Precisely

JULY 18, 2024

Data management recommendations and data products emerge dynamically from the fabric through automation, activation, and AI/ML analysis of metadata. A data product is a reusable set of data, metadata, semantics, and templates that are curated and maintained to be immediately useful for specific business objectives.

Data Management 52

Data Management Management Metadata Database-centric 52

Data Engineering Weekly

JULY 2, 2023

Editors Note: 🔥 DEW is thrilled to announce a developer-centric Data Eng & AI conference in the tech hub of Bengaluru, India, on October 12th! Atlan AI leverages metadata that Atlan captures across the data stack to make AI part of your data stack. Can't we use the vector feature in the existing databases?

Data Engineer 52

Data Engineer Data Engineering Engineering Pipeline-centric 52

Monte Carlo

JANUARY 23, 2024

RAG involves integrating a real-time database into the LLM’s response generation process, while fine-tuning trains models on targeted datasets to improve domain-specific responses. That implies working with new patterns like vector databases.” It can show me how it built that chart, which dataset it used, and show me the metadata.”

Database-centric 52

Database-centric Pipeline-centric Metadata Unstructured Data 52

Cloudera

AUGUST 31, 2021

It has a consistent framework that secures and provides governance for all data and metadata on private clouds, multiple public clouds, or hybrid clouds. The data from your existing data warehouse is migrated to the storage option you choose, and all the metadata is migrated into SDX (Shared Data Experiences) layer of Cloudera Data Platform.

Data Warehouse 81

Data Warehouse Database-centric Metadata Cloud 81

Confluent

MAY 9, 2019

Storing events in a stream and connecting streams via stream processors provide a generic, data-centric, distributed application runtime that you can use to build ETL, event streaming applications, applications for recording metrics and anything else that has a real-time data requirement. Payment processing is an interesting problem.

Kafka 94

Kafka Pipeline-centric Architecture Database-centric 94

The Modern Data Company

MARCH 1, 2024

Each Data Product is designed for a specific purpose, equipped with the necessary data, transformations, and metadata. Here’s a breakdown of their key components: Data Source: Defines the raw data used to build the Data Product, including internal databases, external feeds, or sensor data. Your business will thank you for it.

Database-centric 40

Database-centric Data Lake Government Retail 40