Tag: Business Intelligence
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Unsupervised ML, K-Means Clustering & Customer Segmentation
Table of Clickable Contents Motivation Methods Open-Source Datasets This file contains the basic information (ID, age, gender, income, and spending score) about the customers. Online retail is a transnational data set which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail. The company mainly sells unique all-occasion…
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Working with FRED API in Python: U.S. Recession Forecast & Beyond
The FRED API, or Federal Reserve Economic Data, provides over 267,000 economic time series from 80 sources, offering a wealth of data to promote economic education and research. It encompasses U.S. economic and financial data, including interest rates, monetary indicators, exchange rates, and regional economic data. Additionally, we analyzed correlations, trained currency exchange prediction models,…
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SARIMAX Forecasting of Online Food Delivery Sales
This article provides a beginner-friendly guide to understanding and evaluating ARIMA-based time-series forecasting models such as SARIMA and SARIMAX. It focuses on an QC-optimized SARIMA(X) model to forecast the e-commerce sales of a food delivery company. The post covers essential concepts, data processing, model comparisons, and insights. It also includes a comparison between SARIMA and…
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Power BI for Data Scientists
Power BI is a business analytics tool that provides interactive data visualization capabilities, advanced analytics, and artificial intelligence. Power BI’s AI features include image recognition, text analytics, key driver analysis, and machine learning model building. It offers cloud-based services and a desktop-based interface, allowing data preparation, data discovery, and interactive dashboarding. Supported by Windows, Android,…
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US Real Estate – Harnessing the Power of AI
The content describes a continuation of the use-case series dedicated to real estate (RE) monitoring, trend analysis, and forecast. It focuses on predicting and estimating US house prices using a pre-trained ML model. The content covers various machine learning algorithms, data preprocessing, model training, and evaluation using the Boston housing price dataset. Key takeaways include…
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Gulf’s Oil Price Web Scraping in R
Gulf’s Oil Price Web Scraping in R. Gulf states to gain $1.3 trillion in additional oil revenue by 2026: IMF. We discuss the basics of sourcing oil market price data for free online. discuss the basics of sourcing oil market price data for free online. Webscraping in R is a technique to retrieve large amounts…
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Simple E-Commerce Sales BI Analytics
Good businesses learn from previous efforts and test future ideas using e-commerce analytics (ECA). ECA enable you to delve deep into historical BI data, and future forecasting so that you can make the optimized business decisions. The key benefits of ECA are as follows: Let’s look at the warehouse optimization problem by analyzing Kaggle sales…
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