anaconda in enterprise.
2. Talk to the Fulfillment and Supply Group (FSG) team from Flipkart, and learn about their work with platform engineering where ground truths are the source of data.
3. Attend tutorials on Deep Learning with RedisAI; TransmorgifyAI, Salesforce’s open source AutoML.
4. Discuss interesting problems to solve with data science in agriculture, SaaS perspective on multi-tenancy in Machine Learning (with the Freshworks team), bias in intent classification and recommendations.
5. Meet data science, data engineering and product teams from sponsoring companies to understand how they are handling data and leveraging intelligence from data to solve interesting problems.

Why you should attend?

  1. Network with peers and practitioners from the data ecosystem
  2. Share approaches to solving expensive problems such as cleanliness of training data, model management and versioning data
  3. Demo your ideas in the demo session
  4. Join Birds of Feather (BOF) sessions to have productive discussions on focussed topics. Or, start your own Birds of Feather (BOF) session.

Full schedule published here: https://hasgeek.com/fifthelephant/2019/schedule

Contact details:

For more information about The Fifth Elephant, sponsorships, or any other information call +91-7676332020 or email info@hasgeek.com

Sponsors:

Sponsorship Deck.
Email sales@hasgeek.com for bulk ticket purchases, and sponsoring 2019 edition of JSFoo:VueDay.

JSFoo:VueDay 2019 sponsors:

Platinum Sponsor

Anatta

Community Sponsors

Salesforce Ericsson freshworks
databricks

Exhibition Sponsors

Sapient Atlassian GO-JEK
Bayer

Bronze Sponsor

Sumologic Walmart Labs Atlan
Simpl Great Learning

Community Sponsors

Elastic Anaconda Aruba Networks

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

Namit Mahuvakar

@nomnom

Analysing high throughput Data in Real Time

Submitted Jun 15, 2019

Analysing high throughput Data in Real Time

Namit Mahuvakar
Data Engineering at Hotstar

At Hotstar, India’s largest premium streaming and entertainment platform, we generate more than 15 Billion clickstream events per day. This data is generated from multiple sources and by multiple teams. We built Bifrost, our internal Data Management Platform, as a single platform that allows users to ingest data of any kind & shape, and allow users to query the streaming and stationary data with ease. The data ingestion API abstracts the underlying complexities of producing, consuming, and processing data. It is built to be highly available, durable and resilient since this is the single entry point for all data coming into Hotstar

Kafka is the backbone of our real-time data platform, data is ingested through the in-house fault tolerant solutions around the ingestion API layer which is written entirely in Go to reliably ingest TBs of validated data each day at a peak of a Million messages per second.
In this presentation we will discuss the promises and use of Stream processing over Kafka Streams leveraging KSQL to analyse the ingested events to solve certain real-time use cases such as Playback Failure Rate which is a fundamental metric for over the top media streaming platforms.

Outline

  • Introduction
  • About Hotstar
  • Stream Processing @Hotstar
    • What is Stream Processing and Why was it required
    • Problems that lead to usage
      • Video Player Metricing
      • Social Signals
      • User Targeting
  • Case Study - Video Player Metrics
    • What are the P1 metrics
    • How did we solve and compute them real time
  • Case Study - Social Signals
    • What are the Social Signals
    • How did we solve engagement in real time
  • Key Take Away Discussion
    • Why and when should we use Stream processing
  • Q&A

Requirements

Basic Knowledge on -
* Kafka
* Stream Processing
* HDFS
* SQL

Speaker bio

Currently, Data Engineering at Hotstar. Previously at WebEngage and co-founder at CareODrive. Interested in spreading/sharing knowledge and in solving problems at a scale that matters. Previously held talks at Golang Meet-Ups, Bangalore, India and the 21CF Global Data Summit. Big fan of Radiohead, hit me up for a jam session any time.

Links

  • Lecturer/Organizer -
    • Hack.Me (Open Source Development Workshops) -Hands on session upon building setting up a particular code base of choice, and ways to start contributing to the current open-source world be it GNOME, KDE, Firefox, etc.
    • 21CF Data Summit 2018 - Data Ingestion at Scale Previous
  • *Golang meetup in Bangalore,India : https://www.youtube.com/watch?v=OKl6MnJkrDc

Slides

https://docs.google.com/presentation/d/1LDjmMYOCFZckDvIZuioVkvVeHE0ORC2iv4tbPhVhXm0/edit?usp=sharing

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Make a submission

Accepting submissions till 15 Jun 2019, 01:00 PM

NIMHANS Convention Centre, Bengaluru

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