In 2014, infrastructure components such as Hadoop, Berkeley Data Stack and other commercial tools have stabilized and are thriving. The challenges have moved higher up the stack from data collection and storage to data analysis and its presentation to users. The focus for this year’s conference on analytics – the infrastructure that powers analytics and how analytics is done.
Talks will cover various forms of analytics including real-time and opportunity analytics, and technologies and models used for analyzing data.
Proposals will be reviewed using 5 criteria:
Domain diversity – proposals will be selected from different domains – medical, insurance, banking, online transactions, retail. If there is more than one proposal from a domain, the one which meets the editorial criteria will be chosen.
Novelty – what has been done beyond the obvious.
Insights – what insights does the proposal share with the audience that they did not know earlier.
Practical versus theoretical – we are looking for applied knowledge. If the proposal covers material that can be looked up online, it will not be considered.
Conceptual versus tools-centric – tell us why, not how. Tell the audience what was the philosophy underlying your use of an application, not how an application was used.
Presentation skills – proposer’s presentation skills will be reviewed carefully and assistance provided to ensure that the material is communicated in the most precise and effective manner to the audience.
For queries about proposals / submissions, write to firstname.lastname@example.org
Data Collection and Transport – for e.g, Opendatatoolkit, Scribe, Kafka, RabbitMQ, etc.
Data Storage, Caching and Management – Distributed storage (such as Gluster, HDFS) or hardware-specific (such as SSD or memory) or databases (Postgresql, MySQL, Infobright) or caching/storage (Memcache, Cassandra, Redis, etc).
Data Processing, Querying and Analysis – Oozie, Azkaban, scikit-learn, Mahout, Impala, Hive, Tez, etc.
Big data and security
Big data and internet of things
Data Usage and BI (Business Intelligence) in different sectors.
Please note: the technology stacks mentioned above indicate latest technologies that will be of interest to the community. Talks should not be on the technologies per se, but how these have been used and implemented in various sectors, enterprises and contexts.
Tailor made stores at myntra or how to personalize your search results
This will showcase a unique way of personalization which is a combination between search and recommendations. Here we’ll not go into the details of the algorithms of how a product is deemed suitable for a user but given that the product has been shortlisted on certain criteria how to show case that.
The talk will give some idea of Cassandra and Solr.
Myntra is India’s biggest online fashion store. We sell hundreds of thousands of apparels and footwears hence we continuously face the problem of how to showcase our vast catalogue and how to make sure that a user gets to the prodcut (s)he is looking for with minimum hassle. We’ve tried various approaches with varying degree of success. The approach we’ve taken is kind of non-intrusive cross between recommendations and search where on any product listing page we are first showing products based on user past behaviour and then the usual products.
Associate architect at myntra with over 10 years of experience. Dabbling in big data and search related problems for last four years.