Today, most businesses are embracing digital transformation to meet ever-increasing customer expectations and to remain competitive and relevant in the world economy. While many organizations still struggle to adopt new technologies – often due to the lack of a tailored digital strategy and the reluctance of many to change the way of business operations that […]
7 Key Features of Data Management Systems
Data Management is the practice of gathering, organizing, securing, and storing data for an organization so it can be analyzed for business decisions. Data Management helps minimize potential errors by setting processes and policies around its usage and building confidence in the data used for decision-making throughout the company. Businesses implement Data Management systems to ensure that data […]
Writing a Data Management Plan
A Data Management plan (DMP) is normally a one- or two-page summary, outlining how data will be handled during a research project, and after it has been completed. The goal of a Data Management plan is to consider the many aspects of Data Management (such as data preservation, metadata generation, and analysis) before the project begins. It […]
Five Essential Data Architecture Principles
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 […]