Smart Data Collective

APRIL 8, 2020

Dating back to the 1970s, the data warehousing market emerged when computer scientist Bill Inmon first coined the term ‘data warehouse’. Created as on-premise servers, the early data warehouses were built to perform on just a gigabyte scale. The post How Will The Cloud Impact Data Warehousing Technologies?

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AWS Machine Learning Blog

APRIL 3, 2025

OMRONs data strategyrepresented on ODAPalso allowed the organization to unlock generative AI use cases focused on tangible business outcomes and enhanced productivity. When needed, the system can access an ODAP data warehouse to retrieve additional information.

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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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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. With watsonx.data , businesses can quickly connect to data, get trusted insights and reduce data warehouse costs. But why now?

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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.

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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.

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AWS Machine Learning Blog

JULY 17, 2023

With cloud computing, as compute power and data became more available, machine learning (ML) is now making an impact across every industry and is a core part of every business and industry. Amazon SageMaker Studio is the first fully integrated ML development environment (IDE) with a web-based visual interface.

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Mlearning.ai

FEBRUARY 16, 2023

The demand for information repositories enabling business intelligence and analytics is growing exponentially, giving birth to cloud solutions. The ultimate need for vast storage spaces manifests in data warehouses: specialized systems that aggregate data coming from numerous sources for centralized management and consistency.

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IBM Journey to AI blog

JULY 11, 2023

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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IBM Journey to AI blog

SEPTEMBER 11, 2023

Db2 Warehouse SaaS, on the other hand, is a fully managed elastic cloud data warehouse with our columnar technology. watsonx.data integration At Think, IBM announced watsonx.data as a new open, hybrid and governed data store optimized for all data, analytics, and AI workloads.

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How to Learn Machine Learning

APRIL 26, 2025

At the heart of their work is the idea of setting up a stable and well-functioning data pipelinean automated set of processes that reads raw data from many sources, cleans it, and transforms it into formats for analysis. Data Architect Designs complex databases and blueprints for data management systems.

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phData

FEBRUARY 15, 2024

With the advent of cloud data warehouses and the ability to (seemingly) infinitely scale analytics on an organization’s data, centralizing and using that data to discover what drives customer engagement has become a top priority for executives across all industries and verticals.

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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. It is supported by querying, governance, and open data formats to access and share data across the hybrid cloud. IBM watsonx.ai

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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. Scheduling.

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phData

JULY 18, 2023

Why Migrate to a Modern Data Stack? With the birth of cloud data warehouses, data applications, and generative AI , processing large volumes of data faster and cheaper is more approachable and desired than ever. Data teams can focus on delivering higher-value data tasks with better organizational visibility.

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Alation

DECEMBER 14, 2021

AWS positions itself as an end-to-end solution with full integration of BI, ML, storage and database tools, and customer stories support this. Quick Takes: Cloud Use Cases & Stories. Breakout sessions shared cutting-edge use cases that hint at the future of cloud computing.

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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.

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Snorkel AI

JANUARY 11, 2023

To improve the training data quality (and reduce the number of revision cycles required to translate domain knowledge to a third-party service), the team realized they needed an alternative to hand-labeling data.

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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.

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Alation

SEPTEMBER 7, 2021

With Snowflake, data stewards have a choice to leverage Snowflake’s governance policies. First, stewards are dependent on data warehouse admins to provide information and to create and edit enforcement policies in Snowflake. Alation’s data lineage helps organizations to secure their data in the Snowflake Data Cloud.

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Alation

AUGUST 26, 2021

Data intelligence has thus evolved to answer these questions, and today supports a range of use cases. Examples of Data Intelligence use cases include: Data governance. Cloud Transformation. Cloud Data Migration. Let’s take a closer look at the role of DI in the use case of data governance.

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IBM Journey to AI blog

AUGUST 3, 2023

IBM Security® Discover and Classify (ISDC) is a data discovery and classification platform that delivers automated, near real-time discovery, network mapping and tracking of sensitive data at the enterprise level, across multi-platform environments.

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phData

OCTOBER 17, 2023

It also encourages the ELT pattern of moving the filter and transformation logic from the beginning/middle of the pipeline (where it can be difficult to debug or re-execute when changes are made) to the end inside the cloud data warehouse/lake. This is where dbt comes in – powering the transformations.

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Alation

JANUARY 25, 2022

This “analysis” is made possible in large part through machine learning (ML); the patterns and connections ML detects are then served to the data catalog (and other tools), which these tools leverage to make people- and machine-facing recommendations about data management and data integrations.

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DataRobot Blog

FEBRUARY 21, 2022

Seventy-six percent of companies prioritize AI and machine learning (ML) over other IT initiatives, according to Algorithmia’s 2021 enterprise trends in machine learning report. With growing pressure on data scientists, every organization needs to ensure that their teams are empowered with the right tools. The bar for AI keeps rising.

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Mlearning.ai

JULY 10, 2023

In my 7 years of Data Science journey, I’ve been exposed to a number of different databases including but not limited to Oracle Database, MS SQL, MySQL, EDW, and Apache Hadoop.

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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.

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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.

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phData

SEPTEMBER 27, 2024

Here’s how a composable CDP might incorporate the modeling approaches we’ve discussed: Data Storage and Processing : This is your foundation. You might choose a cloud data warehouse like the Snowflake AI Data Cloud or BigQuery. Here’s where it gets really interesting.

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