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

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

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

Alation

JUNE 28, 2022

This is where metadata, or the data about data, comes into play. Having a data catalog is the cornerstone of your data governance strategy, but what supports your data catalog? Your metadata management framework provides the underlying structure that makes your data accessible and manageable.

Data Governance 52

Data Governance Data Analyst Machine Learning Machine Learning 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

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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

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

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.

Database 52

Database Data Governance Data Silos Data Warehouse 52

IBM Journey to AI blog

JULY 3, 2024

Multiple data applications and formats make it harder for organizations to access, govern, manage and use all their data for AI effectively. Scaling data and AI with technology, people and processes Enabling data as a differentiator for AI requires a balance of technology, people and processes.

AI 45

AI AI Data Quality Database 45

Precisely

JULY 18, 2024

While data fabric is not a standalone solution, critical capabilities that you can address today to prepare for a data fabric include automated data integration, metadata management, centralized data governance, and self-service access by consumers. Increase metadata maturity.

Data Lakes 52

Data Lakes Data Warehouse Data Governance Machine Learning 52

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 87

AWS Analytics Analytics Machine Learning 87

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

JANUARY 5, 2023

Meaning, data architecture is a foundational element of your business strategy for higher data quality. Perform data quality monitoring based on pre-configured rules. Taking an inventory of existing data assets and mapping current data flows. 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

Pickl AI

DECEMBER 4, 2023

Exploring technologies like Data visualization tools and predictive modeling becomes our compass in this intricate landscape. Data governance and security Like a fortress protecting its treasures, data governance, and security form the stronghold of practical Data Intelligence.

Data Analysis 52

Data Analysis Data Analysis Artificial Intelligence Artificial Intelligence 52

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 82

AWS Analytics Analytics Machine Learning 82

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

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

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

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

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

Flipboard

MARCH 21, 2025

Through this unified query capability, you can create comprehensive insights into customer transaction patterns and purchase behavior for active products without the traditional barriers of data silos or the need to copy data between systems. Data analysts discover the data and subscribe to the data.

SQL 137

SQL Data Analyst Data Warehouse AWS 137

Alation

AUGUST 2, 2022

The problem many companies face is that each department has its own data, technologies, and information handling processes. This causes data silos to form, which can inhibit data visibility and collaboration, and lead to integrity issues that make it harder to share and use data.

Data Silos 52

Data Silos Data Lakes Data Analyst Data Scientist 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 69

Data Quality DataOps Data Silos Artificial Intelligence 69

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 40

Analytics Analytics Data Silos Data Governance 40

phData

JUNE 20, 2024

The platform can be quickly deployed to start, but you will want to plan for the future so it’s scalable and performant as the data culture matures. A database storage layer is a central repository for the data, while computing is in another layer. Data democratization is the crux of self-service analytics.

Data Governance 52

Data Governance Analytics Analytics Power BI 52

Precisely

OCTOBER 12, 2023

Regulations like GDPR and CCPA, for example, require institutions to permit their customers to remove select types of personal information from internal databases. To achieve that, you need to know where your customer data resides across multiple systems and lines of business. Privacy requirements.

Data Quality 64

Data Quality Data Governance ML ML 64

Dataconomy

MARCH 18, 2025

Data ingestion Data ingestion involves collecting various forms of datastructured, unstructured, and semi-structuredfrom multiple sources. This can include data at rest, such as databases, and data in motion, like live streaming data from IoT devices.

Machine Learning 91

Machine Learning Machine Learning Data Analysis Data Analysis 91