Dataconomy

MAY 27, 2024

The main solutions on the market are decentralized file storage networks (DSFN) like Filecoin and Arweave, and decentralized data warehouses like Space and Time (SxT). Built to seamlessly integrate with existing enterprise systems, the data warehouse lets businesses tap into blockchain data while publishing query results back on-chain.

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Data Warehouse Database SQL Analytics 213

Flipboard

JANUARY 24, 2025

A common use case with generative AI that we usually see customers evaluate for a production use case is a generative AI-powered assistant. If there are security risks that cant be clearly identified, then they cant be addressed, and that can halt the production deployment of the generative AI application.

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AWS AI AI Data Warehouse 159

Pickl AI

FEBRUARY 23, 2023

Organisations must store data in a safe and secure place for which Databases and Data warehouses are essential. You must be familiar with the terms, but Database and Data Warehouse have some significant differences while being equally crucial for businesses. What is a Database?

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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.

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IBM Journey to AI blog

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. The rise of cloud has allowed data warehouses to provide new capabilities such as cost-effective data storage at petabyte scale, highly scalable compute and storage, pay-as-you-go pricing and fully managed service delivery.

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IBM Journey to AI blog

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

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AWS Database ETL AI 93

IBM Journey to AI blog

APRIL 24, 2023

Data is reported from one central repository, enabling management to draw more meaningful business insights and make faster, better decisions. By running reports on historical data, a data warehouse can clarify what systems and processes are working and what methods need improvement.

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Data Warehouse Data Lakes Database Big Data 112

Flipboard

DECEMBER 11, 2024

Organizations are building data-driven applications to guide business decisions, improve agility, and drive innovation. Many of these applications are complex to build because they require collaboration across teams and the integration of data, tools, and services. The following screenshot illustrates the SageMaker Unified Studio.

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SQL AWS Data Lakes AI 159

Women in Big Data

NOVEMBER 27, 2024

A data warehouse is a centralized repository designed to store and manage vast amounts of structured and semi-structured data from multiple sources, facilitating efficient reporting and analysis. Begin by determining your data volume, variety, and the performance expectations for querying and reporting.

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Data Warehouse Big Data Big Data Azure 59

Dataconomy

OCTOBER 8, 2024

Almost every tech company today is up to its neck in generative AI, with Google focused on enhancing search, Microsoft betting the house on business productivity gains with its family of copilots, and startups like Runway AI and Stability AI going all-in on video and image creation. Why is data integrity important?

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Data Pipeline AI AI Data Warehouse 132

Pickl AI

FEBRUARY 3, 2025

Summary: A Data Warehouse consolidates enterprise-wide data for analytics, while a Data Mart focuses on department-specific needs. Data Warehouses offer comprehensive insights but require more resources, whereas Data Marts provide cost-effective, faster access to focused data.

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Flipboard

JUNE 17, 2023

Former Microsoft and Snowflake exec Bob Muglia’s new book is “ The Datapreneurs: The Promise of AI and the Creators Building Our Future.” ” This week: the origins of data, and the future of the digital species. People will use AI for every possible purpose: the good, the bad, and the evil.

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AI AI Data Warehouse Artificial Intelligence 169

ODSC - Open Data Science

SEPTEMBER 27, 2023

In this article, we will delve into the concept of data lakes, explore their differences from data warehouses and relational databases, and discuss the significance of data version control in the context of large-scale data management. Before we address the questions, ‘ What is data version control ?’

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Data Lakes Data Warehouse Database Big Data 98

Pickl AI

NOVEMBER 15, 2023

Discover the nuanced dissimilarities between Data Lakes and Data Warehouses. Data management in the digital age has become a crucial aspect of businesses, and two prominent concepts in this realm are Data Lakes and Data Warehouses. It acts as a repository for storing all the data.

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AWS Machine Learning Blog

FEBRUARY 14, 2024

With the advent of generative AI solutions, organizations are finding different ways to apply these technologies to gain edge over their competitors. Amazon Bedrock offers a choice of high-performing foundation models from leading AI companies, including AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon, via a single API.

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AWS AI AI Database 133

Dataversity

DECEMBER 15, 2021

The abilities of an organization towards capturing, storing, and analyzing data; searching, sharing, transferring, visualizing, querying, and updating data; and meeting compliance and regulations are mandatory for any sustainable organization. For example, most data warehouses […].

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Data Warehouse Data Lakes Database Business Intelligence 98

Pickl AI

MARCH 24, 2025

Summary: Online Analytical Processing (OLAP) systems in Data Warehouse enable complex Data Analysis by organizing information into multidimensional structures. Key characteristics include fast query performance, interactive analysis, hierarchical data organization, and support for multiple users.

Data Analysis 52

Data Analysis Data Analysis Database Data Warehouse 52

Towards AI

APRIL 10, 2024

Last Updated on April 11, 2024 by Editorial Team Author(s): ronilpatil Originally published on Towards AI. Image by Author Configure PostgreSQL Database Step 1. Search for RDS Services, click on Create database, and select Standard create & move down. But how EC2 will communicate with this database?

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Database Machine Learning Machine Learning AWS 122

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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Data Warehouse AWS AI AI 92

Smart Data Collective

OCTOBER 17, 2022

A point of data entry in a given pipeline. Examples of an origin include storage systems like data lakes, data warehouses and data sources that include IoT devices, transaction processing applications, APIs or social media. The final point to which the data has to be eventually transferred is a destination.

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Data Pipeline Data Warehouse ETL Data Lakes 145

IBM Journey to AI blog

OCTOBER 30, 2023

In today’s digital age where data stands as a prized asset, generative AI serves as the transformative tool to mine its potential. According to a survey by the MIT Sloan Management Review, nearly 85% of executives believe generative AI will enable their companies to obtain or sustain a competitive advantage.

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AWS AI AI Data Warehouse 95

Flipboard

DECEMBER 6, 2023

These datasets are often a mix of numerical and text data, at times structured, unstructured, or semi-structured. needed to address some of these challenges in one of their many AI use cases built on AWS. The generated query is then run against the database to fetch the relevant context.

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SQL Database AWS Machine Learning 168

IBM Journey to AI blog

DECEMBER 7, 2023

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. As AI techniques continue to evolve, innovative applications in the OLAP domain are anticipated.

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Data Preparation Database Data Analysis Data Analysis 72

IBM Journey to AI blog

NOVEMBER 15, 2023

IBM watsonx is changing the game for enterprises of all shapes and sizes, making it easy for them to embed generative AI into their operations. Watsonx is comprised of three components that empower businesses to customize their AI solutions: watsonx.ai The most common use cases from partners often combine several of these AI tasks.

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AI AI Data Warehouse Database 103

AWS Machine Learning Blog

JUNE 13, 2023

Organizations can maximize the value of their modern data architecture with generative AI solutions while innovating continuously. The natural language capabilities allow non-technical users to query data through conversational English rather than complex SQL. The following diagram illustrates the architecture.

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Database SQL AWS AI 84

Pickl AI

JULY 14, 2024

It highlights their unique functionalities and applications, emphasising their roles in maintaining data integrity and facilitating efficient data retrieval in database design and management. Understanding the significance of different types of keys in DBMS is crucial for effective database design and management.

Database 52

Database SQL Data Warehouse Data Analyst 52

IBM Journey to AI blog

APRIL 25, 2023

To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures. Now, let’s chat about why data warehouse optimization is a key value of a data lakehouse strategy. To effectively use raw data, it often needs to be curated within a data warehouse.

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Data Warehouse Data Engineering Data Engineering Data Engineering 58

AWS Machine Learning Blog

APRIL 16, 2024

Solution overview With SageMaker Studio JupyterLab notebook’s SQL integration, you can now connect to popular data sources like Snowflake, Athena, Amazon Redshift, and Amazon DataZone. For example, you can visually explore data sources like databases, tables, and schemas directly from your JupyterLab ecosystem.

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SQL AWS Database Data Scientist 109

IBM Journey to AI blog

SEPTEMBER 11, 2023

Thus, was born a single database and the relational model for transactions and business intelligence. Its early success, coupled with IBM WebSphere in the 1990s, put it in the spotlight as the database system for several Olympic games, including 1992 Barcelona, 1996 Atlanta, and the 1998 Winter Olympics in Nagano.

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Database SQL Data Warehouse Machine Learning 101

IBM Journey to AI blog

APRIL 8, 2024

The new Amazon Relational Database Service (Amazon RDS) for Db2 offering allows customers to migrate their existing, self-managed Db2 databases to the cloud and accelerate strategic modernization initiatives. Can Amazon RDS for Db2 be used for running data warehousing workloads?

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AWS Database Data Warehouse Analytics 87

ODSC - Open Data Science

JUNE 22, 2023

While databases were the traditional way to store large amounts of data, a new storage method has developed that can store even more significant and varied amounts of data. These are called data lakes. What Are Data Lakes? However, even digital information has to be stored somewhere.

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Data Lakes Data Warehouse Database Data Science 98

Dataconomy

JUNE 1, 2023

Cost efficiency : Power BI can directly leverage data stored in OneLake, eliminating the need for separate SQL queries and reducing costs associated with data processing. This open format allows for seamless storage and retrieval of data across different databases.

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IBM Journey to AI blog

OCTOBER 16, 2023

Artificial intelligence (AI) adoption is still in its early stages. As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. ” Are foundation models trustworthy?

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AI AI Data Warehouse ML 88

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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ML ML AWS Data Warehouse 123

ODSC - Open Data Science

FEBRUARY 24, 2023

There are many well-known libraries and platforms for data analysis such as Pandas and Tableau, in addition to analytical databases like ClickHouse, MariaDB, Apache Druid, Apache Pinot, Google BigQuery, Amazon RedShift, etc. With Great Expectations , data teams can express what they “expect” from their data using simple assertions.

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Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

Smart Data Collective

DECEMBER 13, 2022

Five Best Practices for Data Analytics. Extracted data must be saved someplace. There are several choices to consider, each with its own set of advantages and disadvantages: Data warehouses are used to store data that has been processed for a specific function from one or more sources. Select a Storage Platform.

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Data Analysis Data Analysis Analytics Analytics 145

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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