Unite.AI

NOVEMBER 13, 2024

What inspired you to focus on data observability when you founded Acceldata in 2018, and what gaps in the data management industry did you aim to fill? My journey to founding Acceldata in 2018 began nearly 20 years ago as a software engineer, where I was driven to identify and solve problems with software.

Machine Learning 147

Machine Learning Large Language Models Data Quality Automation 147

The MLOps Blog

JUNE 27, 2023

Data quality control: Robust dataset labeling and annotation tools incorporate quality control mechanisms such as inter-annotator agreement analysis, review workflows, and data validation checks to ensure the accuracy and reliability of annotations. Data monitoring tools help monitor the quality of the data.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

Unite.AI

DECEMBER 13, 2024

Prior to Yanolja, Junyoung had a distinguished career at Google, where he worked for nearly two decades in various roles, including Software Engineer, Engineering Manager, and Engineering Director. Second, data is the foundation of AI. At Yanolja, we prioritize data integrity across the entire travel value chain.

Software Engineer 100

Software Engineer Data Quality Data Platform Automation 100

ODSC - Open Data Science

SEPTEMBER 27, 2023

Relational Databases Some key characteristics of relational databases are as follows: Data Structure: Relational databases store structured data in rows and columns, where data types and relationships are defined by a schema before data is inserted.

Big Data 98

Big Data Metadata ETL Data Science 98

Pickl AI

JULY 25, 2023

They work with databases and data warehouses to ensure data integrity and security. Data Integration and ETL (Extract, Transform, Load) Data Engineers develop and manage data pipelines that extract data from various sources, transform it into a suitable format, and load it into the destination systems.

Data Science 52

Data Science Data Scientist ETL Machine Learning 52

Pickl AI

OCTOBER 2, 2024

Summary: Artificial Intelligence (AI) is revolutionising Genomic Analysis by enhancing accuracy, efficiency, and data integration. Despite challenges like data quality and ethical concerns, AI’s potential in genomics continues to grow, shaping the future of healthcare.

Neural Network 52

Neural Network Deep Learning Machine Learning Artificial Intelligence 52

ODSC - Open Data Science

SEPTEMBER 13, 2024

Data Integration GraphRAG can integrate and analyze data from multiple sources. By representing data as a graph, it becomes easier to combine and analyze information from diverse datasets, leading to more comprehensive insights.

Data Science 40

Data Science Artificial Intelligence Artificial Intelligence Natural Language Processing 40