IBM Journey to AI blog

JULY 13, 2023

This is the practice of creating, updating and consistently enforcing the processes, rules and standards that prevent errors, data loss, data corruption, mishandling of sensitive or regulated data, and data breaches. Effective data security protocols and tools contribute to strong data integrity.

Data Quality 74

Data Quality Data Profiling Data Governance Analytics 74

AWS Machine Learning Blog

FEBRUARY 15, 2024

The predicted value indicates the expected value for our target metric based on the training data. The difference of this value therefore is a metric for the abnormality of the actual data observed. Find anomalies and evaluate anomalous events In a typical setup, the code to obtain anomalies is run in a Lambda function.

ML 119

ML ML AWS Data Science 119

Precisely

MAY 3, 2023

Learn more The countdown is on to Trust ’23: the Precisely Data Integrity Summit! We recently announced the details of our annual virtual event , and we’re thrilled to once again bring together thousands of data professionals worldwide for two days of knowledge, insights, and inspiration for your data integrity journey.

Data Governance 52

Data Governance AWS Data Quality Analytics 52

IBM Journey to AI blog

DECEMBER 19, 2023

As organizations collect larger data sets with potential insights into business activity, detecting anomalous data, or outliers in these data sets, is essential in discovering inefficiencies, rare events, the root cause of issues, or opportunities for operational improvements.

Machine Learning 82

Machine Learning Machine Learning Supervised Learning K-nearest Neighbors 82

ODSC - Open Data Science

JANUARY 11, 2024

Getting Started with AI in High-Risk Industries, How to Become a Data Engineer, and Query-Driven Data Modeling How To Get Started With Building AI in High-Risk Industries This guide will get you started building AI in your organization with ease, axing unnecessary jargon and fluff, so you can start today.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Precisely

FEBRUARY 2, 2023

Business managers are faced with plotting the optimal course in the face of these evolving events. And this confidence requires data quality controls that include machine-learning models to recognize whether the appropriate rules are applied to your data and flexible data governance tools that can adapt to different business scenarios.

Data Silos 52

Data Silos Data Pipeline Database Data Observability 52

DagsHub

AUGUST 23, 2024

Data Quality Dimensions Data quality dimensions are the criteria that are used to evaluate and measure the quality of data. These include the following: Accuracy indicates how correctly data reflects the real-world entities or events it represents. Datafold is a tool focused on data observability and quality.

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 52

Heartbeat

MAY 30, 2023

It provides sensory data (observations) and rewards to the agent, and the agent acts in the environment based on its policy. How does DRL work? The environment and the agent are the two main components of DRL. The agent operates in a simulated or physical world called the environment.

Deep Learning 72

Deep Learning Deep Learning Machine Learning Machine Learning 72

The MLOps Blog

JUNE 27, 2023

Talend Data Quality Talend Data Quality is a comprehensive data quality management tool with data profiling, cleansing, and monitoring features. With Talend, you can assess data quality, identify anomalies, and implement data cleansing processes.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

ODSC - Open Data Science

JANUARY 9, 2024

Data engineers act as gatekeepers that ensure that internal data standards and policies stay consistent. Data Observability and Monitoring Data observability is the ability to monitor and troubleshoot data pipelines. Interested in attending an ODSC event?

Data Engineering 97

Data Engineering Data Engineering Data Engineer Data Engineering 97

IBM Journey to AI blog

JUNE 5, 2024

That’s why today’s application analytics platforms rely on artificial intelligence (AI) and machine learning (ML) technology to sift through big data, provide valuable business insights and deliver superior data observability. What are application analytics? Predictive analytics.

Analytics 94

Analytics Analytics AI AI 94

Precisely

FEBRUARY 9, 2024

For instance, a data breach or violation of privacy standards can lead to liability, expensive fines, and a slew of negative publicity that’s a hit to brand reputation and trustworthiness. location-specific attributes and spatial insights that provide context to support stronger overall risk management.

Data Quality 69

Data Quality DataOps Data Silos Artificial Intelligence 69

Pickl AI

MARCH 19, 2025

Apache Spark Apache Spark is a powerful data processing framework that efficiently handles Big Data. It supports batch processing and real-time streaming, making it a go-to tool for data engineers working with large datasets. Apache Kafka Apache Kafka is a distributed event streaming platform used for real-time data processing.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52