Smart Data Collective

JULY 15, 2021

You can think of a data catalog as an enhanced Access database or library card catalog system. It helps you locate and discover data that fit your search criteria. With data catalogs, you won’t have to waste time looking for information you think you have. What Does a Data Catalog Do?

Data Quality 133

Data Quality Database Data Pipeline Data Observability 133

The MLOps Blog

JUNE 27, 2023

It integrates with Git and provides a Git-like interface for data versioning, allowing you to track changes, manage branches, and collaborate with data teams effectively. Dolt Dolt is an open-source relational database system built on Git. It could help you detect and prevent data pipeline failures, data drift, and anomalies.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

Precisely

FEBRUARY 2, 2023

Pipelines must have robust data integration capabilities that integrate data from multiple data silos, including the extensive list of applications used throughout the organization, databases and even mainframes. Changes to one database must also be reflected in any other database in real time.

Data Pipeline 52

Data Pipeline Data Silos Database Data Observability 52

phData

AUGUST 10, 2023

The implementation of a data vault architecture requires the integration of multiple technologies to effectively support the design principles and meet the organization’s requirements. The most important reason for using DBT in Data Vault 2.0 is its ability to define and use macros.

SQL 52

SQL Data Observability Data Quality Data Pipeline 52

Pickl AI

JUNE 7, 2024

It involves retrieving data from various sources, such as databases, spreadsheets, or even cloud storage. The goal is to collect relevant data without affecting the source system’s performance. Compatibility with Existing Systems and Data Sources Compatibility is critical. How to drop a database in SQL server?

ETL 40

ETL Data Quality Data Pipeline Data Warehouse 40

Precisely

MARCH 14, 2023

Manage data with a seamless, consistent design experience – no need for complex coding or highly technical skills. Simply design data pipelines, point them to the cloud environment, and execute. What does all this mean for your business?

Data Quality 52

Data Quality Cloud Data Data Pipeline Data Observability 52

IBM Journey to AI blog

DECEMBER 16, 2022

Because Alex can use a data catalog to search all data assets across the company, she has access to the most relevant and up-to-date information. She can search structured or unstructured data, visualizations and dashboards, machine learning models, and database connections.

Data Quality 52

Data Quality Data Governance Data Scientist Data Wrangling 52

Precisely

APRIL 15, 2025

And yet, many data leaders struggle to trust their AI-driven insights due to poor data observability. In fact, only 59% of organizations trust their AI/ML model inputs and outputs , according to the latest BARC Data Observability Survey: Observability for AI Innovation.

Data Observability 69

Data Observability Data Quality Data Pipeline ML 69

Pickl AI

MARCH 19, 2025

Summary: Data engineering tools streamline data collection, storage, and processing. Learning these tools is crucial for building scalable data pipelines. offers Data Science courses covering these tools with a job guarantee for career growth. What Does a Data Engineer Do?

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52