Remove Data Integration Remove Data Quality Remove Interactive
article thumbnail

The Race For Data Quality in a Medallion Architecture

DataKitchen

The Race For Data Quality In A Medallion Architecture The Medallion architecture pattern is gaining traction among data teams. It is a layered approach to managing and transforming data. It sounds great, but how do you prove the data is correct at each layer? How do you ensure data quality in every layer ?

article thumbnail

Digital twins at scale: Building the AI architecture that will reshape enterprise operations

CIO Business Intelligence

The virtual representation of the physical entity, constructed using data, algorithms and simulations. Data integration. The process of collecting, processing and integrating data from various sources to ensure the digital twin mirrors the physical entity accurately. Ensure data quality.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Top 10 Analytics And Business Intelligence Trends For 2020

datapine

Data exploded and became big. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. 1) Data Quality Management (DQM). We all gained access to the cloud.

article thumbnail

The quest for high-quality data

O'Reilly on Data

Machine learning solutions for data integration, cleaning, and data generation are beginning to emerge. “AI AI starts with ‘good’ data” is a statement that receives wide agreement from data scientists, analysts, and business owners. Data integration and cleaning. Data unification and integration.

article thumbnail

What gives IT leaders pause as they look to integrate agentic AI with legacy infrastructure

CIO Business Intelligence

The problem is that, before AI agents can be integrated into a companys infrastructure, that infrastructure must be brought up to modern standards. In addition, because they require access to multiple data sources, there are data integration hurdles and added complexities of ensuring security and compliance.

IT 141
article thumbnail

Innovative data integration in 2024: Pioneering the future of data integration

CIO Business Intelligence

In the age of big data, where information is generated at an unprecedented rate, the ability to integrate and manage diverse data sources has become a critical business imperative. Traditional data integration methods are often cumbersome, time-consuming, and unable to keep up with the rapidly evolving data landscape.

article thumbnail

AWS Glue Data Quality is Generally Available

AWS Big Data

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning. It takes days for data engineers to identify and implement data quality rules.