Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. Data ingestion/integration services. Data orchestration tools.

Data Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

IBM Journey to AI blog

MAY 9, 2023

Watsonx.data will allow users to access their data through a single point of entry and run multiple fit-for-purpose query engines across IT environments. Through workload optimization an organization can reduce data warehouse costs by up to 50 percent by augmenting with this solution. [1]

Data Warehouse 92

Data Warehouse AWS AI AI 92

IBM Journey to AI blog

JULY 24, 2024

Optimizing performance with fit-for-purpose query engines In the realm of data management, the diverse nature of data workloads demands a flexible approach to query processing. The integration with established data warehouse engines ensures compatibility with existing systems and workflows.

Data Governance 69

Data Governance Data Warehouse Data Preparation Analytics 69

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

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.

Database 101

Database SQL Data Warehouse Machine Learning 101

phData

JULY 18, 2023

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. First up, let’s dive into the foundation of every Modern Data Stack, a cloud-based data warehouse.

Data Warehouse 52

Data Warehouse Analytics Analytics Cloud Data 52

IBM Journey to AI blog

JULY 17, 2023

It is supported by querying, governance, and open data formats to access and share data across the hybrid cloud. Through workload optimization across multiple query engines and storage tiers, organizations can reduce data warehouse costs by up to 50 percent.

AI 74

AI AI Machine Learning Machine Learning 74

Precisely

MAY 13, 2024

As enterprise technology landscapes grow more complex, the role of data integration is more critical than ever before. Wide support for enterprise-grade sources and targets Large organizations with complex IT landscapes must have the capability to easily connect to a wide variety of data sources.

Data Governance 52

Data Governance Data Pipeline Cloud Data Data Quality 52

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.

Azure 71

Azure Database Analytics Analytics 71

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.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Pickl AI

OCTOBER 15, 2024

ETL (Extract, Transform, Load) is a core process in data integration that involves extracting data from various sources, transforming it into a usable format, and loading it into a target system, such as a data warehouse. It supports both batch and real-time data processing , making it highly versatile.

ETL 52

ETL Azure AWS Data Governance 52

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.

Data Governance 64

Data Governance ML ML Augmented Analytics 64

ODSC - Open Data Science

JULY 11, 2023

Conversational artificial intelligence has been around for almost 60 years now. It uses a form of artificial intelligence called Reinforcement Learning from Human Feedback to produce answers based on human-guided computer analytics.2 They are typically used by organizations to store and manage their own data.

Data Lakes 40

Data Lakes AI AI Cloud Computing 40

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.

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.

SQL 52

SQL ML ML Python 52