IBM Journey to AI blog

FEBRUARY 2, 2023

These developments have accelerated the adoption of hybrid-cloud data warehousing; industry analysts estimate that almost 50% 2 of enterprise data has been moved to the cloud. What is holding back the other 50% of datasets on-premises? However, a more detailed analysis is needed to make an informed decision.

Data Warehouse 58

Data Warehouse Cloud Data Analytics Analytics 58

Dataconomy

SEPTEMBER 4, 2023

Data integration: Integrate data from various sources into a centralized cloud data warehouse or data lake. Ensure that data is clean, consistent, and up-to-date. Use ETL (Extract, Transform, Load) processes or data integration tools to streamline data ingestion.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

phData

APRIL 29, 2024

Fivetran enables healthcare organizations to ingest data securely and effectively from a variety of sources into their target destinations, such as Snowflake or other cloud data platforms, for further analytics or curation for sharing data with external providers or customers.

SQL 52

SQL Data Warehouse Azure Cloud Data 52

phData

FEBRUARY 14, 2023

Fivetran works with all three Snowflake cloud providers. If using a network policy with Snowflake, be sure to add Fivetran’s IP address list , which will ensure Azure Data Factory (ADF) Azure Data Factory is a fully managed, serverless data integration service built by Microsoft.

Data Warehouse 59

Data Warehouse Azure AWS Database 59

Alation

JULY 18, 2022

And the highlight, for us data intelligence folks, was the Databricks’ announcement that Unity Catalog , its unified governance solution for all data assets on its Lakehouse platform, will soon be available on AWS and Azure in the upcoming weeks. A simple model to control access to data via a UI or SQL. and much more!

AI 52

AI AI Data Lakes Azure 52

phData

JUNE 11, 2025

Depending on the requirement, it is important to choose between transient and permanent tables, as well as data recovery needs and downtime considerations. By adopting these best practices, organizations can effectively manage Snowflake budgets, optimize credit usage, and drive greater cost efficiency and ROI in their cloud data operations.

Clustering 59

Clustering SQL Database Data Lakes 59

ODSC - Open Data Science

JULY 11, 2023

Co-location data centers: These are data centers that are owned and operated by third-party providers and are used to house the IT equipment of multiple organizations. Edge data centers: These are data centers that are located closer to the edge of the network, where data is generated and consumed, rather than in central locations.

Data Lakes 40

Data Lakes AI AI Cloud Computing 40

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

Mlearning.ai

FEBRUARY 16, 2023

The platform enables quick, flexible, and convenient options for storing, processing, and analyzing data. The solution was built on top of Amazon Web Services and is now available on Google Cloud and Microsoft Azure. Therefore, the tool is referred to as cloud-agnostic. What does Snowflake do?

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

Pickl AI

APRIL 9, 2025

This includes operations like data validation, data cleansing, data aggregation, and data normalization. The goal is to ensure that the data is consistent and ready for analysis. Loading : Storing the transformed data in a target system like a data warehouse, data lake, or even a database.

ETL 52

ETL Data Warehouse AWS Business Intelligence 52

Dataversity

MARCH 29, 2021

The post The Move to Public Cloud and an Intelligent Data Strategy appeared first on DATAVERSITY. Click to learn more about author Joe Gaska. This is especially true when it comes to applications. As […].

DataOps 94

DataOps Data Lakes Azure Cloud Data 94

phData

DECEMBER 4, 2023

However, if there’s one thing we’ve learned from years of successful cloud data implementations here at phData, it’s the importance of: Defining and implementing processes Building automation, and Performing configuration …even before you create the first user account. authorization server.

Clustering 98

Clustering Database SQL Data Pipeline 98

phData

SEPTEMBER 20, 2023

A data mesh is a conceptual architectural approach for managing data in large organizations. Traditional data management approaches often involve centralizing data in a data warehouse or data lake, leading to challenges like data silos, data ownership issues, and data access and processing bottlenecks.

Data Silos 52

Data Silos Database Data Quality Data Engineering 52

The MLOps Blog

MAY 17, 2023

Cloud ETL Pipeline: Cloud ETL pipeline for ML involves using cloud-based services to extract, transform, and load data into an ML system for training and deployment. Cloud providers such as AWS, Microsoft Azure, and GCP offer a range of tools and services that can be used to build these pipelines.

ETL 59

ETL Data Pipeline ML ML 59

Data Science Blog

MAY 15, 2023

tl;dr Ein Data Lakehouse ist eine moderne Datenarchitektur, die die Vorteile eines Data Lake und eines Data Warehouse kombiniert. Die Definition eines Data Lakehouse Ein Data Lakehouse ist eine moderne Datenspeicher- und -verarbeitungsarchitektur, die die Vorteile von Data Lakes und Data Warehouses vereint.

Data Warehouse 147

Data Warehouse Data Lakes Azure AWS 147

phData

SEPTEMBER 27, 2024

Both persistent staging and data lakes involve storing large amounts of raw data. But persistent staging is typically more structured and integrated into your overall customer data pipeline. You might choose a cloud data warehouse like the Snowflake AI Data Cloud or BigQuery. New user sign-up?

Data Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 52