The Fifth Elephant round the year submissions for 2019
Submit a talk on data, data science, analytics, business intelligence, data engineering and ML engineering
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Accepting submissions till 31 Dec 2020, 11:59 PM
Submit a talk on data, data science, analytics, business intelligence, data engineering and ML engineering
Accepting submissions till 31 Dec 2020, 11:59 PM
If you missed the deadline for submitting your talk for The Fifth Elephant 2019 -- to be held in Bangalore on 25 and 26 July -- you can propose a talk here.
We are accepting talks on:
##Perks for submitting proposals:
Submitting a proposal, especially with our process, is hard work. We appreciate your effort.
We offer one conference ticket at discounted price to each proposer.
We only accept one speaker per talk. This is non-negotiable. Workshops may have more than one instructor.
In case of proposals where more than one person has been mentioned as collaborator, we offer the discounted ticket and t-shirt only to the person with who the editorial team corresponded directly during the evaluation process.
##Selection criteria:
The first filter for a proposal is whether the technology or solution you are referring to is open source or not. The following criteria apply for closed source talks:
The criteria for selecting proposals, in the order of importance, are:
No one submits the perfect proposal in the first instance. We therefore encourage you to:
Our editorial team helps potential speakers in honing their speaking skills, fine tuning and rehearsing content at least twice - before the main conference - and sharpening the focus of talks.
##How to submit a proposal (and increase your chances of getting selected):
The following guidelines will help you in submitting a proposal:
To summarize, we do not accept talks that gloss over details or try to deliver high-level knowledge without covering depth. Talks have to be backed with real insights and experiences for the content to be useful to participants.
##Passes and honorarium for speakers:
We pay an honorarium of Rs. 3,000 to each speaker and workshop instructor at the end of their talk/workshop. Confirmed speakers and instructors also get a pass to the conference and networking dinner. We do not provide free passes for speakers’ colleagues and spouses.
##Travel grants for outstation speakers:
Travel grants are available for international and domestic speakers. We evaluate each case on its merits, giving preference to women, people of non-binary gender, and Africans. If you require a grant, request it when you submit your proposal in the field where you add your location. The Fifth Elephant is funded through ticket purchases and sponsorships; travel grant budgets vary.
You must submit the following details along with your proposal, or within 10 days of submission:
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Tuhin Sharma
@tuhinsharma121
Submitted Jul 2, 2019
Cloud-native applications. Multiple Cloud providers. Hybrid Cloud. 1000s of VMs and containers. Complex network policies. Millions of connections and requests in any given time window. This is the typical situation faced by a Security Operations Control (SOC) Analyst every single day. In this talk, the speaker talks about the high-availability and highly scalable data pipelines that he built for the following use cases :
The above can be modeled through anomaly detection models. The main challenge here is the data engineering pipeline. With almost 7 Billion events occurring every day, processing and storing that for further analysis is a significant challenge. The machine learning models (for anomaly detection) has to be updated every few hours and requires the pipeline to create the feature store in a significantly small time window.
The core components of the data engineering pipeline are:
Apache Pulsar is the pub-sub messaging system. It provides unified queuing and streaming. Think of it as a combination of Kafka and RabbitMQ. The event logs are stored in Druid through kafka topic. Druid supports apache kafka based indexing service for realtime data ingestion. Druid has primitive capabilities to create sliding time window statistics. More complex real-time statistics are computed using Flink. Apache Flink is a stream-processing engine and provides high throughput and low latency. Spark jobs are used for batch processing. Cassandra serves as the data warehouse as well as the final database.
The speaker talks through the architectural decisions and shows how to build a modern real-time stream processing data engineering pipeline using the above tools.
Tuhin Sharma is co-founder of Binaize Labs, an AI based Cyber Security Start-up. He worked in IBM Watson and RedHat as Data Scientist where he mainly worked on Social Media Analytics, Demand Forecasting, Retail Analytics and Customer Analytics. He also worked at multiple start ups where he built personalized recommendation systems to maximize customer engagement with the help of ML and DL techniques across multiple domains like FinTech, EdTech, Media, E-comm etc. He has completed his post graduation from Indian Institute of Technology Roorkee in Computer Science and Engineering specializing in Data Mining. He has filed 5 patents and published 4 research papers in the field of natural language processing and machine learning. Apart from this, He loves to play table tennis and guitar in his leisure time. His favourite quote is “Life is Beautiful.” You can tweet him at @tuhinsharma121.
https://docs.google.com/presentation/d/1ZCaETragZsRntQTK1nIpFmcNV_ZJVfz2rrh4omeD-24/edit?usp=sharing
Accepting submissions till 31 Dec 2020, 11:59 PM
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