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

Pickl AI

JUNE 28, 2023

Understanding Data Integration in Data Mining Data integration is the process of combining data from different sources. Thus creating a consolidated view of the data while eliminating data silos. It involves mapping and transforming data elements to align with a unified schema.

Data Mining 52

Data Mining Data Mining Data Mining ETL 52

phData

APRIL 18, 2023

This is due to a fragmented ecosystem of data silos, a lack of real-time fraud detection capabilities, and manual or delayed customer analytics, which results in many false positives. Snowflake Marketplace offers data from leading industry providers such as Axiom, S&P Global, and FactSet.

Data Silos 52

Data Silos ETL Clustering Analytics 52

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. Data Integrity Is a Business Imperative As the number of data tools and platforms continues to grow, the amount of data silos within organizations grow too.

Data Silos 52

Data Silos ETL Data Quality Data Pipeline 52

Pickl AI

NOVEMBER 15, 2023

What Is Data Lake? A Data Lake is a centralized repository that allows businesses to store vast volumes of structured and unstructured data at any scale. Unlike traditional databases, Data Lakes enable storage without the need for a predefined schema, making them highly flexible.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 52

IBM Journey to AI blog

JULY 3, 2024

Open is creating a foundation for storing, managing, integrating and accessing data built on open and interoperable capabilities that span hybrid cloud deployments, data storage, data formats, query engines, governance and metadata.

AI 45

AI AI Data Quality Database 45

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. Learn more about the benefits of data fabric and IBM Cloud Pak for Data.

Data Quality 52

Data Quality Data Lakes Data Warehouse Big Data 52

IBM Journey to AI blog

JANUARY 18, 2023

They defined it as : “ A data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data. ”.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

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. It truly is an all-in-one data lake solution.

Data Lakes 52

Data Lakes Clustering Big Data Big Data 52

phData

SEPTEMBER 27, 2024

. “ This sounds great in theory, but how does it work in practice with customer data or something like a ‘composable CDP’? Well, implementing transitional modeling does require a shift in how we think about and work with customer data. It often involves specialized databases designed to handle this kind of atomic, temporal data.

Data Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 52

Flipboard

DECEMBER 4, 2024

Currently, organizations often create custom solutions to connect these systems, but they want a more unified approach that them to choose the best tools while providing a streamlined experience for their data teams. You can use Amazon SageMaker Lakehouse to achieve unified access to data in both data warehouses and data lakes.

Data Lakes 139

Data Lakes Data Warehouse AWS Database 139

Alation

OCTOBER 19, 2021

Although organizations don’t set out to intentionally create data silos, they are likely to arise naturally over time. This can make collaboration across departments difficult, leading to inconsistent data quality , a lack of communication and visibility, and higher costs over time (among other issues). What Are Data Silos?

Data Silos 52

Data Silos ETL Data Governance Cloud Data 52

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? This is “ lift-and-shift,” while it works, it doesn’t take full advantage of the cloud.

Data Warehouse 98

Data Warehouse Data Lakes Clustering Cloud Data 98

Flipboard

MARCH 21, 2025

Traditionally, answering this question would involve multiple data exports, complex extract, transform, and load (ETL) processes, and careful data synchronization across systems. SageMaker Unified Studio provides a unified experience for using data, analytics, and AI capabilities. Under CATALOGS , select AwsDataCatalog.

SQL 136

SQL Data Analyst Data Warehouse AWS 136