Analytics

In today's data driven business climate, customized analytics from real time and batch datasets are used to create dashboards and visualization tools that provide insight to help companies make informed and innovative business intelligence decisions. We have completed many projects for our clients, where processing and getting the data ready for consumption by reporting tools was key to the success of the project.  Our last few big projects included web, gaming and marketing analytics among a wide range of analytical solutions. Once the data is in the right format - cleaned and sumarized - the reporting layer can easily disply the data in a very intuitive fashion resulting in a wow factor among executives and decision makers.  The key to the success of designing a robust analytical platform depends on the underlying architecture of the different layers responsible for storing, retrieving and presenting data. 

Web Analytics

Web Analytics is the collection, integration, organization and analysis of data from website traffic. The accurate collection, analysis and reporting of this web data is an integral part of effective analytics. Web analytics allows a company to visualize, understand and optimize web usage.  Web analytic tools can be used not only to measure web usage, traffic sources and a multitude of metrics but it is also an extremely powerful tool for market research and improving business.

Data Integration

MDM

Data integration (DI) is the assimilation and processing of data from different sources in batch or realtime to data stores (both datawarehouses and/or big data). It is the syncronization of data between diverse applications and involves a lot of data manipulation. There is a lot of computation and storage intensive processes that need to be run, in order to create clean data stores for reporting and visualization. These processes have become essential to a point where it needs to be implicit in everyday business operations.Data integration works with both internal and external data sources. 

 

Data quality is an important aspect of the Data Integration process. Clean and accurate data needs to be maintained in one place, in order to address data inconsistencies that can be caused if data is updated in more than one system.

 

Creating customized system architectures and integration services. Our approach provides an easy-to-implement, highly scalable, cloud-based datawarehouse for the staging, processing and integration of data. Talend  is at the core of our solution to provide more effective and accurate data integration services. More accurate data means more effective Business Intelligence. 

B2B Integration

With the advent of cloud computing modern enterprises have moved away from monolithic applications that used to manage all business operations to a more distributed individual software as a service applications many of which are provide by independent vendors with specialization in specific business areas. But for the effective working of the organization the information needs to be shared across different platforms and applications. This is accomplished primarily through B2B integration tools which have a number of pre-built connectors which enable the seem less communication between the various systems. Most of these application expose API's which can be used to extract the required information and also allows for posting of information. In additions webhooks can be designed which will listen for event based triggers and capture information using Rest based protocols. In most  cases data transfer takes place in JSON for REST and XML for SOAP based applications. We have used Celigo, Dell Bhoomi and Mulesoft for creating these application integration for our clients.