Assignment 2

Assignment 2 for the BA Business Management program, focusing on data handling and business intelligence. The assignment requires a report with a word count of 2500 words and carries a weightage of 75%. Submission details include electronic submission on Moodle and the requirement to include a reference list.

Toyota

Mining Methods

This assignment focuses on data handling and business intelligence. It covers the analysis of profit and sales using Excel, explores various data mining methods, and discusses the importance of business intelligence. Real-time examples and techniques such as lookup, pivot tables, graphs, and charts are also demonstrated.

University of Southeastern Philippines

Data Science and Big Data

Statistics and Probability

Data Handling and Business Intelligence

This document provides an introduction to data mining and business intelligence methods used for analyzing and extracting information from large datasets. It focuses on the analysis of superstore data using Excel functions and the conjunction of audidealership data with Weka software. The document also discusses the advantages and disadvantages of Weka over Excel.

Artificial Intelligence

This report discusses the use of Excel for data analysis and visualization, focusing on the decline in sales and profits over the years. It also explores the workings of WEKA using audidealership.csv and analyzes various data mining methods used in business. The advantages and disadvantages of WEKA over Excel are also discussed.

This document discusses the concept of data handling and its importance in processing, analyzing, and presenting data. It evaluates the use of Excel and Weka for data analysis, specifically using the Superstore and audidealership datasets. The report explores current trends in data warehousing, business intelligence, and data mining. It also provides insights into the advantages and disadvantages of using Excel and Weka for data analysis. The document includes an analysis of the Superstore data using Excel functions and visualizations, as well as an explanation of the workings of Weka clustering. Additionally, it discusses the most common data mining methods used in businesses.

Professional Development

Data Handling: Evaluating Excel and Weka for Data Analysis

Microsoft Excel

This report explores the concepts of data handling and business intelligence, focusing on data analytics and predictive analytic software. It evaluates the use of Microsoft Excel for pre-processing, analyzing, and visualizing data. The advantages and disadvantages of Weka over Excel are discussed. Different data mining methods and their real-world applications are explained. Additionally, suggestions for additional columns in audidealership1.csv are provided.

Philippine School of Business Administration

This report explores the concepts of data handling and business intelligence, focusing on the use of Excel for pre-processing, analyzing, and visualizing data. It evaluates the decline in sales/profits using Superstore data. The report also discusses the workings of WEKA and common data mining methods. It provides insights into the subject of data handling and business intelligence.

Toyota

Data Handling and Business Intelligencelg...

Data Handling and Business Intelligencelg...

Data Handling and Business Intelligencelg...

Data Handling: Evaluating Excel and Weka for Data Analysislg...

Data Handling and Business Intelligencelg...

Data Handling and Business Intelligencelg...

Data Handling and Business Intelligence

Data Handling and Business Intelligence

Data Handling and Business Intelligence

Data Handling: Evaluating Excel and Weka for Data Analysis

Data Handling and Business Intelligence

Data Handling and Business Intelligence