Precisely

JUNE 2, 2023

As companies strive to leverage AI/ML, location intelligence, and cloud analytics into their portfolio of tools, siloed mainframe data often stands in the way of forward momentum. Insufficient skills, limited budgets, and poor data quality also present significant challenges. To learn more, read our ebook.

Data Silos 52

Data Silos ETL Data Quality Data Pipeline 52

Precisely

FEBRUARY 2, 2023

This requires access to data from across business systems when they need it. Data silos and slow batch delivery of data will not do. Stale data and inconsistencies can distort the perception of what is really happening in the business leading to uncertainty and delay.

Data Pipeline 52

Data Pipeline Data Silos Database Data Observability 52

IBM Journey to AI blog

MAY 15, 2024

Organizations require reliable data for robust AI models and accurate insights, yet the current technology landscape presents unparalleled data quality challenges. This situation will exacerbate data silos, increase costs and complicate the governance of AI and data workloads.

Data Pipeline 59

Data Pipeline ETL SQL Database 59

The MLOps Blog

MAY 17, 2023

We also discuss different types of ETL pipelines for ML use cases and provide real-world examples of their use to help data engineers choose the right one. What is an ETL data pipeline in ML? Moreover, ETL pipelines play a crucial role in breaking down data silos and establishing a single source of truth.

ETL 59

ETL Data Pipeline ML ML 59

ODSC - Open Data Science

SEPTEMBER 29, 2023

A 2019 survey by McKinsey on global data transformation revealed that 30 percent of total time spent by enterprise IT teams was spent on non-value-added tasks related to poor data quality and availability. The data lake can then refine, enrich, index, and analyze that data.

Data Lakes 52

Data Lakes Clustering Big Data Big Data 52

Precisely

MARCH 4, 2024

How it’s done : An AI recommender system is a sophisticated technology that leverages AI and vast amounts of user data – like past preferences, behaviors, and interactions – to suggest tailored products, content, or services. You need to break down data silos and integrate critical data from all relevant sources.

AI 72

AI AI Data Quality Artificial Intelligence 72

AWS Machine Learning Blog

MARCH 15, 2024

Duration of data informs on long-term variations and patterns in the dataset that would otherwise go undetected and lead to biased and ill-informed predictions. Breaking down these data silos to unite the untapped potential of the scattered data can save and transform many lives. Much of this work comes down to the data.”

AWS 101

AWS ML ML Data Silos 101

IBM Journey to AI blog

JANUARY 17, 2023

The rapid growth of data continues to proceed unabated and is now accompanied by not only the issue of siloed data but a plethora of different repositories across numerous clouds. From there, it can be easily accessed via dashboards by data consumers or those building into a data product.

Data Governance 57

Data Governance Data Science AI AI 57

Alation

APRIL 19, 2022

Access the resources your data applications need — no more, no less. Data Pipeline Automation. Consolidate all data sources to automate pipelines for processing in a single repository. Consolidating all data across your organization builds trust in the data. Advanced Tooling.

Data Governance 52

Data Governance Cloud Data Database Data Lakes 52