Dataversity

DECEMBER 20, 2024

While master data might change less frequently than transactional data, implementing data governance practices and defining data retention policy is crucial to maintaining […] The post Building a Strong Data Retention Framework for Retail Operations appeared first on DATAVERSITY.

Retail 130

Retail Data Governance Government Data Quality 130

Domo

APRIL 10, 2025

Supporting data governance Data governance includes rules, policies, and procedures that ensure the proper management and use of an organization’s data assets. Ensure data consistency: MDM eliminates inconsistencies and redundancies arising from disparate systems by centralizing the management of master data.

Master Data Management 52

Master Data Management Data Management Data Governance Supply Chain 52

Astera

SEPTEMBER 4, 2024

Implementing a modern, integrated data architecture can help you break down data silos, which cause C-suite decision-makers to lose 12 hours a week. Furthermore, more than 60% of organizations agree that data silos represent a significant business challenge. Discuss your data strategy with us. What Is Data Mesh?

Data Architecture 52

Data Architecture Data Governance Government Data Discovery 52

The BAWorld

SEPTEMBER 18, 2024

Data integration enables the connection of all your data sources, which helps empower more informed business decisions—an important factor in today’s competitive environment. How does data integration work? There exist various forms of data integration, each presenting its distinct advantages and disadvantages.

Data Warehouse 52

Data Warehouse Finance Data Architecture Banking 52

Astera

NOVEMBER 30, 2023

Here are some key reasons why Data Vault 2.0 was needed: Evolving Data Ecosystems: Data Vault 1.0 was developed in the early 2000s when data ecosystems were simpler and less complex compared to today. With the advent of big data, cloud computing, and advanced analytics, data architectures have become more intricate.

Data Warehouse 52

Data Warehouse Big Data Healthcare Data Governance 52

Astera

MAY 31, 2024

Here are the critical components of data science: Data Collection : Accumulating data from diverse sources like databases, APIs , and web scraping. Data Cleaning and Preprocessing : Ensuring data quality by managing missing values, eliminating duplicates, normalizing data, and preparing it for analysis.

Data Analytics 52

Data Analytics Data Analytics Data Warehouse Healthcare 52

Astera

JANUARY 23, 2024

Businesses need scalable, agile, and accurate data to derive business intelligence (BI) and make informed decisions. Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively.

Agile 52

Agile Data Warehouse Data Quality Government 52