Various ways during which analytics help enterprises drive business growth – Stastwork

VARIOUS WAYS DURING WHICH ANALYTICS HELP ENTERPRISES DRIVE BUSINESS GROWTH

An Academic presentation by Dr. Nancy Agnes, Head, Technical Operations, Statswork Group

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TODAY'S DISCUSSION Outline

Introduction EMERGENCE OF THE NEW CONCEPT OF TECHBUSINESS- ANALYTICS (TBA) Predictive analytics Descriptive Analytics (DESCBA) Prescriptive Analytics (PREBA) Conclusion

INTRODUCTION

Business Analytics help in extracting necessary information from all the data available to transform into a coherent structure for further use. The process of data implementing the advanced analy tics techniques in the business domain to derive and predict useful decisions is called BA

EMERGENCE OF THE NEW CONCEPT OF TECHBUSIN ESSANALYTICS (TBA):

It is the mechanism by which organizations use statistical tools and technology to examine historical data to attain new insights and improve strategic decision-making.

It needs managerial skill that integrates business experience, recognizes market value opportunities, or recognizes problems, with a great understanding of analytical techniques required to align technical talent with functional managers to drive business change.

A new model industry 4.0 technology is founded on business analytics using a recently developed analysis framework called predictive analysis [7].

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PRED ICTIV E ANALYTICS

This uses statistics and network analytics to forecast future models.

Predictive business analytics uses various statistical techniques to build predictive models that extract data from databases, detect trends, and include a predictive score for a range of organizational outcomes.

It uses quantitative techniques (e.g., propensity, segmentation, network analysis and econometric forecasting) and technology (such as models and rulesystems) that use past data for the future

Predictive analytics generates information from historically available datasets to determine and predict future trends and outcomes. The predictive analysis system encompasses 4 steps: Gathering data on present trends Develop postulates based on present trends Generate argument based description Predict the future.

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D ESCRIPTIV E ANALYTICS (DESCBA):

This uses data mining, data intelligence and web analytics to present the trending information of the near past and current events, helping business models know the demands and drawbacks of the markets.

It provides access to historical and current data. It provides the ability to alert, explore and report using both internal and external data from various sources.

Descriptive analytics is the procedure of parsing historical data to understand the changes in a business to make it better in future.

Contd...

Using a range of historical data and benchmarking, decision-makers obtain a holistic view of performance and trends to base business strategy.

Descriptive analytics can help to recognize the areas of strength and weakness in an organization.

Examples of metrics used in descriptive analytics comprise year-overyear pricing modifications, the number of users, month-over-month sales growth, or the total revenue per subscriber.

Descriptive analytics is now being used in conjunction with newer analytics, such as predictive and prescriptive analytics.

In its simplest form, descriptive analytics answers the question, "What happened?"

Contd...

A mixture of a descriptive-analytical process that provides insight into what happened and a predictive analytical process that provides insight into what might happen helps users predict what will happen, when it will happen and why [8].

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PRESCRIPTIV E ANALYTICS (PREBA):

This uses AI, optimization, and reasoning to provide the most suitable set of models for the organization to choose from, indicating the pros and cons of each.

These layers also contain two interconnected analytics: Inquisitive analytics and Preemptive Analytics. analysis approve/reject prepositions, hile The inquisitive analytics uses statistical w and factor to theof three layers is essential for theproper combinatio and application of Business n architecture.analytics functioning [5]

CONCLUSION

The analysis conducted by most published studies shows that IoT has massive potential on businesses across many sectors.

The data collected from IoT implementation allows businesses to increase productivity, which benefits sales and marketing, resource management, growth potential, and profitability.

Since many applications can be accessed on mobile devices, IoT makes users' day-to-day activities much more convenient.

It also helps with inventory management, tracking product use, and tracking sales rates and locations.

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