ElegantJ BI

SEPTEMBER 9, 2021

Business Benefit: Loan applicant’s can discover what predictors can lead towards the required loan amount to be eligible for further proceedings in turn ensuring systematic banking approach and also assist banks to check the loan eligibility criteria before sanctioning a loan to the applicant. Use Case – 2.

Data Discovery 130

Data Discovery Banking Business Intelligence Business Intelligence 130

ElegantJ BI

SEPTEMBER 9, 2021

Business Benefit: Loan applicant’s can discover what predictors can lead towards the required loan amount to be eligible for further proceedings in turn ensuring systematic banking approach and also assist banks to check the loan eligibility criteria before sanctioning a loan to the applicant. Business Use Case – Agriculture.

Data Discovery 130

Data Discovery Banking Business Intelligence Business Intelligence 130

ElegantJ BI

AUGUST 11, 2017

The ElegantJ BI business intelligence solution is powered by unique Managed Memory Computing and the Smarten approach to advanced data analytics. Its customers include well-renowned entities in banking, life and general insurance and non-banking finance companies in India.

Data Discovery 204

Data Discovery Banking Business Intelligence Business Intelligence 204

ElegantJ BI

SEPTEMBER 19, 2021

Business Use Case 2 Business Problem: Predict quality of Red Wine. The data is a result of analysis to determine the quality of the red wine based upon chemicals it consists of. The Smarten approach to data discovery is designed as an augmented analytics solution to serve business users.

Data Discovery 130

Data Discovery Banking Business Intelligence Business Intelligence 130

ElegantJ BI

SEPTEMBER 19, 2021

Business Benefit: The predictive model will help us identify whether a customer fails to repay the loan depending on certain factors, which would lead to easier identification of risky customers and help the bank avert the risk delinquencies. Business Use Case 2. Business Problem: Predict quality of Red Wine.

Data Discovery 130

Data Discovery Banking Business Intelligence Business Intelligence 130

ElegantJ BI

SEPTEMBER 19, 2021

Business Benefit: The predictive model will help us identify whether a customer fails to repay the loan depending on certain factors, which would lead to easier identification of risky customers and help the bank avert the risk delinquencies. Business Use Case 2. Business Problem: Predict quality of Red Wine.

Data Discovery 130

Data Discovery Banking Business Intelligence Business Intelligence 130

ElegantJ BI

OCTOBER 16, 2018

Let’s look at two examples: Based on the historical data related to credit card payments, loan payments, delinquency rate, outstanding balance we want to classify/divide the customers into those who default and those who do not default. a bank needs to classify customers into those that will default and those that will not default.

Banking 162

Banking Retail Data Discovery Business Intelligence 162

ElegantJ BI

OCTOBER 16, 2018

Business Problem: A bank wants to group loan applicants into high/medium/low risk based on attributes such as loan amount, monthly installments, employment tenure, the number of times the applicant has been delinquent in other payments, annual income, debt to income ratio etc. Use Case – 2.

Banking 130

Banking Data Discovery Business Intelligence Business Intelligence 130

ElegantJ BI

OCTOBER 17, 2018

Business Problem: A bank loans officer wants to predict if loan applicants will be a bank defaulter or non defaulter based on attributes such as loan amount, monthly installments, employment tenure, how many times has the applicant been delinquent, annual income, debt to income ratio etc. Use Case – 1.

Logistics 130

Logistics Banking Data Discovery Business Intelligence 130

ElegantJ BI

OCTOBER 16, 2018

Use Case – 1 Business Problem: A bank wants to group loan applicants into high/medium/low risk based on attributes such as loan amount, monthly installments, employment tenure, the number of times the applicant has been delinquent in other payments, annual income, debt to income ratio etc.

Banking 130

Banking Data Discovery Business Intelligence Business Intelligence 130

ElegantJ BI

OCTOBER 16, 2018

Use Case – 1 Business Problem: A bank wants to group loan applicants into high/medium/low risk based on attributes such as loan amount, monthly installments, employment tenure, the number of times the applicant has been delinquent in other payments, annual income, debt to income ratio etc.

Banking 130

Banking Data Discovery Business Intelligence Business Intelligence 130

ElegantJ BI

OCTOBER 17, 2018

Use Case – 1 Business Problem: A bank loans officer wants to predict if loan applicants will be a bank defaulter or non defaulter based on attributes such as loan amount, monthly installments, employment tenure, how many times has the applicant been delinquent, annual income, debt to income ratio etc.

Logistics 130

Logistics Banking Data Discovery Business Intelligence 130

ElegantJ BI

OCTOBER 17, 2018

Use Case – 1 Business Problem: A bank loans officer wants to predict if loan applicants will be a bank defaulter or non defaulter based on attributes such as loan amount, monthly installments, employment tenure, how many times has the applicant been delinquent, annual income, debt to income ratio etc.

Logistics 130

Logistics Banking Data Discovery Business Intelligence 130

ElegantJ BI

OCTOBER 18, 2018

KNN Classification analysis can be useful in evaluating many types of data. Credit/Loan Approval Analysis – Given a list of client transactional attributes, the business can predict whether a client will default on a bank loan. Weather Prediction – Based on temperature, humidity, pressure etc., Use Case – 1.

Banking 130

Banking Data Discovery Business Intelligence Business Intelligence 130

ElegantJ BI

OCTOBER 16, 2018

How Can SVM Classification Analysis Benefit Business Analytics? Let’s examine two business use cases where SVM Classification can benefit the organization. Business Benefit: Once classes are assigned, the bank will have a loan applicant dataset with each applicant labeled as “likely/unlikely to default”.

Banking 130

Banking Data Discovery Business Intelligence Business Intelligence 130

ElegantJ BI

OCTOBER 18, 2018

KNN Classification analysis can be useful in evaluating many types of data. Credit/Loan Approval Analysis – Given a list of client transactional attributes, the business can predict whether a client will default on a bank loan. Weather Prediction – Based on temperature, humidity, pressure etc.,

Banking 130

Banking Data Discovery Business Intelligence Business Intelligence 130

ElegantJ BI

OCTOBER 18, 2018

KNN Classification analysis can be useful in evaluating many types of data. Credit/Loan Approval Analysis – Given a list of client transactional attributes, the business can predict whether a client will default on a bank loan. Weather Prediction – Based on temperature, humidity, pressure etc.,

Banking 130

Banking Data Discovery Business Intelligence Business Intelligence 130

ElegantJ BI

AUGUST 11, 2017

The ElegantJ BI business intelligence solution is powered by unique Managed Memory Computing and the Smarten approach to advanced data analytics. Its customers include well-renowned entities in banking, life and general insurance and non-banking finance companies in India.

Data Discovery 130

Data Discovery Banking Business Intelligence Business Intelligence 130

ElegantJ BI

AUGUST 11, 2017

The ElegantJ BI business intelligence solution is powered by unique Managed Memory Computing and the Smarten approach to advanced data analytics. Its customers include well-renowned entities in banking, life and general insurance and non-banking finance companies in India.

Data Discovery 130

Data Discovery Banking Business Intelligence Business Intelligence 130

ElegantJ BI

OCTOBER 16, 2018

Let’s look at two examples: Based on the historical data related to credit card payments, loan payments, delinquency rate, outstanding balance we want to classify/divide the customers into those who default and those who do not default. a bank needs to classify customers into those that will default and those that will not default.

Banking 130

Banking Retail Data Discovery Business Intelligence 130

ElegantJ BI

OCTOBER 16, 2018

Let’s look at two examples: Based on the historical data related to credit card payments, loan payments, delinquency rate, outstanding balance we want to classify/divide the customers into those who default and those who do not default. a bank needs to classify customers into those that will default and those that will not default.

Banking 130

Banking Retail Data Discovery Business Intelligence 130

ElegantJ BI

OCTOBER 16, 2018

How Can SVM Classification Analysis Benefit Business Analytics? Let’s examine two business use cases where SVM Classification can benefit the organization. Business Benefit: Once classes are assigned, the bank will have a loan applicant dataset with each applicant labeled as “likely/unlikely to default”.

Banking 130

Banking Data Discovery Business Intelligence Business Intelligence 130

ElegantJ BI

OCTOBER 16, 2018

How Can SVM Classification Analysis Benefit Business Analytics? Let’s examine two business use cases where SVM Classification can benefit the organization. Business Benefit: Once classes are assigned, the bank will have a loan applicant dataset with each applicant labeled as “likely/unlikely to default”.

Banking 130

Banking Data Discovery Business Intelligence Business Intelligence 130

ElegantJ BI

OCTOBER 17, 2018

Business Problem: A bank wants to find the correlation between income and credit card delinquency rate of credit card holders. Input Data: The delinquency rate of each credit card customer and the monthly income of each credit card customer.

Data Discovery 130

Data Discovery Business Intelligence Business Intelligence Banking 130

ElegantJ BI

AUGUST 10, 2018

How Does an Enterprise Use the KMeans Clustering Algorithm to Analyze Data? In order to understand how best to make use of this algorithm; let’s look at some general examples, followed by some business use cases. Use Case – 2.

Data Discovery 130

Data Discovery Business Intelligence Business Intelligence Banking 130

ElegantJ BI

OCTOBER 17, 2018

Business Problem: A bank wants to find the correlation between income and credit card delinquency rate of credit card holders. Input Data: The delinquency rate of each credit card customer and the monthly income of each credit card customer.

Data Discovery 130

Data Discovery Banking Business Intelligence Business Intelligence 130

ElegantJ BI

OCTOBER 17, 2018

Business Problem: A bank wants to find the correlation between income and credit card delinquency rate of credit card holders. Input Data: The delinquency rate of each credit card customer and the monthly income of each credit card customer.

Data Discovery 130

Data Discovery Banking Business Intelligence Business Intelligence 130

ElegantJ BI

AUGUST 10, 2018

How Does an Enterprise Use the KMeans Clustering Algorithm to Analyze Data? In order to understand how best to make use of this algorithm; let’s look at some general examples, followed by some business use cases. The Smarten approach to data discovery is designed as an augmented analytics solution to serve business users.

Data Discovery 130

Data Discovery Banking Business Intelligence Business Intelligence 130

ElegantJ BI

AUGUST 10, 2018

How Does an Enterprise Use the KMeans Clustering Algorithm to Analyze Data? In order to understand how best to make use of this algorithm; let’s look at some general examples, followed by some business use cases. The Smarten approach to data discovery is designed as an augmented analytics solution to serve business users.

Data Discovery 130

Data Discovery Banking Business Intelligence Business Intelligence 130

ElegantJ BI

OCTOBER 18, 2018

a business can predict the likelihood of fraud. Business Problem: A bank loans officer wants to predict if a loan applicant will be a bank defaulter or non defaulter based on attributes such as loan amount, monthly installment, employment tenure, the number of times delinquent, annual income, debt to income ratio etc.

Banking 130

Banking Data Discovery Business Intelligence Business Intelligence 130

ElegantJ BI

OCTOBER 18, 2018

a business can predict the likelihood of fraud. Use Case – 1 Business Problem: A bank loans officer wants to predict if a loan applicant will be a bank defaulter or non defaulter based on attributes such as loan amount, monthly installment, employment tenure, the number of times delinquent, annual income, debt to income ratio etc.

Banking 130

Banking Data Discovery Business Intelligence Business Intelligence 130

ElegantJ BI

OCTOBER 18, 2018

a business can predict the likelihood of fraud. Use Case – 1 Business Problem: A bank loans officer wants to predict if a loan applicant will be a bank defaulter or non defaulter based on attributes such as loan amount, monthly installment, employment tenure, the number of times delinquent, annual income, debt to income ratio etc.

Banking 130

Banking Data Discovery Business Intelligence Business Intelligence 130

ElegantJ BI

OCTOBER 16, 2018

Finance – An organization might use this technique to Identify if demographic factors influence banking channel/product/service preference or selection of a type of term plan of an insurance etc. How Can the Chi Square Test of Association Be Used for Business Analysis?

Data Discovery 130

Data Discovery Retail Business Intelligence Business Intelligence 130

ElegantJ BI

JULY 6, 2011

ElegantJ BI sponsors a Business Intelligence Conference event as the Silver Partner , organized. This BI conference will be focusing on Business Intelligence aspects with two tracks – Track I is Technical and Track II is Customer Business Value. by Silicon India on 30th July 2011 at Bangalore from 8:00 a.m.

Business Intelligence 100

Business Intelligence Business Intelligence Banking Healthcare 100

ElegantJ BI

OCTOBER 16, 2018

Finance – An organization might use this technique to Identify if demographic factors influence banking channel/product/service preference or selection of a type of term plan of an insurance etc. How Can the Chi Square Test of Association Be Used for Business Analysis?

Data Discovery 130

Data Discovery Retail Banking Business Intelligence 130

ElegantJ BI

OCTOBER 16, 2018

Finance – An organization might use this technique to Identify if demographic factors influence banking channel/product/service preference or selection of a type of term plan of an insurance etc. How Can the Chi Square Test of Association Be Used for Business Analysis?

Data Discovery 130

Data Discovery Retail Banking Business Intelligence 130

ElegantJ BI

MARCH 6, 2016

ElegantJ BI, a leader in Business Intelligence and Corporate Performance Management solutions, is pleased to announce that its suite of Business Intelligence and performance management tools was listed as a representative vendor in the Gartner ‘Market Guide for Enterprise-Reporting-Based Platforms,’ published in February 2016.

Business Intelligence 130

Business Intelligence Business Intelligence Logistics Data Discovery 130