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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Dataversity

JANUARY 28, 2021

It has been ten years since Pentaho Chief Technology Officer James Dixon coined the term “data lake.” While data warehouse (DWH) systems have had longer existence and recognition, the data industry has embraced the more […]. The post A Bridge Between Data Lakes and Data Warehouses appeared first on DATAVERSITY.

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Data Science 101

MARCH 14, 2020

Even with the coronavirus causing mass closures, there are still some big announcements in the cloud data science world. Google is starting to take enterprise AI seriously and Amazon is continuing to do interesting things. Thanks for reading the weekly news, and you can find previous editions on the Cloud Data Science News page.

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IBM Journey to AI blog

JUNE 15, 2023

Moreover, increased regulatory requirements make it harder for enterprises to democratize data access and scale the adoption of analytics and artificial intelligence (AI). Against this challenging backdrop, the sense of urgency has never been higher for businesses to leverage AI for competitive advantage.

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IBM Journey to AI blog

MAY 9, 2023

Today is a revolutionary moment for Artificial Intelligence (AI). Suddenly, everybody is talking about generative AI: sometimes with excitement, other times with anxiety. The answer is that generative AI leverages recent advances in foundation models. AI is already driving results for business.

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phData

NOVEMBER 4, 2024

It must integrate seamlessly across data technologies in the stack to execute various workflows—all while maintaining a strong focus on performance and governance. Two key technologies that have become foundational for this type of architecture are the Snowflake AI Data Cloud and Dataiku.

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AWS Machine Learning Blog

APRIL 3, 2025

At the heart of this transformation is the OMRON Data & Analytics Platform (ODAP), an innovative initiative designed to revolutionize how the company harnesses its data assets. The robust security features provided by Amazon S3, including encryption and durability, were used to provide data protection.

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Tableau

JUNE 8, 2021

Domain experts, for example, feel they are still overly reliant on core IT to access the data assets they need to make effective business decisions. In all of these conversations there is a sense of inertia: Data warehouses and data lakes feel cumbersome and data pipelines just aren't agile enough.

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IBM Journey to AI blog

MAY 9, 2023

IBM today announced it is launching IBM watsonx.data , a data store built on an open lakehouse architecture, to help enterprises easily unify and govern their structured and unstructured data, wherever it resides, for high-performance AI and analytics. What is watsonx.data?

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Dataversity

MARCH 2, 2022

Without effective and comprehensive validation, a data warehouse becomes a data swamp. With the accelerating adoption of Snowflake as the cloud data warehouse of choice, the need for autonomously validating data has become critical.

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Dataversity

NOVEMBER 29, 2021

There’s been a lot of talk about the modern data stack recently. Much of this focus is placed on the innovations around the movement, transformation, and governance of data as it relates to the shift from on-premise to cloud data warehouse-centric architectures.

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phData

JULY 17, 2023

Over the past few decades, the corporate data landscape has changed significantly. The shift from on-premise databases and spreadsheets to the modern era of cloud data warehouses and AI/ LLMs has transformed what businesses can do with data. Data modeling, data cleanup, etc.

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Dataconomy

SEPTEMBER 4, 2023

Cloud-based business intelligence (BI): Cloud-based BI tools enable organizations to access and analyze data from cloud-based sources and on-premises databases. These tools offer the flexibility of accessing insights from anywhere, and they often integrate with other cloud analytics solutions.

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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. With watsonx.ai, businesses can effectively train, validate, tune and deploy AI models with confidence and at scale across their enterprise.

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IBM Journey to AI blog

JULY 24, 2024

By focusing on five key aspects of cloud adoption for optimizing data management—from evolving data strategies to ensuring compliance—businesses can create adaptable, high performing data ecosystems that are primed for AI innovation and future growth.

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IBM Journey to AI blog

SEPTEMBER 11, 2023

Its robust architecture and proven performance have given businesses uninterrupted access to critical data while powering their enterprise-level applications. was a significant leap forward in data management, empowering organizations to unlock the full potential of their data. is a proven, versatile, and AI-ready solution.

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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

JUNE 6, 2024

Data gets ingested, centralized, and deployed within your cloud data warehouse. This allows companies to use their pre-existing data tools and prevents the need for costly setups. Companies need to bring in data from a wide variety of sources to get a holistic view of the customer.

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Flipboard

AUGUST 17, 2023

Amazon Redshift is the most popular cloud data warehouse that is used by tens of thousands of customers to analyze exabytes of data every day. Conclusion In this post, we demonstrated an end-to-end data and ML flow from a Redshift data warehouse to SageMaker.

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phData

APRIL 28, 2025

As a bonus, well check out Matillions AI Copilot and see how AI can help take workflow design to the next level. A Matillion pipeline is a collection of jobs that extract, load, and transform (ETL/ELT) data from various sources into a target system, such as a cloud data warehouse like Snowflake.

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Dataconomy

SEPTEMBER 27, 2024

The integration of AI and machine learning into analytics is a hot topic right now. How do you see these technologies shaping the future of data analytics? AI and machine learning are basically omnipresent. These technologies also allow us to automate complex data processes.

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Tableau

JUNE 8, 2021

Domain experts, for example, feel they are still overly reliant on core IT to access the data assets they need to make effective business decisions. In all of these conversations there is a sense of inertia: Data warehouses and data lakes feel cumbersome and data pipelines just aren't agile enough.

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phData

SEPTEMBER 2, 2024

Matillion is a SaaS-based data integration platform that can be hosted in AWS, Azure, or GCP. It offers a cloud-agnostic data productivity hub called Matillion Data Productivity Cloud. Below is a sample scenario for 3 business units within an organization for the data mart layer of the data warehouse.

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IBM Journey to AI blog

JULY 11, 2023

Data warehouses are a critical component of any organization’s technology ecosystem. The next generation of IBM Db2 Warehouse brings a host of new capabilities that add cloud object storage support with advanced caching to deliver 4x faster query performance than previously, while cutting storage costs by 34x 1.

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Pickl AI

APRIL 9, 2025

By 2025, global data volumes are expected to reach 181 zettabytes, according to IDC. To harness this data effectively, businesses rely on ETL (Extract, Transform, Load) tools to extract, transform, and load data into centralized systems like data warehouses.

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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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phData

JULY 18, 2023

The good news is that there’s a concept called the Modern Data Stack that when utilized properly, consistently helps empower organizations to harness the full potential of their data. Throughout this journey, we’ve helped hundreds of clients achieve eye-opening results by moving to the Modern Data Stack.

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Snorkel AI

JANUARY 11, 2023

Using AI to help customers optimize ad spending and maximize their reach on YouTube. As an example, they used the unstructured video title tags and descriptions stored in their Snowflake data warehouse and created prompts that asked the FM to classify videos based on the description. There are billions of videos on YouTube.

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phData

NOVEMBER 28, 2023

In July 2023, Matillion launched their fully SaaS platform called Data Productivity Cloud, aiming to create a future-ready, everyone-ready, and AI-ready environment that companies can easily adopt and start automating their data pipelines coding, low-coding, or even no-coding at all. Or would you even go to that directly?

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AWS Machine Learning Blog

JULY 17, 2023

Amazon Redshift is a fully managed, fast, secure, and scalable cloud data warehouse. Organizations often want to use SageMaker Studio to get predictions from data stored in a data warehouse such as Amazon Redshift. She helps key customer accounts on their AI and ML journey.

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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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IBM Journey to AI blog

SEPTEMBER 26, 2023

States’ existing investments in modernizing and enhancing ancillary supportive technologies (such as document management, web portals, mobile applications, data warehouses and location services) could negate the need for certain system requirements as part of the child support system modernization initiative.

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Precisely

JANUARY 25, 2024

These systems support containerized applications, virtualization, AI and machine learning, API and cloud connectivity, and more. In light of this, modernization should not be viewed as a replacement strategy so much as an approach to unifying mainframe operations with today’s cloud platforms. Best Practice 2.

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IBM Journey to AI blog

JUNE 2, 2023

improved document management capabilities, web portals, mobile applications, data warehouses, enhanced location services, etc.) IBM Operational Decision Manager (ODM) enables businesses to respond to real-time data by applying automated decisions, enabling business users to develop and maintain operational systems decision logic.

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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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ODSC - Open Data Science

FEBRUARY 6, 2024

This open-source streaming platform enables the handling of high-throughput data feeds, ensuring that data pipelines are efficient, reliable, and capable of handling massive volumes of data in real-time. Each platform offers unique features and benefits, making it vital for data engineers to understand their differences.

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Tableau

DECEMBER 7, 2022

Traditionally, organizations built complex data pipelines to replicate data. Those data architectures were brittle, complex, and time intensive to build and maintain, requiring data duplication and bloated data warehouse investments. Salesforce Data Cloud for Tableau solves those challenges.

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