Click to learn more about author Terence Siganakis. Organizations are constantly coming to us wanting help in becoming more “data-driven.” They want to improve their decision making, shifting the process to be more quantitative and less based on gut and experience. This is a worthy goal but is a little more complex than just putting dashboards […]
An Introduction to Integrated Deployment
Click to learn more about author Paolo Tamagnini. Welcome our integrated deployment blog series, where we focus on solving the challenges around productionizing Data Science. Topics will include: Resolving the challenges of deploying models Building guided analytics applications that create not only a model but a complete model process, using our component approach to AutoML […]
What Are Simple Random Sampling and Stratified Random Sampling Analytical Techniques?
Click to learn more about author Kartik Patel. This article discusses the analytical technique known as sampling and provides a brief explanation of two types of sampling analysis and how each of these methods is applied. What Is Sampling Analysis? Sampling is the technique of selecting a representative part of a population for the purpose of […]
The Future of Augmented Analytics: Adding the “Why” into Your Business Reports
Click to learn more about author Neerav Parekh. Data is the new oil, and unlike oil, we are never going to run out of data. With more and more data being produced each minute, businesses have massive, complex datasets that are difficult to deal with. Digging deeper into the data to uncover valuable insights is […]
Tapping the Value of Unstructured Data: Challenges and Tools to Help Navigate
Click to learn more about author Daniel Martin. The amount of data generated in the digital world is increasing by the minute! This massive amount of data is termed “big data.” We may classify the data as structured, unstructured, or semi-structured. Data that is structured or semi-structured is relatively easy to store, process, and analyze. […]
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 […]
How Synthetic Data Powers Real-World AI Applications
Click to learn more about author Ashok Sharma. Machine learning (ML) algorithms are everywhere these days. AI applications aren’t something that will be present in the future. They’re already here and have begun making an impact on our lives. AI usage is currently in an embryonic stage and faces significant challenges. The biggest challenge surrounds the […]
Data Management and Healthcare Data
Click to learn more about author Conor O’Flynn. Accurate and complete data is an indispensable tool for healthcare professionals and patients alike, and it is an essential part of the medical profession. Patient notes have been modernized and replaced with electronic patient records that allow clinicians to view a patient’s medical history in seconds. At […]
2021 Crystal Ball: What’s in Store for AI, Machine Learning, and Data
Click to learn more about author Rachel Roumeliotis. Artificial intelligence (AI) is no longer a “nice-to-have.” From business processes and smart home technology to healthcare and life sciences, AI continues to evolve and grow as it plays an increasing role in many aspects of our work, home lives, and beyond. As we bid 2020 a […]
What Will Machine Learning Fraud Models Look Like in 2021?
Click to learn more about author Trevor Anderson. 2020 will forever be known as the year the coronavirus pandemic swept the globe. Coping with the crisis pushed organizations across industries (as well as consumers) into drastic shifts. In some cases, trends that were expected to play out over a decade accelerated to just a couple […]