Data Architecture principles are a set of policies that govern the enterprise data framework with its operating rules for collecting, integrating, using, and managing data assets. The basic purpose of the Data Architecture principles is to keep the supportive data framework clean, consistent, and auditable. The overall enterprise Data Strategy is built around these principles. […]
The Business Glossary and Automated Metadata Tools
Automated metadata tools can be used to develop and build business glossaries, graphs, and data catalogs. By eliminating the human factor, metadata errors can be minimized and tasks accomplished much more quickly. Business glossaries act as the foundation for a shared and common language. Automated metadata tools can cut down on the amount of time […]
Data Quality Management 101
Data Quality Management is necessary for dealing with the real challenge of low-quality data. Data Quality Management can stop the waste of time and energy required to deal with inaccurate data by manually reprocessing it. Low-quality data can hide problems in operations and make regulatory compliance a challenge. Good Data Quality Management is essential for […]
Data Architecture Challenges
The more your business grows, the more complex your business’s Data Architecture becomes. Enterprise Data Architecture challenges abound – from the beginning and throughout the journey. Data has now become the lifeblood of any business, and business data cannot survive without a solid underlying Data Architecture. Data helps businesses to identify risks and opportunities, understand […]
Data Leadership: The Key to Data Value
Data and business have become inseparable, so if your business isn’t using data effectively, you’re in trouble. Yet using it effectively can be a struggle. Not knowing how to find the right data, not trusting the available data, and not having confidence in the tools and people providing that data can lead people to conclude […]
Measuring Data Consistency
Measuring data consistency can tell a researcher how valuable and useful their data is. However, the term “data consistency” can be confusing. There are three versions of it. When the term is applied to databases, it describes data consistency within the database. When used with computing strategies, data consistency is focused on the use of […]
Data Mesh vs. Data Lake: Which Is Better for Your Business?
In a data-driven business climate, data is playing a key role in capturing market intelligence and “actionable insights” to augment business operations. Thus, Data Management platforms, tools, and associated technologies are increasingly getting a global focus. Two Data Management technologies have created controversies and have become the topic of hot debates: the data lake and […]
Case Study: New Innovations in IoT Technologies for Manufacturers
Manufacturers want to save money, conserve energy, and reduce greenhouse gas emissions, but it’s a challenge to see where and when energy use is occurring. When the utility bill arrives, a manufacturer can see how much total energy was used, but energy use is not broken down on a machine-by-machine basis. Invisible energy use hides […]
Aligning Data Architecture and Data Strategy
Peter Aiken disagrees with the popular idea that it’s impossible to put a dollar value on Data Architecture. “It won’t be the right number, but it will be at least a dollar value on it, and if there’s money involved, people should be paying attention to it.” Aiken is an author, Professor of Information Systems, […]
Advances in Data Warehouses
Data warehouses have advanced in the past few years, adding multiple enhancements and new capabilities. A data warehouse stores business data from a variety of applications and databases. It acts as a single repository, which an organization can access with BI (business intelligence) and analytics tools, before making decisions. A data warehouse provides faster processing […]