Posts by Melody Smith
Data Driven Integrity
Data integrity is of paramount importance in business decision-making. Improving data integrity involves implementing measures to ensure the accuracy, consistency, and reliability of data throughout its lifecycle. CMS Wire brought this interesting topic to us in their article, “Maximizing AI and Machine Learning with Quality Data.” In conjunction with data integrity, it is critical to establish…
Read MoreRevolutionizing Information Science: The Impact of Deep Learning
In the digital age, where vast amounts of data are generated and consumed every second, the field of information science has evolved significantly. One of the most transformative technologies driving this evolution is deep learning. Deep learning is a subset of artificial intelligence (AI) and has proven to be a game-changer in improving the efficiency,…
Read MoreCan You See the Data?
The more data you have from different sources and stored in different spaces, the more likely it is to be scattered. This interesting information came to us from Blocks and Files in their article, “Data fragmentation needs a data intelligence fix.” Data visibility means knowing what data you have and where it came from, and…
Read MorePeer Review and Compliance
Trust is important in any industry. When it comes to publishing scientific and academic journals, it couldn’t be more important. The Scholarly Kitchen brought this interesting and important topic to our attention in their article, “Revisiting — Compliance: The Coming Storm.” A high level of trust is essential to ensure publication and sharing of research…
Read MoreGoverning Healthcare Data
Data governance in healthcare is essential for upholding patient privacy, ensuring data integrity, supporting clinical decision-making, facilitating research, and maintaining regulatory compliance. All these measures ultimately contribute to better patient care and overall healthcare system efficiency. This interesting information came to us from Health Leaders in their article, “Why Data Governance in Healthcare is Essential…
Read MoreAI in Daily Life
Artificial intelligence (AI) and machine learning are becoming daily terminology not only for professionals but also consumers. This interesting topic came to us from Built In in their article, “How Artificial Intelligence and Machine Learning Will Reshape Enterprise Technology.” AI is more common than anyone may think. It is being used worldwide across multiple industries including healthcare and…
Read MoreAnalytics and AI
Artificial intelligence (AI)-powered systems can analyze data from hundreds of sources and offer predictions about what works and what doesn’t. AI can also apply data analytics about customers to predictive algorithms about their preferences, including informing product development and marketing channels. This interesting information came to us from IT Web in their article, “The (near)…
Read MoreThe Power of AI and Cloud Computing
As businesses are expanding and evolving, they are looking to cloud computing and artificial intelligence (AI) for solutions. Cloud computing offers numerous benefits, such as scalability, cost efficiency, and accessibility, but it also comes with specific security risks. It’s essential for organizations to be aware of these risks and take appropriate measures to mitigate them.…
Read MoreBusiness Intelligence Relies on Data
Data management continues to be critical for optimizing data usage and driving better business outcomes. Tech Target brought this interesting information to our attention in their article, “Data management trends: Convergence and more money.” Many organizations have struggled to deal with the ongoing impact of the pandemic, inflationary concerns, and the specter of economic slowdown.…
Read MoreLearning From Machines
Since machine learning models are imperfect, people must understand when to believe a model’s predictions in high-stakes situations. MarkTechPost brought this interesting news to our attention in their article, “MIT researchers have developed a new technique that can enable a machine learning model to quantify how confident it is in its predictions.” Robust machine learning…
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