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 email@example.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.
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.
Developing Real-Time Data Pipelines with Apache Kafka
The audience would be benefitted in terms of understanding “A High-throughput distributed Messaging system”- KAFKA, which is developed used at Linkedin.
Audience will be understanding :
What is Apache Kafka ,
What Problem Apache Kafka Solves,
Brief overview about its components,
Its High-throughput and Durable data persistence System ,
Sample Use cases,
Comparison with existing solutions,
Kafka powered Solutions,
KAFKA can be in conjunction with realtime computaion systems like Storm can help us to scale at millions of records processing per second.
In nutshell, Audience will be able to understand the scenarios where kafka can be plugged in the architecture where its competitors like JMS, flume ,scribe are limiting.
kafka features of Compression and log compaction can be useful for many participants worried about network bandwidth and disk space.
The Session will have an overiew , concepts , Architecture Details of KAFKA.
Where to fit it, the benefits and features.
API discussion and a Simple Demo or application.
And The Support for Kafka from other products for integration, deployement and monitoring.
A standard VM with JAVA >1.6 and and editor like eclipse or any preferred one.
I Manisha Sethi,have been working in BigData technologies like Hadoop , YARN and NoSQL DBs for many years. With three years of experience i have got the opportuninty to work on kafka in AWS as well to handle TB,s of DATA among various DC’s. And I have also developed applications on kafka with Storma and Cassandra for real time Data Processing.
Currently Working with GODATADRIVEN- The Cloudera partners.