Theme and format
The Fifth Elephant 2017 is a four-track conference on:
- Data engineering – building pipelines and platforms; exposure to latest open source tools for data mining and real-time analytics.
- 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.
- Hands-on tutorials on data mining tools, and ML platforms and techniques.
- 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:
- Draft slides, mind map or a textual description detailing the structure and content of your talk.
- 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.
- 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.
- Proposals will be filtered and shortlisted by an Editorial Panel.
- Proposers, editors and community members must respond to comments as openly as possible so that the selection processs is transparent.
- Proposers are also encouraged to vote and comment on other proposals submitted here.
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.
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”.
- 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 firstname.lastname@example.org or call +91-7676332020.
Dr. Elephant: Achieving Quicker, Easier, and Cost-effective Big Data Analytics
Open Source: https://github.com/linkedin/dr-elephant
Is your job running slower than usual? Do you want to make sense from the thousands of Hadoop & Spark metrics? Do you want to monitor the performance of your flow, get alerts and auto tune them? These are the common questions every Hadoop user asks but there is not a single solution that addresses it. We at Linkedin faced lots of such issues and have built a simple self serve tool for the hadoop users called Dr. Elephant.
Dr. Elephant, which is already open sourced, is a performance monitoring and tuning tool for Hadoop and Spark. It tries to improve the developer productivity and cluster efficiency by making it easier to tune jobs. Since its open source, it has been adopted by multiple organizations and followed with a lot of interest in the Hadoop and Spark community.
In this talk, we will discuss about Dr. Elephant and outline our efforts to expand the scope of Dr. Elephant to be a comprehensive monitoring, debugging and tuning tool for Hadoop and Spark applications. We will talk about how Dr. Elephant performs exception analysis, give clear and specific suggestions on tuning, tracking metrics and monitoring their historical trends.
Phase 1: Introduction to Dr. Elephant. How and why it all started?
Phase 2: This section will cover how Dr. Elephant helps in quickly and easily optimizing Big data applications, saving millions of dollars for the company. I will also talk about the open source activities and initiatives around Dr. Elephant.
Phase 3: I will talk about our efforts to expand the scope of Dr. Elephant to be a comprehensive monitoring, debugging and tuning tool for Hadoop and Spark applications.
Akshay Rai is an engineer at Linkedin working with the Grid team. He is also the lead engineer for the open sourced Dr. Elephant project by Linkedin. He has been working on solutions to improve the developer productivity and building systems to monitor Big Data applications in real time.