Proposal guidelines
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:
- Data engineering – engineering and architecture approaches; problems that teams were attempting to solve (and therefore the solutions that they built).
- ML engineering – engineering and architecture approaches; problems that teams were attempting to solve (and therefore the solutions that they built).
- Data science – and its applications in diverse domains.
- Open source algorithms
- Data privacy and its solutions in technology; engineering implementations of HIPPA compliance, GDPR and other data protection frameworks.
- Data security – standards, approaches to solving data security, challenges and problems to solve for data security at scale.
- Business intelligence – how non-technical teams are accessing data in companies to mine intelligence; approaches to BI; real-life case studies and applications of BI; what counts as business intelligence for businesses.
- Decision science.
Submissions are closed for this project
All submissions
Building a large-scale Data as a Service (DaaS) platform to consistently deliver high-quality datasetsAayushi Pathak (@09aayushi) (proposing)
Session type: Short talk of 20 mins
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Finding needles in high dimensional haystacks: Product Matching in RetailAayushi Pathak (@09aayushi) (proposing)
Session type: Short talk of 20 mins
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Websites to DatasetsAayushi Pathak (@09aayushi) (proposing)
Session type: Short talk of 20 mins
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A Journey of Building Dream11's Data PlatformPradip Thoke (@thokepradip)
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Deep Learning powered Genomic Researchusha rengaraju (@usharengaraju)
Session type: Workshop
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Panel Discussion around Healthcare Analyticsusha rengaraju (@usharengaraju)
Session type: Birds of a Feather session of 1 hour
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Interpretable NLP ModelsLogesh kumar (@infinitylogesh)
Session type: Tutorial
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Real-Time DataQuality on FlinkJaydeep Vishwakarma
Session type: Full talk of 40 mins
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Building a Location Intelligence Platform for audience segmentationSanjoy Bose (@sanjoybsahaj)
Session type: Short talk of 20 mins
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How to make a kickass data platform with spark and S3Anshul Singhle
Session type: Full talk of 40 mins
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Anomaly Detection at Scale: Architectural Choices for Data Pipelines for 7B events per dayTuhin Sharma (@tuhinsharma121)
Session type: Full talk of 40 mins
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Deploying Deep Learning models on the Edge (Android, IOS, ...)A Naveen Kumar (@4nonymou5)
Session type: Full talk of 40 mins
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Machine Learning Model Management with MLflowRavi Ranjan (@raviranjan03)
Session type: Tutorial
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Building a data pipeline inside and outside a vehicleChaitanya Hegde (@chaitanyahegde)
Session type: Short talk of 20 mins
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Data Science for the discretionary managers: Lessons from a 60 trillion$ traditional industry resistant to change and facing the quant threatChandini Jain (@chandinijain)
Session type: Short talk of 20 mins
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Case study: Outbound logistics optimization for multi depot problem with time windowAmit Garg (@garg108)
Session type: Short talk of 20 mins
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