phData

NOVEMBER 28, 2024

“ Vector Databases are completely different from your cloud data warehouse.” – You might have heard that statement if you are involved in creating vector embeddings for your RAG-based Gen AI applications. in a 2D space based on the machine learning algorithm used.

Python 52

Python Database SQL Machine Learning 52

Alation

APRIL 14, 2022

This two-part series will explore how data discovery, fragmented data governance , ongoing data drift, and the need for ML explainability can all be overcome with a data catalog for accurate data and metadata record keeping. The Cloud Data Migration Challenge. Data pipeline orchestration.

Data Governance 59

Data Governance ML ML Cloud Data 59

Alation

JUNE 9, 2021

We have an explosion, not only in the raw amount of data, but in the types of database systems for storing it ( db-engines.com ranks over 340) and architectures for managing it (from operational datastores to data lakes to cloud data warehouses). Organizations are drowning in a deluge of data.

Data Governance 59

Data Governance Database Cloud Data Machine Learning 59

Dataconomy

MAY 14, 2025

It enables organizations to capture every user interaction across websites, mobile apps, and other digital products in a structured, rich event format then funnel those events in real time to data warehouses, AI models, or other destinations of choice. Those who seize this moment can set the terms of engagement to their advantage.

AI 70

AI AI Data Warehouse Data Pipeline 70

phData

JUNE 26, 2024

This is a perfect use case for machine learning algorithms that predict metrics such as sales and product demand based on historical and environmental factors. Cleaning and preparing the data Raw data typically shouldn’t be used in machine learning models as it’ll throw off the prediction.

Machine Learning 52

Machine Learning Machine Learning Data Engineer Data Engineering 52

phData

MAY 6, 2024

Another benefit of deterministic matching is that the process to build these identities is relatively simple, and tools your teams might already use, like SQL and dbt , can efficiently manage this process within your cloud data warehouse. It thrives on patterns, combinations of data points, and statistical probabilities.

Data Lakes 52

Data Lakes Data Warehouse Cloud Data SQL 52

Snorkel AI

MAY 26, 2023

And so data scientists might be leveraging one compute service and might be leveraging an extracted CSV for their experimentation. And then the production teams might be leveraging a totally different single source of truth or data warehouse or data lake and totally different compute infrastructure for deploying models into production.

SQL 52

SQL ML ML Python 52

Snorkel AI

MAY 26, 2023

And so data scientists might be leveraging one compute service and might be leveraging an extracted CSV for their experimentation. And then the production teams might be leveraging a totally different single source of truth or data warehouse or data lake and totally different compute infrastructure for deploying models into production.

SQL 52

SQL ML ML Python 52

phData

OCTOBER 28, 2024

Understanding Matillion and Snowflake, the Python Component, and Why it is Used Matillion is a SaaS-based data integration platform that can be hosted in AWS, Azure, or GCP and supports multiple cloud data warehouses.

Python 52

Python ETL AWS Database 52

phData

SEPTEMBER 27, 2024

Let’s break down why this is so powerful for us marketers: Data Preservation : By keeping a copy of your raw customer data, you preserve the original context and granularity. Here’s how a composable CDP might incorporate the modeling approaches we’ve discussed: Data Storage and Processing : This is your foundation.

Data Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 52