Precisely

FEBRUARY 20, 2025

If you cant use predictive analytics and make quick, confident data-driven decisions, you risk falling behind to your competitors that can. Solution: Ensure real-time insights and predictive analytics are both accurate and actionable with data integration.

Data Silos 69

Data Silos AI AI Data Quality 69

IBM Journey to AI blog

MAY 9, 2024

How can a healthcare provider improve its data governance strategy, especially considering the ripple effect of small changes? Data lineage can help.With data lineage, your team establishes a strong data governance strategy, enabling them to gain full control of your healthcare data pipeline.

Data Governance 85

Data Governance Data Silos Data Quality Predictive Analytics 85

Data Science Blog

FEBRUARY 4, 2023

If the data sources are additionally expanded to include the machines of production and logistics, much more in-depth analyses for error detection and prevention as well as for optimizing the factory in its dynamic environment become possible.

Cloud Data 147

Cloud Data Data Science Business Intelligence Business Intelligence 147

phData

APRIL 18, 2023

Data movements lead to high costs of ETL and rising data management TCO. The inability to access and onboard new datasets prolong the data pipeline’s creation and time to market. Data co-location enables teams to access, join, query, and analyze internal and external vendor data with minimal to no ETL.

Data Silos 52

Data Silos ETL Clustering Analytics 52

Pickl AI

JULY 3, 2023

Gain hands-on experience with data integration: Learn about data integration techniques to combine data from various sources, such as databases, spreadsheets, and APIs. BI Developers should be familiar with dimensional modelling techniques, including star schemas, snowflake schemas, and slowly changing dimensions.

Business Intelligence 52

Business Intelligence Business Intelligence SQL Data Visualization 52

Pickl AI

OCTOBER 10, 2024

It integrates well with cloud services, databases, and big data platforms like Hadoop, making it suitable for various data environments. Typical use cases include ETL (Extract, Transform, Load) tasks, data quality enhancement, and data governance across various industries.

Data Quality 52

Data Quality AWS Machine Learning Machine Learning 52

IBM Journey to AI blog

JULY 17, 2023

The next generation of Db2 Warehouse SaaS and Netezza SaaS on AWS fully support open formats such as Parquet and Iceberg table format, enabling the seamless combination and sharing of data in watsonx.data without the need for duplication or additional ETL.

AI 74

AI AI Machine Learning Machine Learning 74