Big Data and Analytics


In today's marketplace, it is imperative for organizations to collect and analyze massive amounts of data (both structured and semi-structured), as well as associated business processes, through the lens of defined processes and tools. Thus, Big Data analytics, Data Warehousing, and Business Intelligence solutions play an important role in the continuous improvement of operational efficiency, performance management, and strategic decision making.



As the amount of data generated increases at geometric rates, businesses need more intelligent ways to understand and utilize data. The solutions to this growing dilemma are to be found in the new field of Big Data. Machine learning is one of the most important aspects of this approach. Open source technologies like Hadoop, MongoDB, and Vertica are making it easier to perform Big Data analysis and the consequent strategic decision making. In addition, data logs are playing an important role in maintaining system health.


At Indecomm, we help our clients achieve their Big Data solution goals by leveraging our expertise in Big Data (MongoDB etc.), near Real Time search (Elasticsearch, etc.). Our DW/BI practice provides clients and enterprise product companies with best-in-class services that collect, organize, and analyze enterprise data residing in disparate systems which, in turn, generate the insights necessary to make strategic decisions that drive the business. To do this, we build and maintain data warehouses, implement algorithms for analytics, build ETL routines, perform complex calculations, provide integration solutions and large-scale reporting services and solutions. For clients that are required to implement their products at various locations, we can work onsite as well as from offshore.


With the increased use of applications for analysis of billing information, error monitoring and such comes a corresponding increase in application-generated logs. At Indecomm, we help our clients analyze data generated by these applications, so that they can monitor and determine the health of the distributed setup (which usually includes hundreds of machines). Solutions like Logstash, Splunk and Kibana are used to provide real-time monitoring, which allows the user to reduce analysis time and respond quickly to any issues.