Building a Generic but highly customizable and scalable Anomaly Detection System @ Badoo

Jul 2017

24 Mon

25 Tue

26 Wed

27 Thu 08:15 AM – 10:00 PM IST

28 Fri 08:15 AM – 06:25 PM IST

29 Sat

30 Sun

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MLR Convention Centre, Whitefield, Bengaluru,

##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.

##Selection Process

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.

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

##Contact
For more information about speaking proposals, tickets and sponsorships, contact info@hasgeek.com or call +91-7676332020.

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The Fifth Elephant Pune Meetup

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The Fifth Elephant

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

All submissions

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Building a Generic but highly customizable and scalable Anomaly Detection System @ Badoo

Submitted May 31, 2017

Section: Full talk for data engineering track Technical level: Intermediate

Badoo is a data driven company with 340 million users across 190 countries it provides a number of apps and white label services across multiple platforms. Badoo crunches through around 23 billion events per day with 600 different types of events. Automated tracking a large number of events and reporting observations which do not conform to an expected pattern is the essential part of our data driven methodology.

Badoo had an Anomaly Detection prototype which was built using the strong competence of Data scientists involving complex algorithm. Prototype gave us the experience of many requirements which needs to be fulfilled to have a scalable and robust system.

Based on our learning with the prototype, Badoo Data Engineering team decided to build a new Anomaly Detection system with the following requirement,

Extensible: User should be able to add any new Anomaly report without any manual intervention involved.
Scalable: User can be able to track and process thousands of metrics.
Accuracy: we should low false-positive rate.
Customizable: User should be able to define its own condition of Notification and Notification delivery medium.
Accuracy: System should have a low false-positive rate.
Secure: System must be able to specify the level of access to data.

In this talk, I would be sharing the learnings and the Architecture of our Anomaly detection system build using Hadoop, Spark and other Big Data Technologies.

Outline #

Introduction to Badoo.
Details of Badoo’s in-house event tracking system.
Learning from Anomaly Detection Prototype.
New Anomaly Detection system.
- The architecture of the system.
- Anomaly Detection Module.
- Ranking Module.
- Delivery Module.
- Flow for adding a new report to Anomaly Detection system.
Future work.

Speaker bio #

Akash Mishra is currently working as a Data Engineer at Badoo Trading Limited with more than 6 years experience in building large scale big data application for various client of ThoughtWorks Technologies. He has production experience with various big data technologies like Spark,Hadoop, Mesos e.t.c. He is passionate developer and has deep interest in Distributed Systems. He has co-organised Big Data Meetup for Pune & NCR. He has already given various talks in meetups and Geek Night & contributed to Apache Spark project.

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