Big Data Analytics

Dear Employer, I am having more than 3.2+yr experience with in IT industry with machine learning in big data mahout , HBase, Impala , naive map reduce with analysis different data set and different file formats. I have gone through the requirement and I had similar experience in past. Also have hands on developed several recommendation system using big data using different frameworks mahout(big data) and crab with python. Proficiency in different scaleless tools on top of hdfs i.e Impala,Hive,Pig,Sqoop,Spark Also have expertise in R,Python,Java,Scala Certifications and awards:- Cloudera Hadoop Big Data Developer. Coursera Data Science specialization in statistical learning and machine learning. Microsoft SQL server MCTS SPOJ world rank less than 1374 I have been developing web services on top of big data plat form using Hadoop for a MNC. So, I feel I am the right candidate for this work because of having major experience in big data and hadoop HDFS and developing recommendation on top of hadoop. Here this project has multiple things UI and backend(big data store) and there has to be a seamless integration between these two also I have few question in mind if you have time we can discuss on those. Bid can be negotiable after discussion. One more thing money is not important for me thing that matter s for me is satisfaction of client and I mean it. I am waiting for your response if you feel I am the right guy. Thanks,

A proposal has not yet been provided

We are having a team of expert researcher. We have designed and implemented a number of algorithms and systems for distributed computing and related area. We are having experience of around 7 years of research/ development and writing in Cloud computing, big data and Green cloud computing. We have thorough experience on various cloud and big data technology like OpenNebula, Openstack, Hadoop, Map-Reduce etc. We have used and customized these toolkits for our research and development.

I have +5 year expirence in big data analysist. Give me more details of project.

6+ years of experience in machine learning and master degree holder in computer science. Expertise in R,WEKA, JAVA,PYTHON, Hadoop, MapReduce. Worked on many projects in machine learning.

Good Day! As i see some people from India sent their bis :-) 50 million rows it's not a big table and query to this table on index fields for 10-100 record would work fast - near 20-50 ms. But i don't now what do you call "fast". If your table work slow i think it consists varchar field and you try to looking for record with condition on this fields. In this case search engine works not good and you should change structure, because if you change only platform it cound't solve your esues.

Machine learning scholar(PHD degree ), My research area includes Data mining, NLP, Image processing. My past experience in machine learning includes 8+ year in machine learning research. I have expertise in R, Python,JAVA, Hadoop, MapReduce, Hbase, Hive etc.

we have research and development team of 9 members. we have experience of developing cloud projects, and simulations, for this we have used many open source and commercial tools like ec2, rackspaces, google app engine, cloudera, openstack, cloud stack, hadoop, pig, sqoop, hive, and spark. We have good exposure of these tools.

I have 4+ years of working experience in machine learning domain and have master degree in computer science. Worked on many projects mainly in Predictive analytics, Natural language language, text mining, web mining etc. Expertise in R, Python, Hadoop, MapReduce, Hbase,Hive,Pig etc.

I had prior experience in working similar kind of project, where client was facing performance issues while searching for address related fields in his UI. For that scenario, I have migrated the entire address data from RDBMS to Elastic Search cluster (which works very well for Search Related functionality) and another batch job to sync the RDBMS data with Elastic Search Cluster. Elastic search provides both java API’s and Rest to query the data. Whenever user types for those particular fields, request will go to Elastic Search cluster instead of normal RDBMS. Performance gains will be huge with this approach. Hadoop is mainly used for OLAP purpose and it’s not meant for low latency access. I suggest Elastic search is best suited for this project. Elastic Search is a Distributed search engine, there will no single point of failure. Alternatives: Apache Solr – Similar to Elastic search. Both Elastic Search and Solr are based on Lucene.