Clean Data, Data Profiling and SQL - Data Science Current

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Clean Data

Data Profiling

SQL

Turn the face of your business from chaos to clarity

Dataconomy

JULY 28, 2023

Data scientists must decide on appropriate strategies to handle missing values, such as imputation with mean or median values or removing instances with missing data. The choice of approach depends on the impact of missing data on the overall dataset and the specific analysis or model being used.

Power BI

Power BI Data Preparation Exploratory Data Analysis Machine Learning

Data Quality Framework: What It Is, Components, and Implementation

DagsHub

AUGUST 23, 2024

Data quality is crucial across various domains within an organization. For example, software engineers focus on operational accuracy and efficiency, while data scientists require clean data for training machine learning models. Without high-quality data, even the most advanced models can't deliver value.

Data Quality

Data Quality Data Governance Machine Learning Machine Learning

Mastering the AI Basics: The Must-Know Data Skills Before Tackling LLMs

ODSC - Open Data Science

APRIL 15, 2025

Data Cleaning: Eliminate theNoise Why it matters : Noisy, incomplete, or inconsistent data can sink even the best-trained model. What youll do: Cleaning involves handling missing values, correcting errors, standardizing formats, and filtering outliers.

Data Wrangling

Data Wrangling Data Science AI AI

Webinars

Mastering Apache Airflow® 3.0: What’s New (and What’s Next) for Data Orchestration

MORE WEBINARS

Turn the face of your business from chaos to clarity

Data Quality Framework: What It Is, Components, and Implementation

Mastering the AI Basics: The Must-Know Data Skills Before Tackling LLMs

Webinars

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