Data Science Dojo

APRIL 29, 2025

You may combine event data (e.g., shot types and results) with tracking data (e.g., Effective data collection ensures you have all the necessary information to begin the analysis, setting the stage for reliable insights into improving shot conversion rates or any other defined problem.

Power BI 195

Power BI Analytics Analytics EDA 195

Alation

JANUARY 20, 2022

Several weeks ago (prior to the Omicron wave), I got to attend my first conference in roughly two years: Dataversity’s Data Quality and Information Quality Conference. Ryan Doupe, Chief Data Officer of American Fidelity, held a thought-provoking session that resonated with me. Step 4: Data Sources. Step 5: Data Profiling.

Data Quality 94

Data Quality Data Governance Data Profiling Clean Data 94

Dataconomy

JULY 28, 2023

By analyzing the sentiment of users towards certain products, services, or topics, sentiment analysis provides valuable insights that empower businesses and organizations to make informed decisions, gauge public opinion, and improve customer experiences. Noise in data can arise due to data collection errors, system glitches, or human errors.

Power BI 91

Power BI Data Preparation Exploratory Data Analysis Machine Learning 91

Pickl AI

OCTOBER 18, 2023

How to Scale Your Data Quality Operations with AI and ML: In the fast-paced digital landscape of today, data has become the cornerstone of success for organizations across the globe. Every day, companies generate and collect vast amounts of data, ranging from customer information to market trends.

Data Quality 52

Data Quality ML ML Machine Learning 52

Pickl AI

JULY 24, 2024

Missing Data Incomplete datasets with missing values can distort the training process and lead to inaccurate models. Missing data can occur due to various reasons, such as data entry errors, loss of information, or non-responses in surveys. Both scenarios result in suboptimal model performance.

Data Quality 52

Data Quality Machine Learning Machine Learning Clean Data 52

DagsHub

AUGUST 23, 2024

As a result, Gartner estimates that poor data quality costs organizations an average of $13 million annually. High-quality data significantly reduces the risk of costly errors, and the resulting penalties or legal issues. Data quality is crucial across various domains within an organization.

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 52

Snorkel AI

MAY 12, 2023

For example, when customers log onto our website or mobile app, our conversational AI capabilities can help find the information they may want. To borrow another example from Andrew Ng, improving the quality of data can have a tremendous impact on model performance. This is to say that clean data can better teach our models.

Machine Learning 52

Machine Learning Machine Learning ML ML 52