Practice Areas

Enterprise are deluged with data irrespective of the industry sector-from health care and financial services to retail and manufacturing. In this voluminous data, lies business insights, opportunities and potential success drivers. Leveraging this Data is a daunting task. We understand challenge part is combining everything and making sense out of it. We also are cognizant of the competitive advantage this data can yield. Our competencies lie in Relational Databases, NewSQL systems, Non-relational systems like NoSQL databases and large scale processing systems like Hadoop. We are conversant with varieties of Data Structures, Data latencies and volumes of data for acquisition, integration, assimilation and processing.

Data Science is about making sense of large amounts of messy data, using it to model and solve complex problems, and presenting the compelling solutions by "telling a story with data." It draws up skills and knowledge from different disciplines - Data engineering, math and statistics, modeling and programming, visualization - aided by deep domain expertise. To expect a single person to have this expertise is unrealistic. Generally, this taklent is pooled as data science teams. Generally, the team composition could be Programmers use statistical software and other contemporary tools to build analytical models and present the results.Data Preparers spend most of their time acquiring data and selecting, combining, and organizing it for use, plus doing some analytics on it. Generalists do a bit of everything, including working with business people to frame problems and discuss analyses, and advising or pitching in on data preparation and programming. Managers provide direction and resources, participate in analytics design and interpretation, and do most of the presentation of results.

Our team has several with different level of skill sets, experience and knowledge to form Data Science teams. We have ability to put together a full-stack Data Science Team.

Data visualization is the presentation of data in a pictorial or graphical format. As more and more data is collected and analyzed, decision makers at all levels welcome data visualization software that enables them to see analytical results presented visually, find relevance among the millions of variables, communicate concepts and hypotheses to others, and even predict the future. Because of the way the human brain processes information, it is faster for people to grasp the meaning of many data points when they are displayed in charts and graphs rather than poring over piles of spreadsheets or reading pages and pages of reports. Our team is capable of creating Interactive visualization - moving beyond the display of static graphics and spreadsheets to using computers and mobile devices to drill down into charts and graphs for more details, and interactively (and immediately) changing what data you see and how it is processed.

In the world that is evolving rapidly, our developers adapt and are quick footed with polyglot programming paradigms and frameworks. Deom the client-side JavaScript, solid understanding of HTML, CSS, image formats, tools and browser quirks to the Server-side NodeJS and understanding of web servers, HTTP, SQL/NoSQL databases and data-exchange formats such as XML and JSON. Even those writing a basic native mobile or desktop app on a single platform require web connectivity, data store, IDE and build tool experience. Besides these, high performance and scientific computing is essential for building systems of today and tomorrow.