IBM Journey to AI blog

SEPTEMBER 25, 2023

They set up a couple of clusters and began processing queries at a much faster speed than anything they had experienced with Apache Hive, a distributed data warehouse system, on their data lake. Uber chose Presto for the flexibility it provides with compute separated from data storage.

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Data Lakes Analytics Analytics Clustering 102

AWS Machine Learning Blog

SEPTEMBER 18, 2024

Context In early 2023, Zeta’s machine learning (ML) teams shifted from traditional vertical teams to a more dynamic horizontal structure, introducing the concept of pods comprising diverse skill sets. Though it’s worth mentioning that Airflow isn’t used at runtime as is usual for extract, transform, and load (ETL) tasks.

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AWS Machine Learning Machine Learning ML 120

IBM Journey to AI blog

JULY 17, 2023

It is supported by querying, governance, and open data formats to access and share data across the hybrid cloud. Through workload optimization across multiple query engines and storage tiers, organizations can reduce data warehouse costs by up to 50 percent.

AI 74

AI AI Machine Learning Machine Learning 74

Pickl AI

JANUARY 15, 2025

As businesses increasingly rely on data-driven strategies, the global BI market is projected to reach US$36.35 billion in 2029 , reflecting a compound annual growth rate (CAGR) of 5.35% from 2023 to 2029. The rise of big data, along with advancements in technology, has led to a surge in the adoption of BI tools across various sectors.

Business Intelligence 52

Business Intelligence Business Intelligence Power BI Data Visualization 52

phData

SEPTEMBER 26, 2023

Data flows from the current data platform to the destination. Transformations Transformations can be a part of data ingestion (ETL pattern) or can take place at a later stage after data has been landed (ELT pattern). Either way, it’s important to understand what data is transformed, and how so.

SQL 52

SQL Database ETL Data Modeling 52

The MLOps Blog

JANUARY 26, 2024

Related article How to Build ETL Data Pipelines for ML See also MLOps and FTI pipelines testing Once you have built an ML system, you have to operate, maintain, and update it. They store their feature data in Hopsworks’ free serverless platform, app.hopsworks.ai. Typically, these activities are collectively called “ MLOps.”

Machine Learning 72

Machine Learning Machine Learning ML ML 72

Flipboard

MARCH 21, 2025

Traditionally, answering this question would involve multiple data exports, complex extract, transform, and load (ETL) processes, and careful data synchronization across systems. The existing Data Catalog becomes the Default catalog (identified by the AWS account number) and is readily available in SageMaker Lakehouse.

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SQL Data Analyst Data Warehouse AWS 141

phData

AUGUST 22, 2024

Test Case 3 - Introduce SQL Syntax Error The final model was created with a WHERE clause that contains no logic, causing it to fail when executed in the data warehouse. The model appears to be part of a larger data warehouse or ETL pipeline. This output is less helpful.

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SQL Data Quality Python Data Warehouse 52

The MLOps Blog

OCTOBER 20, 2023

Placing functions for plotting, data loading, data preparation, and implementations of evaluation metrics in plain Python modules keeps a Jupyter notebook focused on the exploratory analysis | Source: Author Using SQL directly in Jupyter cells There are some cases in which data is not in memory (e.g.,

SQL 52

SQL Database Data Scientist Python 52

The MLOps Blog

JANUARY 23, 2023

Importing data Pricing lakeFS LakeFS is an open source data version control and management platform for data lakes. With lakeFS it is possible to test ETLs on top of production data, in isolation, without copying anything.

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ML ML Data Lakes Machine Learning 52

Flipboard

DECEMBER 4, 2024

Currently, organizations often create custom solutions to connect these systems, but they want a more unified approach that them to choose the best tools while providing a streamlined experience for their data teams. You can use Amazon SageMaker Lakehouse to achieve unified access to data in both data warehouses and data lakes.

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Data Lakes Data Warehouse AWS Database 139

Alation

APRIL 14, 2023

Last week, the Alation team had the privilege of joining IT professionals, business leaders, and data analysts and scientists for the Modern Data Stack Conference in San Francisco. In “The modern data stack is dead, long live the modern data stack!” Cloud costs are growing prohibitive.

Data Pipeline 52

Data Pipeline Data Warehouse Cloud Data ETL 52

phData

SEPTEMBER 27, 2024

In transitional modeling, we’d add new atoms: Subject: Customer#1234 Predicate: hasEmailAddress Object: "john.new@example.com" Timestamp: 2023-07-24T10:00:00Z The old email address atoms are still there, giving us a complete history of how to contact John. Extract, Load, and Transform (ELT) using tools like dbt has largely replaced ETL.

Data Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 52