My Service

Data Science

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured, similar to data mining.

Machine Learning

Machine learning is an interdisciplinary field that uses statistical techniques to give computer systems the ability to "learn" (e.g., progressively improve performance on a specific task) from data, without being explicitly programmed.

Business Analytics

Business analytics (BA) refers to the skills, technologies, practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning.

System Analysis

System analysis is the process of studying a procedure or business in order to identify its goals and purposes and create systems and procedures that will achieve them in an efficient way.

BPR & BPMS

Business process re-engineering (BPR) is a business management strategy, focusing on the analysis and design of workflows and business processes within an organization.

Enterprise Resource Planning

Enterprise resource planning (ERP) is the integrated management of core business processes, often in real-time and mediated by software and technology.

Data Science as a SERVICE

Are you still struggling to unlock the true potential of your Big Data?
All the desired customer information is at your fingertips. You have a variety of analytics tools installed across various platforms. You can scrutinize and analyze your customers, revenues and operations under any angle.
But do you lack the system to operationalize all that data and your current tools do not deliver the full picture?
Only 23% of enterprises manage to use ¾ of all the Big Data at their disposal. Over 37% of people admit that it takes over a day to access the source for analytics and can take over a week in extreme cases. We deliver actionable insights – you take respective business decisions to move your company forward. The data science services will help you stay well ahead of the competition, take the guesswork out of your consumer-driven decisions, drive your revenues growth and improve the overall operations efficiency. Picture the following – another angry customer rings up your support team. By typing their credentials, your support representative can review their past spending with your company, recent purchase history or account type. But what if…they could additionally receive real-time insights on the customer’s return history? Their public and private feedback on your company left in the surveys and review websites, their purchase frequency and more? This kind of data enables your staff to take better decisions and deliver more personalized support. And that’s just one example. The Big Data Solutions enable you to take better marketing decisions, measure and optimize your social media campaigns; predict customer behavior with razor sharp accuracy and make precise sales forecasting.

Learn More

MY SERVICE POINT

As data science getting more and more traction in all the major industries. So, in this new, exciting
and challenging field there are lots of opportunities.

Data Science

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured, similar to data mining. Data science is a "concept to unify statistics, data analysis, machine learning and their related methods" in order to "understand and analyze actual phenomena" with data. It employs techniques and theories drawn from many fields within the context of mathematics, statistics, information science, and computer science. Turing award winner Jim Gray imagined data science as a "fourth paradigm" of science (empirical, theoretical, computational and now data-driven) and asserted that "everything about science is changing because of the impact of information technology" and the data deluge.

Machine Learning

Machine learning is an interdisciplinary field that uses statistical techniques to give computer systems the ability to "learn" (e.g., progressively improve performance on a specific task) from data, without being explicitly programmed. The name machine learning was coined in 1959 by Arthur Samuel. Machine learning explores the study and construction of algorithms that can learn from and make predictions on data– such algorithms overcome following strictly static program instructions by making data-driven predictions or decisions, through building a model from sample inputs. Machine learning is employed in a range of computing tasks where designing and programming explicit algorithms with good performance is difficult or infeasible; example applications include email filtering, detection of network intruders, and computer vision.

Business Analytics

Business analytics refers to the skills, technologies, practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics focuses on developing new insights and understanding of business performance based on data and statistical methods. In contrast, business intelligence traditionally focuses on using a consistent set of metrics to both measure past performance and guide business planning, which is also based on data and statistical methods. Business analytics makes extensive use of statistical analysis, including explanatory and predictive modeling, and fact-based management to drive decision making. It is therefore closely related to management science. Analytics may be used as input for human decisions or may drive fully automated decisions. Business intelligence is querying, reporting, online analytical processing (OLAP), and "alerts."