Introduction
Data analysis is the process of examining, organizing, and interpreting data to uncover patterns, trends, and insights. It involves techniques like statistical analysis, data visualization, and cleaning to extract meaningful information. Data analysis supports decision-making, problem-solving, and strategy development across various fields by transforming raw data into actionable knowledge.
Description
Data Analysis or Data Analytics is studying, cleaning, modeling, and transforming data to find useful information, suggest conclusions, and support decision-making. This Data Analytics Tutorial will cover all the basic to advanced concepts of Excel data analysis like data visualization, data preprocessing, time series, data analysis tools, etc. Data Analysis Process Data Analysis is developed by the statistician John Tukey in the 1970s. It is a procedure for analyzing data, methods for interpreting the results of such systems, and modes of planning the group of data to make its analysis easier, more accurate, or more factual. Therefore, data analysis is a process for getting large, unstructured data from different sources and converting it into information that is gone through the below process: Data Requirements Specification Data Collection Data Processing Data Cleaning Data Analysis Communication Data Preprocessing: Data preparation is a critical step in any data analysis or machine learning project. It involves a variety of tasks aimed at transforming raw data into a clean and usable format. Properly prepared data ensures more accurate and reliable analysis results, leading to better decision-making and more effective predictive models. This guide will cover key aspects of data preparation, including data formatting, data cleaning, outlier detection, data transformation, and data sampling.
Details
- Instructor ID: 2
- Duration: 3 months
- Start Date: 2025-04-14
- End Date: 2025-07-14
- Price: ₦70,000.00