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

JULY 7, 2016

Graph Engine: A new graph engine for superior performance and visualization effects. This enhancement further enables crisp, clear visualization and supports the concept of Smart Visualization. GeoMaps: The GeoMaps component supports worldwide GeoMaps visualization. Here are just some of the highlights of version 4.3

Business Intelligence 130

Business Intelligence Business Intelligence Data Discovery Logistics 130

ElegantJ BI

JULY 7, 2016

Graph Engine: A new graph engine for superior performance and visualization effects. This enhancement further enables crisp, clear visualization and supports the concept of Smart Visualization. GeoMaps: The GeoMaps component supports worldwide GeoMaps visualization. Here are just some of the highlights of version 4.3

Business Intelligence 130

Business Intelligence Business Intelligence Data Discovery Logistics 130

ElegantJ BI

JULY 7, 2016

Graph Engine: A new graph engine for superior performance and visualization effects. This enhancement further enables crisp, clear visualization and supports the concept of Smart Visualization. GeoMaps: The GeoMaps component supports worldwide GeoMaps visualization. Here are just some of the highlights of version 4.3

Business Intelligence 130

Business Intelligence Business Intelligence Data Discovery Logistics 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

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

SEPTEMBER 9, 2021

About Smarten The Smarten approach to augmented analytics and modern business intelligence focuses on the business user and provides tools for Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.

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. 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

Its customers include well-renowned entities in banking, life and general insurance and non-banking finance companies in India. ElegantJ BI provides deep dive analytics and dazzling visualization without the need for user-technical skills and offers a driving force in analytics around the world.

Data Discovery 130

Data Discovery Banking Business Intelligence Business Intelligence 130

ElegantJ BI

AUGUST 11, 2017

Its customers include well-renowned entities in banking, life and general insurance and non-banking finance companies in India. ElegantJ BI provides deep dive analytics and dazzling visualization without the need for user-technical skills and offers a driving force in analytics around the world.

Data Discovery 130

Data Discovery Banking Business Intelligence Business Intelligence 130

ElegantJ BI

AUGUST 14, 2018

Business Problem: A bank marketing manager wishes to analyze which products are frequently and sequentially bought together. Business Benefit: Based on the rules generated, the organization can determine which banking products can be cross sold to each existing or prospective customer to drive sales and bank revenue.

Banking 130

Banking Data Discovery 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

AUGUST 14, 2018

Use Case – 2 Business Problem: A bank marketing manager wishes to analyze which products are frequently and sequentially bought together. Business Benefit: Based on the rules generated, the organization can determine which banking products can be cross sold to each existing or prospective customer to drive sales and bank revenue.

Banking 130

Banking Data Discovery Business Intelligence Business Intelligence 130

ElegantJ BI

OCTOBER 16, 2018

Use Case – 1 Business Problem: A bank loan officer wants to predict if the loan applicant will default on a loan, based attributes such as Loan amount, monthly payment installments, employment tenure, number of times delinquent, annual income, debt to income ratio etc. How Can SVM Classification Analysis Benefit Business Analytics?

Banking 130

Banking Data Discovery Business Intelligence Business Intelligence 130

ElegantJ BI

AUGUST 14, 2018

Use Case – 2 Business Problem: A bank marketing manager wishes to analyze which products are frequently and sequentially bought together. Business Benefit: Based on the rules generated, the organization can determine which banking products can be cross sold to each existing or prospective customer to drive sales and bank revenue.

Banking 130

Banking Data Discovery Business Intelligence Business Intelligence 130

ElegantJ BI

OCTOBER 16, 2018

Use Case – 1 Business Problem: A bank loan officer wants to predict if the loan applicant will default on a loan, based attributes such as Loan amount, monthly payment installments, employment tenure, number of times delinquent, annual income, debt to income ratio etc. How Can SVM Classification Analysis Benefit Business Analytics?

Banking 130

Banking Data Discovery Business Intelligence Business Intelligence 130

ElegantJ BI

OCTOBER 16, 2018

Business Problem: A bank loan officer wants to predict if the loan applicant will default on a loan, based attributes such as Loan amount, monthly payment installments, employment tenure, number of times delinquent, annual income, debt to income ratio etc. How Can SVM Classification Analysis Benefit Business Analytics? Use Case – 1.

Banking 130

Banking Data Discovery Business Intelligence Business Intelligence 130

ElegantJ BI

JUNE 13, 2017

We have people who deal with banks, customers and systems. I remember years ago the union of the Communist Party of India in the Public Sector Banks in India went on strike against computerization. If you look at the shape of banking today, we can eventually look at only decision makers sitting at the front desk.

Banking 195

Banking Logistics Finance Planning 195

ElegantJ BI

MAY 20, 2016

ElegantJ BI has created a clear roadmap toward ‘Smart Data Discovery’ that promotes self-serve data preparation, smart visualization, and Plug n’ Play predictive analytics , to put the power of BI tools in the hands of business users to transform them into citizen data scientists. .”

Business Intelligence 130

Business Intelligence Business Intelligence Data Discovery Logistics 130

ElegantJ BI

SEPTEMBER 19, 2021

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. Business Use Case 2 Business Problem: Predict quality of Red Wine.

Data Discovery 130

Data Discovery Banking Business Intelligence Business Intelligence 130

ElegantJ BI

MAY 20, 2016

ElegantJ BI has created a clear roadmap toward ‘Smart Data Discovery’ that promotes self-serve data preparation, smart visualization, and Plug n’ Play predictive analytics , to put the power of BI tools in the hands of business users to transform them into citizen data scientists. .”

Business Intelligence 130

Business Intelligence Business Intelligence Data Discovery Logistics 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

MAY 20, 2016

ElegantJ BI has created a clear roadmap toward ‘Smart Data Discovery’ that promotes self-serve data preparation, smart visualization, and Plug n’ Play predictive analytics , to put the power of BI tools in the hands of business users to transform them into citizen data scientists.

Business Intelligence 130

Business Intelligence Business Intelligence Data Discovery Logistics 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. How Can the Karl Pearson Correlation Method Be Used to Target Enterprise Analytical Needs?

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. How Can the Karl Pearson Correlation Method Be Used to Target Enterprise Analytical Needs?

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. How Can the Karl Pearson Correlation Method Be Used to Target Enterprise Analytical Needs?

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? Loan applicants in a bank might be grouped as low, medium, and high risk applicants based on applicant age, annual income, employment tenure, loan amount, the number of times a payment is delinquent etc.

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? Loan applicants in a bank might be grouped as low, medium, and high risk applicants based on applicant age, annual income, employment tenure, loan amount, the number of times a payment is delinquent etc.

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? Loan applicants in a bank might be grouped as low, medium, and high risk applicants based on applicant age, annual income, employment tenure, loan amount, the number of times a payment is delinquent etc. Use Case – 2.

Data Discovery 130

Data Discovery Business Intelligence Business Intelligence Banking 130

ElegantJ BI

OCTOBER 18, 2018

Use Case – 2 Business Problem: A bank-marketing manager wishes to analyze which products are frequently and sequentially bought together. Business Benefit: Based on the rules generated, banking products can be cross-sold to each existing or prospective customer to drive sales and bank revenue.

Business Analysis 130

Business Analysis Business Analysis Banking Data Discovery 130

ElegantJ BI

OCTOBER 18, 2018

Use Case – 2 Business Problem: A bank-marketing manager wishes to analyze which products are frequently and sequentially bought together. Business Benefit: Based on the rules generated, banking products can be cross-sold to each existing or prospective customer to drive sales and bank revenue.

Business Analysis 130

Business Analysis Business Analysis Banking Data Discovery 130

ElegantJ BI

OCTOBER 18, 2018

Business Problem: A bank-marketing manager wishes to analyze which products are frequently and sequentially bought together. Business Benefit: Based on the rules generated, banking products can be cross-sold to each existing or prospective customer to drive sales and bank revenue. Use Case – 2.

Business Analysis 130

Business Analysis Business Analysis Banking Data Discovery 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. The Smarten approach to data discovery is designed as an augmented analytics solution to serve business users.

Data Discovery 130

Data Discovery Retail Banking Business Intelligence 130