Remove Analytics Remove Data Quality Remove Metadata Remove Unstructured Data
article thumbnail

Data architecture strategy for data quality

IBM Big Data Hub

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

article thumbnail

Data governance in the age of generative AI

AWS Big Data

Data governance is a critical building block across all these approaches, and we see two emerging areas of focus. First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Informatica’s new data management clouds target health, finance services

CIO Business Intelligence

Some of the accelerators included as part of the new platform are integrations with Salesforce, NPI data, National Patient Account Services, Workday, Oracle Fusion HCM Cloud, Orange HRM, Salesforce Health Cloud, MedPro, healthcare-focused cloud company Veeva, and HR vendor UltiPro. Analytics for faster decision making.

Finance 140
article thumbnail

The state of data quality in 2020

O'Reilly on Data

We suspected that data quality was a topic brimming with interest. The responses show a surfeit of concerns around data quality and some uncertainty about how best to address those concerns. Key survey results: The C-suite is engaged with data quality. Data quality might get worse before it gets better.

article thumbnail

Prioritizing Data: Why a Solid Data Management Strategy Will Be Critical in 2024

Ontotext

In 2023, data leaders and enthusiasts were enamored of — and often distracted by — initiatives such as generative AI and cloud migration. LLMs can optimize several tasks, such as updating taxonomies, classifying entities, and extracting new properties and relationships from unstructured data.

article thumbnail

Five benefits of a data catalog

IBM Big Data Hub

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

article thumbnail

Data Lakes on Cloud & it’s Usage in Healthcare

BizAcuity

Data lakes are centralized repositories that can store all structured and unstructured data at any desired scale. The power of the data lake lies in the fact that it often is a cost-effective way to store data. Deploying Data Lakes in the cloud. Numbers are only good if the data quality is good.

Data Lake 102