IBM Journey to AI blog

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

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Data Warehouse Cloud Data Analytics Analytics 58

AWS Machine Learning Blog

NOVEMBER 27, 2023

SageMaker endpoints can be registered to the Salesforce Data Cloud to activate predictions in Salesforce. SageMaker Canvas provides a no-code experience to access data from Salesforce Data Cloud and build, test, and deploy models using just a few clicks. Set up OAuth for Salesforce Data Cloud in SageMaker Canvas.

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ML ML AWS SQL 98

AWS Machine Learning Blog

APRIL 3, 2025

Amazon AppFlow was used to facilitate the smooth and secure transfer of data from various sources into ODAP. Additionally, Amazon Simple Storage Service (Amazon S3) served as the central data lake, providing a scalable and cost-effective storage solution for the diverse data types collected from different systems.

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AWS Data Governance Data Silos SQL 82

AWS Machine Learning Blog

AUGUST 4, 2023

If you are a returning user to SageMaker Studio, in order to ensure Salesforce Data Cloud is enabled, upgrade to the latest Jupyter and SageMaker Data Wrangler kernels. This completes the setup to enable data access from Salesforce Data Cloud to SageMaker Studio to build AI and machine learning (ML) models.

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Smart Data Collective

OCTOBER 27, 2021

Google BigQuery is a serverless and cost-effective multi-cloud data warehouse. It is easy to integrate with any existing data pipelines, and it can also stream data from the most popular message buses such as Amazon Kinesis and Kafka. It can also batch load files from data lakes such as Amazon S3 and HDFS.

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Analytics Analytics Data Warehouse Business Intelligence 130

The MLOps Blog

MAY 17, 2023

From data processing to quick insights, robust pipelines are a must for any ML system. Often the Data Team, comprising Data and ML Engineers , needs to build this infrastructure, and this experience can be painful. However, efficient use of ETL pipelines in ML can help make their life much easier.

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AWS Machine Learning Blog

SEPTEMBER 5, 2023

In order to improve our equipment reliability, we partnered with the Amazon Machine Learning Solutions Lab to develop a custom machine learning (ML) model capable of predicting equipment issues prior to failure. Our teams developed a framework for processing over 50 TB of historical sensor data and predicting faults with 91% precision.

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phData

NOVEMBER 1, 2024

Chief Information Officer, Legal Industry Survey respondents noted improved data quality and compliance and risk management as the top two outcomes for organizations with a focus on more standardized data controls when working to implement GenAI and LLM applications.

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Data Governance Data Quality ML ML 52

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

SQL 52

SQL ML ML Python 52

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

SQL 52

SQL ML ML Python 52

AWS Machine Learning Blog

APRIL 12, 2023

The PdMS includes AWS services to securely manage the lifecycle of edge compute devices and BHS assets, cloud data ingestion, storage, machine learning (ML) inference models, and business logic to power proactive equipment maintenance in the cloud. It’s an easy way to run analytics on IoT data to gain accurate insights.

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AWS ML ML Machine Learning 110

Alation

APRIL 14, 2022

And, as organizations progress and grow, “data drift” starts to impact data usage, models, and your business. In today’s AI/ML-driven world of data analytics, explainability needs a repository just as much as those doing the explaining need access to metadata, EG, information about the data being used.

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Data Governance ML ML Cloud Data 59

IBM Journey to AI blog

MAY 9, 2023

After some impressive advances over the past decade, largely thanks to the techniques of Machine Learning (ML) and Deep Learning , the technology seems to have taken a sudden leap forward. A data store built on open lakehouse architecture, it runs both on premises and across multi-cloud environments. But why now?

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AI AI Data Warehouse Machine Learning 110

Alation

DECEMBER 14, 2021

Compliance in the Cloud ( GDPR, CCPA ) is still in in its infancy and tough to navigate, with people wondering: How do you manage policies in the cloud? How do you provide access and connect the right people to the right data? AWS has created a way to manage policies and access, but this is only for data lake formation.

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AWS Data Lakes Data Warehouse Machine Learning 52

Alation

APRIL 19, 2022

Data modernization is the process of transferring data to modern cloud-based databases from outdated or siloed legacy databases, including structured and unstructured data. In that sense, data modernization is synonymous with cloud migration. 5 Benefits of Data Modernization. Advanced Tooling.

Data Governance 52

Data Governance Cloud Data Database Data Silos 52

Dataversity

FEBRUARY 17, 2022

With machine learning (ML) and artificial intelligence (AI) applications becoming more business-critical, organizations are in the race to advance their AI/ML capabilities. To realize the full potential of AI/ML, having the right underlying machine learning platform is a prerequisite.

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IBM Journey to AI blog

JULY 17, 2023

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. 1 When comparing published 2023 list prices normalized for VPC hours of watsonx.data to several major cloud data warehouse vendors. IBM watsonx.ai

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AI AI Machine Learning Machine Learning 74

Alation

JUNE 21, 2022

Over time, we called the “thing” a data catalog , blending the Google-style, AI/ML-based relevancy with more Yahoo-style manual curation and wikis. Thus was born the data catalog. In our early days, “people” largely meant data analysts and business analysts. ML and DataOps teams).

DataOps 52

DataOps Data Scientist Data Quality Data Pipeline 52

Alation

JULY 18, 2022

Automatically tracking data lineage across queries executed in any language. To ensure you can deliver on this world-changing vision of data, Alation helps you maximize the value of your data lake with integrations to the Unity catalog. An information scheme in the Lakehouse. … and much more!

AI 52

AI AI Data Lakes Azure 52

Mlearning.ai

FEBRUARY 16, 2023

Thus, the solution allows for scaling data workloads independently from one another and seamlessly handling data warehousing, data lakes , data sharing, and engineering. Machine Learning Integration Opportunities Organizations harness machine learning (ML) algorithms to make forecasts on the data.

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Data Warehouse Business Intelligence Business Intelligence Database 52

AWS Machine Learning Blog

NOVEMBER 1, 2024

Instead, a core component of decentralized clinical trials is a secure, scalable data infrastructure with strong data analytics capabilities. Amazon Redshift is a fully managed cloud data warehouse that trial scientists can use to perform analytics. With SageMaker, you can optimize your ML environment for sustainability.

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AWS Data Lakes Machine Learning Machine Learning 112

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 Models 52

Data Models Data Modeling Apache Kafka Data Lakes 52