Finalytica July, 2020: Knowledge Series

Price Optimisation through Machine Learning for Retail Stores


Price optimisation refers to determining the prices of products/services such that the company can achieve its business objectives. In recent times, there have been major technical advancements in this field with more reliable and faster techniques.… Continue reading

Finalytica Feb, 2020: Knowledge Series

An overview of clustering in analytics

Just as the name suggests, clustering aims at creating clusters of the subject matter at hand, based on the various properties it possesses. This can be pretty useful when it comes to classifying elements in the future, into one of these clusters or in terms of establishing patterns in the data.… Continue reading

Finalytica, Knowledge Series: Jan, 2020

Time Series 101 : Everything you need to know about Time Series

Time is always an important factor when it comes to observing patterns or forecasting trends, be it predicting stock prices or future sales of products. For example, if the expected sales of a product are supposed to take a hit, a company can take various measures to stunt that fall or even improve the performances.… Continue reading

Finalytica: Experential Learning, Dec 2019

Credit Risk Assessment

Credit Risk assessment is a critical issue that Banks face nowadays. Which basically tells if a loan applicant can be a defaulter, so they can go ahead and grant the loan or not. This helps the banks to minimize the possible losses and can increase the volume of credit given.… Continue reading

Finalytica Nov-2019: Experential Learnings

AI Driven Narrator Chatbot – Use Cases

A chatbot is a machine that has a conversation with humans via text or audio. An AI powered chatbot is a smarter version which uses natural language processing (NLP) and machine learning (ML) to better understand the intent of the data and provide a more natural, accurate insight.… Continue reading

Finalytica, October, 2019: Experential Learning

Automated MIS Reports and triggers application through BI tool – Narrator


A MIS Automation is an automatedreport, analysis of business or management information organized and programmed in such a way that it produces regular reports on operations for every level of management hierarchy in organization.… Continue reading

G-square's narrator

Finalytica July, 2019: Experiential Learning

Prescriptive Analytics for Sales: Combining Analytics with Business Understanding

BI and reports have been driving salesforce in an organization for some time now. But building reports manually on a monthly / weekly / regular basis is daunting, boring, and error prone.… Continue reading

Finalytica June, 2019: Experential Learning

Credit Risk Rating Using Supervised ML and Business Understanding

The risk rating models are designed to help assess the likelihood of default. Assessing risk at the loan level provides an opportunity to aggregate risk at the portfolio level and can help to quantify the risks based on the type of loan, geographic location or region, industry sector, or other variables including financials.… Continue reading

Finalytica May, 2019: Experential Learning

Converting Content to a Chat-Bot

The best way to learn or understand information is through asking questions. A QnA format of learning is more effective than reading long form content, especially when time is critical. More over searching for an information and reading multiple documents just to know one thing is inefficient.… Continue reading

Finalytica April, 2019: Experential Learning

G-Square Architecture for Unified Analytics

G-Square Solutions provides a complete package/architecture for unified analytics, which helps its clients in achieving various analytics & machine learning tasks right from the ETL of data to its final analytical usage. It is a light weight and pocket friendly architecture, widely present in the market.… Continue reading

Finalytica April, 2019: Knowledge Series

Light Weight Architecture for Unified Analytics

Unified Analytics is a new set of solutions that unify data processing right from the ETL of the data from client’s database – setting up organized staging platform (Data Warehouse) for structured & unstructured data & usage of AI technologies with the transformed data to have a 10k feet view of the business & identify hidden business opportunities.… Continue reading

Finalytica March, 2019: Knowledge Series

Too many cooks make the broth tastier.


Incorrect is the old adage: Too many cooks spoil the broth.

Updated adage in this age of AI and ML: Too many models make the accuracy higher.

Ensemble Learning in Machine Learning is when more than one machine learning algorithms merge to produce a better and more robust decision model, even though individually, they may be weak or average in predictions.… Continue reading