Flipboard

MAY 14, 2025

Their information is split between two types of data: unstructured data (such as PDFs, HTML pages, and documents) and structured data (such as databases, data lakes, and real-time reports). Different types of data typically require different tools to access them. Traditionally, businesses face a challenge.

AWS 143

AWS AI AI Database 143

IBM Journey to AI blog

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

AWS 93

AWS Database ETL AI 93

Flipboard

MAY 5, 2025

Connecting insights across data silos: LLMs can synthesize information from multiple reports and databases, delivering integrated perspectives. Additionally, connecting insights across disparate databases and reports can uncover unseen relationships, enabling the discovery of new solutions to complex challenges.

AWS 73

AWS Data Silos Database Artificial Intelligence 73

Dataversity

APRIL 23, 2021

Within the Data Management industry, it’s becoming clear that the old model of rounding up massive amounts of data, dumping it into a data lake, and building an API to extract needed information isn’t working. The post Why Graph Databases Are an Essential Choice for Master Data Management appeared first on DATAVERSITY.

Database 90

Database Data Lakes Data Silos Data Governance 90

Dataconomy

JUNE 1, 2023

Unified data storage : Fabric’s centralized data lake, Microsoft OneLake, eliminates data silos and provides a unified storage system, simplifying data access and retrieval. This open format allows for seamless storage and retrieval of data across different databases.

Power BI 194

Power BI Data Lakes Azure Data Silos 194

Precisely

DECEMBER 16, 2024

Tool overload can lead to inefficiencies and data silos. If you rely on retrospective data, youre creating a lag in decision-making, which simply isnt good enough to stay ahead of security or operational disruptions. The difficulties faced by IT teams often boil down to three key issues: Data silos.

Artificial Intelligence 57

Artificial Intelligence Artificial Intelligence Data Silos Machine Learning 57

AWS Machine Learning Blog

DECEMBER 29, 2022

The use of RStudio on SageMaker and Amazon Redshift can be helpful for efficiently performing analysis on large data sets in the cloud. However, working with data in the cloud can present challenges, such as the need to remove organizational data silos, maintain security and compliance, and reduce complexity by standardizing tooling.

AWS 141

AWS Machine Learning Machine Learning Database 141

IBM Data Science in Practice

NOVEMBER 28, 2022

Insights from data gathered across business units improve business outcomes, but having heterogeneous data from disparate applications and storages makes it difficult for organizations to paint a big picture. How can organizations get a holistic view of data when it’s distributed across data silos?

Data Pipeline 130

Data Pipeline Data Quality Data Preparation Data Governance 130

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

Precisely

JUNE 27, 2024

Minimize data input The less data that you have going into ETL process, the faster and cleaner your results are likely to be. That’s why you want to strip out any unnecessary data as early in the ETL process as possible. The post ETL Best Practices for Optimal Integration appeared first on Precisely.

ETL 52

ETL Data Silos Data Quality Database 52

Alation

MARCH 29, 2022

In the 1970s, data was confined to mainframes and primitive databases. Reports required a formal request of the few who could access that data. The 1980s ushered in the antithesis of this version of computing — personal computing and distributed database management — but also introduced duplicated data and enterprise data silos.

Business Intelligence 96

Business Intelligence Business Intelligence Data Silos Citizen Data Scientist 96

Precisely

JULY 12, 2024

However, simply having high-quality data does not, of itself, ensure that an organization will find it useful. That is where data integrity comes into play. Data quality is an essential subset of data integrity, but it is possible to have good data quality without also having data integrity.

Data Quality 104

Data Quality Data Governance Database Analytics 104

IBM Journey to AI blog

APRIL 15, 2024

Data virtualization empowers businesses to unlock the hidden potential of their data, delivering real-time AI insights for cutting-edge applications like predictive maintenance, fraud detection and demand forecasting. A data virtualization platform breaks down data silos by using data virtualization.

Analytics 81

Analytics Analytics Data Silos AI 81

IBM Journey to AI blog

MAY 15, 2024

According to International Data Corporation (IDC), stored data is set to increase by 250% by 2025 , with data rapidly propagating on-premises and across clouds, applications and locations with compromised quality. This situation will exacerbate data silos, increase costs and complicate the governance of AI and data workloads.

Data Pipeline 85

Data Pipeline ETL SQL Database 85

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

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

Precisely

JANUARY 17, 2023

Build an Ongoing Discipline for Data Integrity In the earlier stages of data maturity, many organizations view data integrity through the lens of data quality. Moreover, they tend to understand data quality improvement as a one-off exercise. That approach assumes that good data quality will be self-sustaining.

Data Quality 97

Data Quality Machine Learning Machine Learning Data Silos 97

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

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

OCTOBER 30, 2023

Overall, this partnership enables the retailer to make data-driven decisions, improve supply chain efficiency and ultimately boost customer satisfaction, all in a secure and scalable cloud environment. The platform provides an intelligent, self-service data ecosystem that enhances data governance, quality and usability.

AWS 95

AWS AI AI Data Warehouse 95

phData

SEPTEMBER 20, 2023

A data mesh is a decentralized approach to data architecture that’s been gaining traction as a solution to the challenges posed by large and complex data ecosystems. It’s all about breaking down data silos, empowering domain teams to take ownership of their data, and fostering a culture of data collaboration.

Data Silos 52

Data Silos Database Data Quality Data Engineering 52

IBM Journey to AI blog

MAY 9, 2023

Through workload optimization an organization can reduce data warehouse costs by up to 50 percent by augmenting with this solution. [1] 1] It also offers built-in governance, automation and integrations with an organization’s existing databases and tools to simplify setup and user experience.

Data Warehouse 92

Data Warehouse AWS AI AI 92

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

Precisely

JUNE 12, 2023

Lack of agility : To take advantage of the newest advances in technology, insurers must have the capacity to use their data efficiently and effectively. Data silos create significant barriers to cloud transformation. CDC eliminates silos and opens the door to data-driven innovation.

Data Silos 52

Data Silos Augmented Analytics Database ML 52

phData

FEBRUARY 27, 2024

Cloning Capabilities Zero copy cloning in Snowflake refers to the ability to create a clone of a database or table without physically duplicating the underlying data. This would involve adding a prefix or suffix to all databases to determine their environment. Establish data governance guidelines.

Database 52

Database Data Governance Data Silos Data Warehouse 52

Alation

OCTOBER 5, 2021

Roadblock #3: Silos Breed Misunderstanding. A data silo is an island of information that does not connect with other islands. Typically, these data silos will prevent two-way flows of data outside and inside of the organization.

Data Governance 96

Data Governance Data Quality Data Silos Analytics 96

AWS Machine Learning Blog

JANUARY 13, 2023

Analyzing real-world healthcare and life sciences (HCLS) data poses several practical challenges, such as distributed data silos, lack of sufficient data at a single site for rare events, regulatory guidelines that prohibit data sharing, infrastructure requirement, and cost incurred in creating a centralized data repository.

AWS 102

AWS Analytics Analytics Machine Learning 102

AWS Machine Learning Blog

JANUARY 13, 2023

Analyzing real-world healthcare and life sciences (HCLS) data poses several practical challenges, such as distributed data silos, lack of sufficient data at any single site for rare events, regulatory guidelines that prohibit data sharing, infrastructure requirement, and cost incurred in creating a centralized data repository.

AWS 107

AWS Analytics Analytics Machine Learning 107

phData

SEPTEMBER 15, 2023

To configure Salesforce and Snowflake using the Sync Out connector, follow these steps: Step 1: Create Snowflake Objects To use Sync Out with Snowflake, you need to configure the following Snowflake objects appropriately in your Snowflake account: Database and schema that will be used for the Salesforce data.

Data Warehouse 52

Data Warehouse Tableau Data Silos Analytics 52

phData

MAY 13, 2024

Even if organizations survive a migration to S/4 and HANA cloud, licensing and performance constraints make it difficult to perform advanced analytics on this data within the SAP environment. Additionally, change data markers are not available for many of these tables.

Database 52

Database Analytics Analytics Machine Learning 52

Alation

APRIL 19, 2022

Data producers and consumers alike are working from home and hybrid locations more often. And in an increasingly remote workforce, people need to access data systems easily to do their jobs. This might mean that they’re accessing a database from a smartphone, computer, or tablet. Today, data dwells everywhere.

Data Governance 52

Data Governance Cloud Data Database Data Silos 52

IBM Journey to AI blog

FEBRUARY 2, 2023

The rise of cloud has allowed data warehouses to provide new capabilities such as cost-effective data storage at petabyte scale, highly scalable compute and storage, pay-as-you-go pricing and fully managed service delivery. In 2021, cloud databases accounted for 85% 1 of the market growth in databases.

Data Warehouse 58

Data Warehouse Cloud Data Analytics Analytics 58

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

Alation

MAY 2, 2023

Some of the key benefits of this include: Simplified data governance Data governance and data analytics support each other, and a strong data governance strategy is integral to ensuring that data analytics are reliable and actionable for decision-makers.

Analytics 52

Analytics Analytics Data Silos Data Governance 52

Precisely

FEBRUARY 9, 2024

They’re where the world’s transactional data originates – and because that essential data can’t remain siloed, organizations are undertaking modernization initiatives to provide access to mainframe data in the cloud. That approach assumes that good data quality will be self-sustaining.

Data Quality 67

Data Quality DataOps Data Silos Artificial Intelligence 67

phData

FEBRUARY 13, 2024

Employing a modular structure, SAP ERP encompasses modules such as finance, human resources, supply chain , and more, facilitating real-time collaboration and data sharing across different departments through a centralized database. Violations of license restrictions can result in penalties, additional fees, or even legal consequences.

Analytics 59

Analytics Analytics Data Scientist Data Models 59