Digital Consulting Services

Digital Consulting Services

Digital Practice Full Stack Development

Developing an End to end application to solve a real world problem requires to build a very robust and intelligent application but with a consumer grade user interface. Full stack developers work with both the front and back end of a website. They’re familiar with HTML, CSS, JavaScript, and one or more back end languages.

As the line between what can be done on the front end vs the back end becomes more and more similar, and as things that were previously only possible on the back end become possible on the front end, more developers are becoming what we call “full stack.” A lot of employers (especially agencies who work on different kinds of sites) are looking for developers who know how to work on all the parts of a site, so they can use the best tools for the job regardless of whether it’s technically “front end” or “back end.”

Technologies we work on

  • Front end- HTML, HTML5, JavaScript, J Query, CSS3
  • Backend- Ruby on Rails, PHP, Angular2, Node.js
  • Database- MySQL, MongoDB, CouchDB

Robotic Process Automation (RPA)

RPA is an advanced form for business process automation where we address multiple repetitive task to be automated with the use of advanced technologies like robotics and artificial intelligence. RPA is an application of technology, governed by business logic and structured inputs, aimed at automating business processes. Using RPA tools, a company can configure software, or a “robot,” to capture and interpret applications for processing a transaction, manipulating data, triggering responses and communicating with other digital systems. RPA scenarios range from something as simple as generating an automatic response to an email to deploying thousands of bots, each programmed to automate jobs in an ERP system.

 

We can help you with consulting and skilled resources around

  • Blue Prism
  • UiPath
  • Automation Anywhere

Big Data and Analytics

Big data is primarily defined by the volume of a data set. Big data sets are generally huge — measuring tens of terabytes — and sometimes crossing the threshold of petabytes. The term big data was preceded by very large databases (VLDBs) which were managed using database management systems (DBMS). Today, big data falls under three categories of data sets — structured, unstructured and semi-structured.

Big Data analytics is the process of collecting, organizing and analyzing large sets of data (called Big Data) to discover patterns and other useful information

We can help you with consulting and skilled resources around

  • Hadoop
  • Spark
  • Apache Solr
  • Apache Drill