I specialize in cleaning and preprocessing raw data to make it ready for analysis or reporting. This includes removing duplicates, handling missing values, standardizing data formats, and correcting inconsistencies. By transforming messy data into a clean, structured format, I ensure that you can get accurate and reliable insights from your datasets.

Duplicate Removal: Identifying and removing duplicate records to ensure your data is accurate and not skewed by repetitions.

Handling Missing Values: Applying strategies to manage missing or incomplete data, such as imputation or deletion, depending on the situation.

Data Transformation: Standardizing data formats (e.g., date formats, numerical values) to ensure consistency across the dataset.

Error Correction: Identifying and correcting data entry errors, outliers, and inconsistencies that could affect analysis accuracy.

Data Normalization: Scaling or normalizing data to ensure it fits into the analysis models smoothly.

Share Your Raw Data: Provide the dataset that needs cleaning (in any format: Excel, CSV, etc.).

Define the Goals: We’ll discuss your objectives, such as preparing data for analysis or reporting.

Data Cleaning & Preprocessing: I will clean the data by removing duplicates, handling missing values, and standardizing formats to make it analysis-ready.

Deliverable & Review: You’ll receive the cleaned dataset along with a summary of the changes made. We’ll schedule a review to address any questions or adjustments.

"The cleaned data was exactly what we needed to move forward with our analysis. Great job!"

"Thanks for handling the missing values and duplicates. The dataset now runs much smoother!"

"The preprocessing was spot on. We could start our analysis right away, without any data issues!"