Data Analysis
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Data Scrapping
Data scraping is a technique used to extract large amounts of information from websites and online sources. It involves automated tools or software programs designed to gather data from web pages quickly and efficiently.With data scraping, you gain access to valuable insights and information that can drive better decision-making and give your business a competitive edge.
Exploratory Data Analysis
Exploratory Data Analysis (EDA) is a critical process in data science and analytics that involves examining and visualizing datasets to uncover patterns, trends, and relationships. EDA helps in understanding the data's underlying structure and extracting meaningful insights.
EDA is an essential step in any data analysis workflow, providing a foundation for more complex data modeling and ensuring that subsequent analyses are based on a solid understanding of the data.
Data Cleaning
Remove Duplicates: Eliminate duplicate entries to prevent redundancy.
Handle Missing Values: Fill in missing data or remove incomplete records.
Correct Errors: Fix typos, formatting issues, and incorrect values.
Standardize Data: Ensure data follows a consistent format and structure.
Validate Data: Check for accuracy and consistency across different data sources.
Visualization Dashboards
A visualization dashboard is an interactive tool that displays data in a visual format, making it easy to monitor, analyze, and understand key metrics and trends at a glance. Dashboards aggregate data from multiple sources and present it in charts, graphs, and other visual elements, providing users with actionable insights.