Business Intelligence, Advanced Analytics and Big Data Solutions

 

For Business Analytics Solutions, we will meet up with the customers and understand their business and objectives they are trying to achieve, then we will advise the use cases with clear and specific business goals to deliver the expected business value, for example, HR analytics, Sales forecasting, Upsell, CrossSell, NextSell propensity models, recommendation engines, workflow/processes optimizations.

 

Key parameters that we focus to offer our services to customers, which are applied on different verticals and business units.

 

Predictive Modelling

• Application of logic and mathematics to data to specify a preferred course of action

• Uses statistics to predict outcomes.

• Can be applied to any type of unknown event, regardless of when it occurred. For example, predictive models are often used to detect crimes and identify suspects, after the crime has taken place.

• In many cases the model is chosen on the basis of detection theory to try to guess the probability of an outcome given a set amount of input data, for example given an email determining how likely that it is spam.

 

Demand Forecasting

• Art and science of forecasting customer demand to drive holistic execution of such demand by corporate supply chain and business management.

• Involves techniques including both informal methods, such as educated guesses, and quantitative methods, such as the use of historical sales data and statistical techniques or current data from test markets.

• May be used in production planning, inventory management, and at times in assessing future capacity requirements, or in making decisions on whether to enter a new market

 

Operations Research

• Optimal or near-optimal solutions to complex decision-making problems.

• Emphasis on human-technology interaction and because of its focus on practical applications.

• Often concerned with determining the maximum (of profit, performance, or yield) or minimum (of loss, risk, or cost) of some real-world objective.

 

Optimizations

• Achieved by data mapping, an essential aspect in data integration.

• Includes data transformation or data mediation between a data source and its destination, and in this case, the data sources could refer to the logical schema and the destination the data view schema.

• Data mapping as a means of data optimization could translate data between various kinds of data types and presentation formats into a unified format used in different reporting tools.