Big Data

The challenges include analysis, capture, cu-ration, search, sharing, storage, transfer, visualization, and privacy violations. The trend to larger data sets is due to the additional information derivable from analysis of a single large set of related data, as compared to separate smaller sets with the same total amount of data, allowing correlations to be found to “spot business trends, prevent diseases, combat crime and so on.

Our data engineering team is having strong capabilities for both traditional and big data needs. Whether it is fetching and managing data, or building and integrating analytic solutions, our engineers are intimately familiar with state-of-the art technologies, and customize the solution per client needs and constraints.

We have worked on a variety of big data environments, We are in-depth experience in  web scrawling , fetching data using APIs or scrubbing. As per the clients required structure . We are compatible with all languages to  analyze the large volumes of unstructured data .

Technologies where we are very sound and achieving the requirements .

  • Cloudera
  • Hortonworks
  • HBase
  • Hive
  • MongoDB
  • Cassandra
  • Elasticsearch
  • fluent
  • MapReduce
  • Pig
  • machine learning