Blockchain, which is akin to a distributed and decentralized accounts ledger, can record and verify high volumes of digital transactions, irrespective of location. So, blockchain has the capacity to contribute to many industry sectors, besides finance. As a secure technology platform, blockchain’s main benefits are accuracy, protection against fraud, and easy sharing of information. The […]
Data Management, Artificial Intelligence, and Ethics
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 […]
Fundamentals of Hyperautomation
Hyperautomation describes a mixture of advanced technologies – robotics, artificial intelligence, machine learning – currently being used to make automated processes drastically more efficient and to augment humans. It encompasses a range of tools which can be automated, especially the more sophisticated aspects of automation, including analysis, discovery, design, measuring, monitoring, and reassessing. To function […]
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 […]
So You Want to Be a Data Engineer?
The work of data engineers is extremely technical. They are responsible for designing and maintaining the architecture of data systems, which incorporates concepts ranging from analytic infrastructures to data warehouses. Data engineers need to have a solid understanding of commonly used scripting languages and are expected to support the steady evolution of improved Data Quality, […]