N. L. Dalmia Centre of Excellence Offering Postgraduate Program in Business Analytics

MUMBAI :  N. L. Dalmia Centre of Excellence, one of the top-rated technical academic institutes in India, has collaborated with Virginia Tech, a leading American research university, to unleash knowledge-driven Postgraduate Program in Business Analytics. The move is in line with the institution’s mission for equipping the pursuant with proven strategies that define predictive analysis, and giving them a way forward in the labour market and the ensuing career. N. L. Dalmia Centre of Excellence has a reputation for enriched, immersive learning experiences, which is optimally evident in the way the program will be delivered.

The PG program encompasses instructions on contemporary technologies – from cloud computing to quantitative methods and everything in between – to keep professionals on the cutting edge. They can also get familiar with several facets of innovation and quick response methods to Black Swans. The program lasts for 11 months and is divided into six units, each lasting roughly for two months. In association with Virginia Tech, N. L. Dalmia Centre for Excellence have put together a credentialed, multimodal faculty that will walk one through the learning process while industry professionals will be there to give colloquia. Instructions are provided in both face-to-face and online modes.

What is predictive analysis?

Corporations are awakening to the role that predictive analysis plays in nourishing their long-term growth prospects. Predictive analysis is a multimodality approach undertaken to make sense of historic and transactional data, which is growing at an inconvenient rate in variety, volume and velocity. It is essentially software that amalgamates several statistical algorithms, including data mining, modelling, artificial intelligence and machine learning, to pre-empt future. Predictive analysis empowers corporations to extract actionable, relevant information from data to uncover patterns, find associations, mitigate risks and streamline processes. The whole idea boils down to staying informed on the past events to figure out what the future has in store. The adage ‘answers to the future lies in the past’ holds so true in predictive analysis.

Predictive modelling is an integral part of predictive analysis, involving the creation of a model, which is subsequently tested and validated. We have access to multiple modelling methods, including classification models, regression models and neural networks, based on statistics and artificial intelligence. However, the bottom line remains same across the board – to forecast an outcome in real time using the growing influx of data. The analytics are particular about choosing the appropriate modelling method, basing their decisions on detection theory and outcomes of tests, validations and assessments. Each predictive model is tailored to address a particular issue and can be used repeatedly with specifically trained algorithms.

Some applications of predictive analysis:

As an effective, outcome-oriented and low-cost proposition, vis-à-vis the conventional analysis, predictive analysis is making its way into sectors and geographies. Let’s get a brief idea of how the ingenious analytical method is helping businesses to tide over the lean phases and create long term value.

  • Customer segmentation: 
    Assumingly, one is the head of marketing division of a corporation. Since they will be dealing with a vast customer base with diverse tastes, inclinations and needs, the ‘one size fits all’ approach may fail miserably. However, if the clientele is organized into specific groups based on certain commonalities – demographics, gender, spending capacity and more – they have a better chance of targeting the right audience in the right manner. This process is called the customer segmentation. The predictive analysis adds cutting edge to customer segmentation by using past data to recognize potential clients and keep the existing ones intact.
  • Financial modelling
    When one represents the real financial situation through an apt model, the process is called financial modelling. Usually, the financial model entails an organization’s asset or investment and presents it in a lucid and elaborate manner for the non-technical people to understand. It is all about extracting information on the behavioural aspect of markets and several variables and converting it into numerical predictions that can be the cornerstone of wise business decisions.
  • Sales Forecasting: 
    As imperative as sales are for a business, one has to analyze sales patterns in the past to forecast future trends. The sheer magnitude of factors that can affect sales is overwhelming enough to drive them on the edge. Through an all-inclusive, data-driven algorithm, predictive analysis can save the day, providing near accurate sales forecasts for all regions and segments.
  • Detect deceptions:
    Since no business is immune to frauds, the management has to be on its toes to detect such practices before they gain criticality. Predictive analysis is proving to be a handy tool for fraud detection and cyber security, providing one with real-time behavioural patterns. Any anomaly in patterns is indicative of vulnerabilities and frauds that otherwise would have slipped through the cracks.
  • Market study:
    All major brands have one thing in common – they are attuned to the market demands. They put in resources to know what exactly the end user desires and then create products, services and solutions accordingly. When paired with predictive analysis, these market surveys can pinpoint exact customer needs, leading to higher ROI and lesser attrition rates.
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