Jul 2014
21 Mon
22 Tue
23 Wed 09:30 AM – 05:00 PM IST
24 Thu 09:45 AM – 05:00 PM IST
25 Fri 08:30 AM – 07:15 PM IST
26 Sat 08:30 AM – 07:15 PM IST
27 Sun
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.
Tickets: http://fifthel.doattend.com
Website: https://fifthelephant.in/2014
For queries about proposals / submissions, write to info@hasgeek.com
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.
Real-time analytics
Opportunity analytics
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.
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At Wingify, we have built a system to process and store analytics data for our customers, which they can use to slice and dice the data to make more meaningful reports. This talk is about how we solved this problem and how we used Elasticsearch to solve this problem at our scale rather quickly. Audience will take away some of the data problems they can quickly solve with Elasticsearch.
At Wingify, we collect data for website and mobile A/B testing campaigns created by our customers, store, process and crunch it to make it usable by our customers in the form of various reports that they use for Conversion Rate Optimization. This data is critical for our customers to make engineering, design and business decisions to improve their conversions and achieve their business goals. Being able to generate custom reports according to our customers’ requirements with the ability to slice and dice the data to get more targeted and meaningful reports is an important feature of the core of our application. And the enormous amount of data generated by campaigns created by thousands of customers makes this problem even more difficult as we have to carefully process the data keeping in mind the current and the future needs of the application, store it so that our users can play with it with the utmost flexibility and serve reports created using this data as fast as possible.
This talk will focus on how we discovered and used Elasticsearch to quickly prototype and use it to solve the described problem, how we took our implementation from prototype to production and the challenges we faced along the way:
I am a software engineer based out of New Delhi, working for Wingify, a Delhi based bootstrapped startup that develops the A/B testing tool - Visual Website Optimizer (VWO). At Wingify, I am primarily focused on services, scalability and infrastructure engineering, which also happens to involve working with data and analytics and all the problems that come with it. I am an open-source enthusiast. In my free time, I evangelize and try to organize local meetups and watch movies.
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