The Fifth Elephant 2017

On data engineering and application of ML in diverse domains

##Theme and format
The Fifth Elephant 2017 is a four-track conference on:

  1. Data engineering – building pipelines and platforms; exposure to latest open source tools for data mining and real-time analytics.
  2. Application of Machine Learning (ML) in diverse domains such as IOT, payments, e-commerce, education, ecology, government, agriculture, computational biology, social network analysis and emerging markets.
  3. Hands-on tutorials on data mining tools, and ML platforms and techniques.
  4. Off-the-record (OTR) sessions on privacy issues concerning data; building data pipelines; failure stories in ML; interesting problems to solve with data science; and other relevant topics.

The Fifth Elephant is a conference for practitioners, by practitioners.

Talk submissions are now closed.

You must submit the following details along with your proposal, or within 10 days of submission:

  1. Draft slides, mind map or a textual description detailing the structure and content of your talk.
  2. Link to a self-record, two-minute preview video, where you explain what your talk is about, and the key takeaways for participants. This preview video helps conference editors understand the lucidity of your thoughts and how invested you are in presenting insights beyond your use case. Please note that the preview video should be submitted irrespective of whether you have spoken at past editions of The Fifth Elephant.
  3. If you submit a workshop proposal, you must specify the target audience for your workshop; duration; number of participants you can accommodate; pre-requisites for the workshop; link to GitHub repositories and documents showing the full workshop plan.

##About the conference
This year is the sixth edition of The Fifth Elephant. The conference is a renowned gathering of data scientists, programmers, analysts, researchers, and technologists working in the areas of data mining, analytics, machine learning and deep learning from different domains.

We invite proposals for the following sessions, with a clear focus on the big picture and insights that participants can apply in their work:

  • Full-length, 40-minute talks.
  • Crisp, 15-minute talks.
  • Sponsored sessions, of 15 minutes and 40 minutes duration (limited slots available; subject to editorial scrutiny and approval).
  • Hands-on tutorials and workshop sessions of 3-hour and 6-hour duration where participants follow instructors on their laptops.
  • Off-the-record (OTR) sessions of 60-90 minutes duration.

##Selection Process

  1. Proposals will be filtered and shortlisted by an Editorial Panel.
  2. Proposers, editors and community members must respond to comments as openly as possible so that the selection processs is transparent.
  3. Proposers are also encouraged to vote and comment on other proposals submitted here.

Selection Process Flowchart

We will notify you if we move your proposal to the next round or reject it. A speaker is NOT confirmed for a slot unless we explicitly mention so in an email or over any other medium of communication.

Selected speakers must participate in one or two rounds of rehearsals before the conference. This is mandatory and helps you to prepare well for the conference.

There is only one speaker per session. Entry is free for selected speakers.

##Travel grants
Partial or full grants, covering travel and accomodation are made available to speakers delivering full sessions (40 minutes) and workshops. Grants are limited, and are given in the order of preference to students, women, persons of non-binary genders, and speakers from Asia and Africa.

##Commitment to Open Source
We believe in open source as the binding force of our community. If you are describing a codebase for developers to work with, we’d like for it to be available under a permissive open source licence. If your software is commercially licensed or available under a combination of commercial and restrictive open source licences (such as the various forms of the GPL), you should consider picking up a sponsorship. We recognise that there are valid reasons for commercial licensing, but ask that you support the conference in return for giving you an audience. Your session will be marked on the schedule as a “sponsored session”.

##Important Dates:

  • Deadline for submitting proposals: June 10
  • First draft of the coference schedule: June 20
  • Tutorial and workshop announcements: June 20
  • Final conference schedule: July 5
  • Conference dates: 27-28 July

For more information about speaking proposals, tickets and sponsorships, contact or call +91-7676332020.

Hosted by

All about data science and machine learning

Regunath Balasubramanian


Scalability truths and serverless architectures - why it is harder with stateful, data-driven systems

Submitted May 22, 2017

Building scalable systems is not easy. It is not as simple as deploying on a cloud and expecting it to scale alongwith the cloud’s elasticity. Many systems and solutions that claim elasticity of scale often indirectly limit their claims to stateless services.
Serverless architecture is a recent addition to the developer programming/deployment toolset that offers the convenience of zero server deployments while preserving elasticity of scaling.
Building and scaling stateless systems has far fewer challenges over stateful systems. That said, stateless services are limited by data centre infrastructure and begs attention at large footprints - at tens of millions of requests per second. It is therefore seemingly easier to scale stateless services and adds credence to claims of almost limitless elastic scale.
In reality, there is little truth in a truly stateless service, in fact it is a case of state being pushed to another service/system. The challenges therefore shift to scaling stateful services - something harder to achieve.

In this talk I will give an overview of typical application workloads - online vs offline, interactive vs batch, sync vs async etc. and commonly used patterns and libraries to build these systems. We will also evaluate each of these examples to identify critical stateful services/systems and the challenges in scaling them. We will then take the Flipkart Flux open source project as an example to understand the design of a highly scalable stateful system that offers serverless computing for deployed applications, similar to AWS Lambda. The talk will cover various design and tech choices that enables millions of stateful, data-driven workflows/computes to run on the Flux system.


  • Defining scalability - as applied to stateless and stateful systems
  • Stateless service - case of state pushed to a stateful layer
  • Database/Data store for stateful systems. Choices of such stores - Relational, Append-only etc
  • Distributing stateful compute, things to take care of
  • Introduction to serverless architecture, what to expect. Services available
  • Building your own stateful serverless compute engine - the Flux example
  • Data engineering for stateful systems - scaling from single node to multi-node cluster on the network

Speaker bio

Regunath is an open source developer, engineer who built Aadhaar and later was responsible for Flipkart platform services. He is currently at HealthFace building data-driven decision systems for healthcare and personal health records. He is also a core contributor on the Flux project discussed in this talk.


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All about data science and machine learning