Transforming Workforce Shift Verification with Artificial Intelligence
Opportunity for Change A leading healthcare provider, faced a significant challenge in managing the shift verification process for its hourly workers. Each week, the payroll team had to manually review shift entries and compare them to timecards, shift terminals, or...
The Fourth Step to Data Mesh is Federated Governance
Data mesh is a strategic approach to decentralized data management that provides standardized self-serve data products through a governance model. This enables data-driven organizations to achieve agile, comprehensive and secure data management. Four main principles...
The Third Step to Data Mesh is the Self-Serve Platform
Data mesh is an approach to data management that helps organizations become more agile and prudent with managing, analyzing, and distributing data. Four main principles are fundamental in a data mesh. The first principle is domain ownership, and the second is data as...
The Second Step to Data Mesh is Data as a Product
Data mesh is a new approach to organizational data management that helps data-driven organizations become more agile and prudent with managing, analyzing, and distributing data. Four main principles are fundamental in a data mesh system. The first principle is domain...
The First Step to Data Mesh is Domain Ownership
In our previous post, we discussed the opportunity of developing a data mesh architecture and how it can benefit data-driven enterprise organizations. In the next four posts of our data mesh series, we will cover the fundamental principles that make up the...
Unleashing Value with a Decentralized Data Mesh
Organizationally sourced data is increasingly complex and filled with valuable business intelligence. As organizations become increasingly data-driven, they will need to become more agile and prudent with managing, analyzing, and distributing data. Implementing a data...
How to Select the Best Technology for Data Quality Management
Outdated data quality software can put you at a competitive disadvantage and drive up organizational costs. Modern technology is proactive, avoids more costs, and mitigates more risk. In the following post, we will outline what to look for when selecting data quality...
How to Develop a Strategy for Data Quality Management
Does your organization have a strategy for data quality control? Improving data quality and reducing operational costs requires a solid plan. Establishing a strategy to manage data quality and set organizational standards is essential. To develop and execute a data...
4 Steps to Take Now to Determine the Quality of Your Data
With executive confidence dwindling and the high costs associated with poor data, it's crucial to ask: How bad is your data quality? More importantly, how can it be quantified? US businesses lose an estimated $611 billion annually due to data quality problems, and...
How to Determine the Cost of Bad Data and Gain Organizational Trust
Executives often harbor skepticism toward organizational data. Understanding the financial impact of bad data is a crucial first step in earning their trust. Why Executives Distrust Their Data The value of enterprise data is determined by a variety of factors,...
Transforming Workforce Shift Verification with Artificial Intelligence
Opportunity for Change A leading healthcare provider, faced a significant challenge in managing the shift verification process for its hourly workers. Each week, the payroll team had to manually review shift entries and compare them to timecards, shift terminals, or...
The Fourth Step to Data Mesh is Federated Governance
Data mesh is a strategic approach to decentralized data management that provides standardized self-serve data products through a governance model. This enables data-driven organizations to achieve agile, comprehensive and secure data management. Four main principles...
The Third Step to Data Mesh is the Self-Serve Platform
Data mesh is an approach to data management that helps organizations become more agile and prudent with managing, analyzing, and distributing data. Four main principles are fundamental in a data mesh. The first principle is domain ownership, and the second is data as...
The Second Step to Data Mesh is Data as a Product
Data mesh is a new approach to organizational data management that helps data-driven organizations become more agile and prudent with managing, analyzing, and distributing data. Four main principles are fundamental in a data mesh system. The first principle is domain...
The First Step to Data Mesh is Domain Ownership
In our previous post, we discussed the opportunity of developing a data mesh architecture and how it can benefit data-driven enterprise organizations. In the next four posts of our data mesh series, we will cover the fundamental principles that make up the...
Unleashing Value with a Decentralized Data Mesh
Organizationally sourced data is increasingly complex and filled with valuable business intelligence. As organizations become increasingly data-driven, they will need to become more agile and prudent with managing, analyzing, and distributing data. Implementing a data...
How to Select the Best Technology for Data Quality Management
Outdated data quality software can put you at a competitive disadvantage and drive up organizational costs. Modern technology is proactive, avoids more costs, and mitigates more risk. In the following post, we will outline what to look for when selecting data quality...
How to Develop a Strategy for Data Quality Management
Does your organization have a strategy for data quality control? Improving data quality and reducing operational costs requires a solid plan. Establishing a strategy to manage data quality and set organizational standards is essential. To develop and execute a data...
4 Steps to Take Now to Determine the Quality of Your Data
With executive confidence dwindling and the high costs associated with poor data, it's crucial to ask: How bad is your data quality? More importantly, how can it be quantified? US businesses lose an estimated $611 billion annually due to data quality problems, and...
How to Determine the Cost of Bad Data and Gain Organizational Trust
Executives often harbor skepticism toward organizational data. Understanding the financial impact of bad data is a crucial first step in earning their trust. Why Executives Distrust Their Data The value of enterprise data is determined by a variety of factors,...