Combining ethics with Data Management and artificial intelligence can build an organization people will trust. Ethical behavior promotes the smooth functioning of human interactions, which includes business, and supports the overall community. AI has the potential to make ethical decisions and can be used to create a healthy relationship with the customer base. Businesses can […]
Fundamentals of Data Stewardship: Frameworks and Responsibilities
If organizations must have Data Stewardship, but struggle with deploying valuable Data Stewardship programs, how can companies mitigate the challenges and get better results faster? The Art of War, by the Chinese military general Sun Tzu, provides insight. He advised, “strategy without tactics is the slowest route to victory. Tactics without strategy is the noise […]
Artificial Neural Networks: An Overview
Neural networks and deep learning currently provide some of the most reliable image recognition, speech recognition, and natural language processing solutions available. However, it wasn’t always that way. One of the earliest and simplest teaching philosophies for artificial intelligence was marginally successful. It suggested that loading the maximum amount of information into a powerful computer […]
Challenges for Data Governance and Data Quality in a Machine Learning Ecosystem
The high availability of data, enhanced computing power and advanced Data Science technologies together make a lethal combination for data-driven outcomes. With the open data economy just around the corner, well-tuned Data Governance capabilities will be the goal of most businesses. Current Data Management practices are focused on risk free data sharing and regulatory compliance. […]
Case Study: Crown College Uses Predictive Analytics to Retain At-Risk Students
Crown College in St. Bonifacius MN embraced a five-year persistence and completion project four years ago. The college’s Presidents’ Cabinet embraced persistence and completion as an improvement initiative to retain at-risk students and the school had been accepted into the Higher Learning Commission (HLC) Persistence and Completion Academy. HLC accredits colleges and universities in a […]
A Brief History of Metadata
Metadata is a small amount of data designed to provide reference information about other data. For example, in 280 BC, the Great Library of Alexandria attached a small, dangling tag to the end of each individual scroll. The tags gave the title, subject, and author, allowing library users to assume the content, without having to […]
Data Strategy vs. Data Architecture
“Data Leadership is about understanding the organization’s relationship with data and seeking ways to help the organization meet its goals using whatever tools are available,” said Anthony Algmin, of Algmin Data Leadership in a DATAVERSITY® interview. Within that overall Data Leadership Framework, sit Data Strategy and Data Architecture as individual disciplines. Data Strategy Companies often […]
Fundamentals of AIaaS and AIPaas (AI-as-a-Service and AI Platforms-as-a-Service)
There are many factors that have started making businesses restless and eager to dive into the newest intelligent technologies for their Data Management practices. The business operators have sighed with relief knowing that they no longer have to engage dedicated talents for advanced model development or cloud infrastructure planning. The idea of “managed (hosted) Data […]
Case Study: Department of the Interior Lays Out Steps for Metadata Implementation
After the U.S. Office of Management and Governance issued the Open Data Policy, federal agencies set to the task of developing Enterprise Data Inventories to support a mandate of government transparency. The Department of the Interior (DOI) took this opportunity to create and implement a Metadata Management framework using an enterprise approach, properly documenting data […]
Graph Databases: Updates on Their Growing Popularity
Graph databases became recognized as a database design in 2006, when Tim Bernes-Lee developed the concept of a huge database called the “linked data.” This concept became the basis of graph storage, and could display how organizations, people, and items or entities are associated, or “interconnected” with one another, and the nature of the relationships. […]