IBM Journey to AI blog

OCTOBER 22, 2024

The data universe is expected to grow exponentially with data rapidly propagating on-premises and across clouds, applications and locations with compromised quality. This situation will exacerbate data silos, increase pressure to manage cloud costs efficiently and complicate governance of AI and data workloads.

Data Silos 102

Data Silos Data Pipeline DataOps Business Intelligence 102

AWS Machine Learning Blog

APRIL 3, 2025

By analyzing their data, organizations can identify patterns in sales cycles, optimize inventory management, or help tailor products or services to meet customer needs more effectively. One key initiative is ODAPChat, an AI-powered chat-based assistant employees can use to interact with data using natural language queries.

AWS 81

AWS Data Governance Data Silos SQL 81

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

phData

NOVEMBER 9, 2023

The primary objective of this idea is to democratize data and make it transparent by breaking down data silos that cause friction when solving business problems. What Components Make up the Snowflake Data Cloud? What is a Data Lake?

Data Warehouse 98

Data Warehouse Data Lakes Clustering Cloud Data 98

IBM Journey to AI blog

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. What does a modern data architecture do for your business?

Data Quality 52

Data Quality Data Lakes Data Warehouse Big Data 52

ODSC - Open Data Science

SEPTEMBER 29, 2023

In today’s digital world, data is king. Organizations that can capture, store, format, and analyze data and apply the business intelligence gained through that analysis to their products or services can enjoy significant competitive advantages. But, the amount of data companies must manage is growing at a staggering rate.

Data Lakes 52

Data Lakes Clustering Big Data Big Data 52

Dataversity

APRIL 1, 2021

In the data-driven world we live in today, the field of analytics has become increasingly important to remain competitive in business. In fact, a study by McKinsey Global Institute shows that data-driven organizations are 23 times more likely to outperform competitors in customer acquisition and nine times […].

Analytics 69

Analytics Analytics Data Silos Data Lakes 69