Developed project for the PowerforAlls data analysis project. Integrated a lot of often source code to the Django project and auto indexing documents with opensemanticsearch tool and visualize data with HighCharts and Mapbox.

I have expertise in accounts and finance here is the project of data entry I have done for my clients a few days ago.

This is my data cleansing project

This is a data scraping job portfolio. To complete this work I applied data entry, data mining, data scraping, web scraping , data analysis, big data skills. This was my a successful job.

For an offline company, I input manual data in an Excel sheet.

Types of Data Entry: Specify the types of data you've worked with (textual, numeric, image based, etc.) and mention any specialties (medical, legal, financial, etc.). Accuracy and Speed: Highlight your typing speed and accuracy rates, if available. Mention any tools or software you use to enhance your efficiency. Quality Assurance: Emphasize your attention to detail and quality control measures implemented to ensure accuracy in data entry. Problem Solving: Illustrate instances where you encountered challenges during data entry and how you resolved them. Privacy and Security Awareness

The client needed accurate and organized lead generation data for vacant properties in Pasadena, TX. Their goal was to compile property owner details, including names, addresses, phone numbers, and other relevant contact information, into a well structured Excel sheet for marketing and outreach purposes. Client Goals Create a clean, organized database of property leads. Ensure all contact information was accurate to avoid errors in outreach campaigns. Complete the project within a short timeframe to meet their deadlines. Challenges Encountered Data Accuracy: Some phone numbers and addresses were either incomplete or inconsistent. Solution: I conducted additional online research and cross verified details from reliable databases to ensure the information was accurate and complete. Data Formatting: The client needed the data in a specific format compatible with their CRM software.

The goal of this project is to clean and preprocess the employee dataset to ensure accuracy, consistency, and completeness for further analysis. This involves handling missing values, standardizing data formats, correcting inconsistencies, and removing duplicates to improve data quality.