AWS Machine Learning Blog

OCTOBER 9, 2024

Amazon Lookout for Metrics is a fully managed service that uses machine learning (ML) to detect anomalies in virtually any time-series business or operational metrics—such as revenue performance, purchase transactions, and customer acquisition and retention rates—with no ML experience required.

AWS 92

AWS ML ML Data Quality 92

IBM Journey to AI blog

APRIL 25, 2023

In a prior blog , we pointed out that warehouses, known for high-performance data processing for business intelligence, can quickly become expensive for new data and evolving workloads. To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures.

Data Warehouse 58

Data Warehouse Data Engineering Data Engineering Data Engineering 58

Mlearning.ai

FEBRUARY 16, 2023

Today, companies are facing a continual need to store tremendous volumes of data. The demand for information repositories enabling business intelligence and analytics is growing exponentially, giving birth to cloud solutions. Snowflake data warehouses deliver greater capacity without the need for any additional equipment.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

AWS Machine Learning Blog

DECEMBER 29, 2022

You can quickly launch the familiar RStudio IDE and dial up and down the underlying compute resources without interrupting your work, making it easy to build machine learning (ML) and analytics solutions in R at scale. Users can also interact with data with ODBC, JDBC, or the Amazon Redshift Data API. Conclusion.

AWS 134

AWS Machine Learning Machine Learning Natural Language Processing 134

IBM Journey to AI blog

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. An AI governance framework ensures the ethical, responsible and transparent use of AI and machine learning (ML). The development and use of these models explain the enormous amount of recent AI breakthroughs.

AI 88

AI AI Data Warehouse ML 88

AWS Machine Learning Blog

JUNE 25, 2024

To create and share customer feedback analysis without the need to manage underlying infrastructure, Amazon QuickSight provides a straightforward way to build visualizations, perform one-time analysis, and quickly gain business insights from customer feedback, anytime and on any device. The LLM generates output based on the user prompt.

AWS 125

AWS Natural Language Processing Machine Learning Machine Learning 125

IBM Journey to AI blog

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

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.

Data Warehouse 60

Data Warehouse Database Cloud Data Big Data 60

IBM Journey to AI blog

APRIL 8, 2024

Answer : Yes, Amazon RDS for Db2 can support analytics workloads, but it is not a data warehouse. Amazon RDS  Amazon RDS for Db2 supports single-node transactional, mixed and analytics workloads.    Scalability 5.

AWS 87

AWS Database Data Warehouse Analytics 87

How to Learn Machine Learning

APRIL 26, 2025

For example, at an online streaming service, a Data Engineer would build a pipeline that collects user activity from the instant in which the activity happens, processes it into real-time data, and uses either a cloud data warehouse like Snowflake or BigQuery, making the data available for analysts and data scientists to work on.

Data Science 52

Data Science Data Analyst Data Scientist Machine Learning 52

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. IBM watsonx.ai

AI 74

AI AI Machine Learning Machine Learning 74

IBM Journey to AI blog

SEPTEMBER 11, 2023

Don Haderle, a retired IBM Fellow and considered to be the “father of Db2,” viewed 1988 as a seminal point in its development as D B2 version 2 proved it was viable for online transactional processing (OLTP)—the lifeblood of business computing at the time. Db2 (LUW) was born in 1993, and 2023 marks its 30th anniversary.

Database 101

Database SQL Data Warehouse Machine Learning 101

Dataconomy

SEPTEMBER 27, 2023

Data science and analytics MCSA and MCSE certifications can also lead to roles in data science and analytics, such as data analyst, data scientist, or business intelligence developer. Data analysts collect, clean, and analyze data to extract insights that can help businesses make better decisions.

Database Administration 113

Database Administration Database Azure Cloud Computing 113

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.

Data Warehouse 52

Data Warehouse Analytics Analytics Cloud Data 52

IBM Journey to AI blog

AUGUST 4, 2023

Data fabric Data fabric architectures are designed to connect data platforms with the applications where users interact with information for simplified data access in an organization and self-service data consumption. Then, it applies these insights to automate and orchestrate the data lifecycle.

Data Lakes 73

Data Lakes AI AI Data Governance 73

IBM Journey to AI blog

MARCH 14, 2024

.   Request a live demo or start a proof of concept with Amazon RDS for Db2 Db2 Warehouse SaaS on AWS The cloud-native Db2 Warehouse fulfills your price and performance objectives for mission-critical operational analytics, business intelligence (BI) and mixed workloads.

AWS 93

AWS Database ETL AI 93

phData

DECEMBER 12, 2023

A complete view of the fan, rather than pieces of information spread across various departments, means less guesswork and more data insights. Step 2: Analyze the Data Once you have centralized your data, use a business intelligence tool like Sigma Computing , Power BI , Tableau , or another to craft analytics dashboards.

Data Warehouse 52

Data Warehouse Machine Learning Machine Learning Tableau 52

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.

Data Governance 59

Data Governance ML ML Cloud Data 59

IBM Journey to AI blog

JULY 3, 2024

This includes integration with your data warehouse engines, which now must balance real-time data processing and decision-making with cost-effective object storage, open source technologies and a shared metadata layer to share data seamlessly with your data lakehouse.

AI 45

AI AI Data Quality Database 45

Alation

MAY 24, 2022

Alation has been leading the evolution of the data catalog to a platform for data intelligence. Higher data intelligence drives higher confidence in everything related to analytics and AI/ML. It will allow for layout customization and better version history tracking to determine how it has changed over time.

Data Quality 98

Data Quality Data Governance ETL Data Observability 98

Alation

AUGUST 26, 2021

Under an active data governance framework , a Behavioral Analysis Engine will use AI, ML and DI to crawl all data and metadata, spot patterns, and implement solutions. Data Governance and Data Strategy. Finally, data catalogs leverage behavioral metadata to glean insights into how humans interact with data.

Data Governance 64

Data Governance ML ML Augmented Analytics 64

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. Data quality details signal to users whether data can be trusted or used.

Data Governance 59

Data Governance Data Scientist Data Quality Data Profiling 59

IBM Journey to AI blog

DECEMBER 16, 2022

It uses metadata and data management tools to organize all data assets within your organization. It synthesizes the information across your data ecosystem—from data lakes, data warehouses, and other data repositories—to empower authorized users to search for and access business-ready data for their projects and initiatives.

Data Quality 52

Data Quality Data Governance Data Scientist Data Wrangling 52

Pickl AI

DECEMBER 10, 2024

Exalytics: The In-Memory Analytics Machine Oracle Exalytics is a pioneering solution for in-memory analytics and business intelligence. By leveraging cutting-edge hardware and software integration, Exalytics enables businesses to analyse large datasets in real-time.

Database 52

Database Analytics Analytics Business Intelligence 52

DagsHub

NOVEMBER 11, 2024

We use data-specific preprocessing and ML algorithms suited to each modality to filter out noise and inconsistencies in unstructured data. NLP cleans and refines content for text data, while audio data benefits from signal processing to remove background noise. Tools like Unstructured.io

AI 52

AI AI Data Lakes Database 52

DagsHub

AUGUST 23, 2024

As companies increasingly rely on data for decision-making, poor-quality data can lead to disastrous outcomes. Even the most sophisticated ML models, neural networks, or large language models require high-quality data to learn meaningful patterns. When bad data is inputted, it inevitably leads to poor outcomes.

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 52

Flipboard

MAY 9, 2025

This pattern creates a comprehensive solution that transforms raw social media data into actionable business intelligence (BI) through advanced AI capabilities. 3B Instruct Amazon Bedrock, the system provides tailored marketing content that adds business value. By integrating LLMs such as Anthropics Claude 3.5

AWS 98

AWS Natural Language Processing AI AI 98

Pickl AI

FEBRUARY 23, 2025

Statistics : A survey by Databricks revealed that 80% of Spark users reported improved performance in their data processing tasks compared to traditional systems. Google Cloud BigQuery Google Cloud BigQuery is a fully-managed enterprise data warehouse that enables super-fast SQL queries using the processing power of Googles infrastructure.

Big Data 52

Big Data Big Data Apache Hadoop Apache Kafka 52