Big Data Application Development

Big Data is a term applied to data sets and technology stacks that exceed the processing capacity of traditional software tools. In most cases it means that data volumes, formats and sources don't allow to effectively capture, store, request and analyze the data in relational databases within a required elapsed time. Growing data volumes and interconnected systems have necessitated a need for the next generation of analytics and data management solutions. Hadoop, NoSQL and the related ecosystem provide the framework enabling your company to analyze and manage growing volumes of structured and unstructured data.

ThoughtExecution is enabling organizations to leverage and take advantage of the Big Data movement. Our customers are finding new insights from their data and converting them into better business decisions.

Here are some symptoms that your current data technology, architecture or strategy fits into the Big Data category

  • Frequent write operations lock data records and block reading operations. An increasing data volume affects retrieval operation timing so that a search or extraction of business data can't be completed within appropriate time limits
  • Your IT people says that adding new fields to the table will require more than a month of testing as it affects all the systems involved in the data table and requires changes in data models
  • You have to procure new hardware with a more powerful CPU, hundreds of gigabytes of memory to process your data in time

If you see any of these symptoms you’re certainly dealing with Big Data. In that case, Big Data Technologies might help you.

Data Business Challenges :

  • Exponential growth of data volumes makes storage and processing of business prohibitive requires to focus on TCO reduction for information storage and processing
  • Ability to analyze and process big data becomes necessity to manage business, or loose to the competition
  • Wide range of technologies to “offer” solution for data “problems” emerging daily, but selecting right solution and proven expertise becomes a challenge as ever

Big Data technology stacks allow to effectively capture, store, select and process data of big volume, variety and velocity

Real time analytics on the huge data is a real value. Most organizations aren’t able to leverage the data they generate! Big Data analytics solutions will put together a framework for data visualization.

ThoughtExecution Services offerings in Big Data Application Development

  • By technically understanding your needs and requirements ThoughtExecution can help you in evaluating multiple commercial product and Open Source options to let you make the best choice based on your technical and business needs.
  • Have an expertise in the Open Source Hadoop™ Distributed File System (HDFS) with which we able to deal with Big Data challenges quickly and efficiently.
  • With the use of Hadoop which is a scalable solution and performs effectively even on commodity hardware with less resources, we ensures high availability and reliability to our clients.
  • By Harnessing Hadoop functionalities would be able to focus on key areas of Big Data that enables enterprises to optimally utilize existing resources cost effectively.
  • Creating architecture which is extensible, maintainable and portable to different environments.
  • MapReduce - On the "Map" stage of the algorithm, the programming task divides into several sub tasks with the ensuing sub-task distribution closer to data location, on a "Reduce" stage, the results from the sub-tasks are combined into result value
  • Key/Value Storages (including in-memory caches) - Simple interface, Predictable performance, Effective building block of any system

ThoughtExecution expertise in Big Data Technologies stack

MapReduce Programming
HDFS File System
Hive Query Language
Oozie, Zookeeper
Data Management: Flume, Sqoop
Cluster Configuration & Optimization
NoSQL Databases
Apache Mahout
Data Operators & Algorithms
Machine Learning & Data Mining
Text Mining & Language Processing
Lucene, Solr, Nutch
Platforms & Distributions
Amazon Elastic MapReduce
Apache Hadoop
Cloudera CDH