The Fifth Elephant is rated as India’s best conference on big data, data science and application of data to real-life use cases.
It is a conference for practitioners, by practitioners. The Fifth Elephant completed its seventh edition in Bangalore, on 26 and 27 July 2018. The Bangalore edition caters to data and ML engineers, architects, technologists, data scientists, product managers, researchers and business decision-makers.
Call for proposals
The winter edition will cover the following topics:
- Data engineering
- Data governance including data quality, version control and trust in data, and workflows in organizations.
- Leveraging data for business use cases – with analytics and data science
- Leveraging data for business use cases – case studies of how and why analytics and data science were applied in organizations.
- Inculcating analytical thinking in teams and organizations.
We’d like to hear talks from the following domains:
- Consumer internet companies
We work with our speakers to help participants from other domains understand and apply insights presented to their use cases. Therefore, individuals and companies from other domains should consider attending the winter edition.
Target audience - who should attend and speak at The Fifth Elephant:
You should attend and speak at The Fifth Elephant if your work involves:
- Engineering – ML engineering, data engineering, data-ops
- Data science.
- Product development - analyzing data to build features for existing products.
- Cleaning data and ensuring better data quality.
The winter edition is a single-day conference. We are accepting sessions for the following formats:
- Full talks of 30 minutes.
- Crisp talks of 20 minutes.
- BOF sessions for 60 minutes duration, on a focussed topic.
- Workshops and tutorials of 3-6 hours duration on math and data science, full stack data engineering, and data science concepts and tools. Workshops will be held before and after the conference.
Write to email@example.com if you are interested in speaking at the winter edition.
The first filter for a proposal is whether the technology or solution you are referring to is open source or not. While the winter edition does not include talks on engineering, talks which advertise proprietary solutions will be considered under sponsored sessions category.
Note the following guidelines for sponsored talks:
- If the technology or solution is proprietary, and you want to speak about your proprietary solution to make a pitch to the audience, you should pick up a sponsored session. This involves paying for the speaking slot. Write to firstname.lastname@example.org
- If the technology or solution is in the process of being open sourced, we will consider the talk only if the solution is open sourced at least three months before the conference.
- If your solution is closed source, you should consider proposing a talk explaining why you built it in the first place; what options did you consider (business-wise and technology-wise) before making the decision to develop the solution; or, what is your specific use case that left you without existing options and necessitated creating the in-house solution.
The criteria for selecting proposals, in the order of importance, are:
- Key insight or takeaway: what can you share with participants that will help them in their work and in thinking about analytics and the problem space?
- Structure of the talk and flow of content: a detailed outline – either as mind-map or draft slides or textual description – will help us understand the focus of the talk, and the clarity of your thought process.
- Ability to communicate succinctly, and how you engage with the audience. You must submit link to a two-minute preview video explaining what your talk is about, and what is the key takeaway for the audience.
No one submits the perfect proposal in the first instance. We therefore encourage you to:
- Submit your proposal early so that we have more time to iterate if the proposal has potential.
- Write to email@example.com if you have questions about how to submit a talk.
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.
We only accept one speaker per talk. This is non-negotiable. Workshops may have more than one instructor.
How to submit a proposal (and increase your chances of getting selected):
The following pointers will help you in submitting a proposal:
- Focus on why, not how. Explain to participants why you made a business or engineering decision, or why you chose a particular approach to solving your problem.
- The journey is more important than the solution you may want to explain. We are interested in the journey, not the outcome alone. Share as much detail as possible about how you solved the problem. Glossing over details does not help participants grasp real insights.
- We do not accept how-to talks unless they demonstrate latest technology. If you are demonstrating new tech, show enough to motivate participants to explore the technology later.
- Similarly, we don’t accept talks on topics that have already been covered in the previous editions. If you are unsure about whether your proposal falls in this category, drop an email to: firstname.lastname@example.org
- Content that can be read off the internet does not interest us. Our participants are keen to listen to use cases and experience stories that will help them in their practice.
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. We do not provide free passes for speakers’ colleagues and spouses. Please do not ask us for this.
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.
Last date for submitting proposals is 15 October 2018:
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-recorded, 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 the solution you have built, or 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 a document showing the full workshop plan.
For more information about the conference, sponsorships, or any other information contact email@example.com or call 7676332020.
Data pipeline on day one of your startup: cost and scale sensitive!
by Kumar Puspesh, CTO and co-founder at Moonfrog
- Business Requirements
- Having a scalable system for data ingestion
- Data design - Specific or Generic?
- Querying interface - why stick to SQL?
- Query interface users - skills, requirements and expectations
- Data ingestion
- High throughput stats service
- Thin client: Badger
- High throughput Ingestion backend
- Hot loading to Redshift
- Data Warehousing
- Data design in Redshift and data lake
- Tuning for scale
- Taking care of Querying patterns of Product Managers and Data scientists
- S3 as Data Lake
- On demand Data loading and querying: OnDemand Table(s)
- Flexibility for complicated analysis: Adhoc redshift cluster(s)
- On demand Data loading and querying: OnDemand Table(s)
- Scaling up
- Typical bottlenecks and solutions we tried
Reducing cost of production AI: a feature engineering case study
by Venkata Pingali, CEO and co-founder at Scribble Data
- Feature Engineering Overview
- Typical Feature Engineering Cycle
- Detailed Cost Drivers
- Examples: Reconciliation & auditing, change management
- Indicative Quantitative Improvement
- Detailed discussion of each driver
Data governance: lessons on data usage and data controls from finance domain
by Kaushik Bhatt, Vice President at Wells Fargo
Data Governance session outline will cover,
- systematic approach to identifying enterprise data assets, who owns them and who can access them - data protection approach - data catalogue, data profiling and data quality
Role of data in solving capacity and efficiency problems in real-time logistics
by Piyush Srivastava, Director of Engineering for Delivery Team at Swiggy
- Introduction and Context
- The Capacity Problem - what is it; why it is important?
- The Efficiency Problem - what, why and the necessary trade-offs
- Data and its Nature
- Challenges with Accurate Data Capture
- Challenges with high Variance
- Real-time Vs. historical data
- Representing Capacity
- Aggregated capacity (Zone-level)
- Point-in-time-capacity (Order-level)
- Journey and Results: Solving for Capacity
- Efficiency Levers
- Predictions and accounting for errors
- Optimal Assignment
- Aggregate Analysis Vs. Specific Analysis
- Pitfalls of Aggregate Analysis
Patterns for building a scalable Data Platform
by Jayesh Sidhwani, Data Infrastructure Team Lead at Hotstar
- Ingestion Patterns
- Unified Ingestion Proxy
- Schema Definitions
- In-flight enrichments
- Highly Available
- Storage Patterns
- Decouple storage and compute
- Query Lineage & Optimization
- Noisy Neighbour
- Consumption Patterns
- Single GUI and a programmatic interface. All the magic underneath
- Parity between streaming and stationary data
- Ingestion Patterns
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Venkata Pingali (@venkatapingali)
kaushik bhatt (@bhattkaushik)
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