Synthetic data is at an inflection point of utilization. The emerging technology is just beginning its adoption cycle and value to the enterprise, but change is on the horizon. According to my company’s recent survey, industry leaders believe that, on average, 59% of their industry will utilize synthetic data in five years, either independently or in combination with […]
Semantic Technology Trends in 2022
Semantic technology trends are expanding well beyond an interesting, more advanced search engine. Besides providing scientists with a more functional search engine, semantic technology is now being used to improve artificial intelligence and machine learning. Semantic technology uses a variety of tools and methods designed to add “meaning” to a computer’s understanding of data. When […]
How to Prepare Data for AI and ML
Regardless of how clever the machine or how brilliant the algorithm, the success of intelligence-based solutions is intrinsically tied to the quality of the data that goes in. That’s why, aside from its people, data is the most important thing an organization owns. Data must be the first stop on the journey to implementing artificial […]
Data Science vs. Decision Science: A New Era Dawns
Data Science vs. Decision Science: Basic Descriptions In Data Science, a variety of advanced technologies like data mining, statistics, predictive analytics, AI, and machine learning are used in conjunction to deliver solutions for business problems. In Decision Science, analyzed data is “interpreted” to arrive at business decisions that meet specific objectives. So while Data Science […]
Unlocking the Value of Hidden, Unstructured Data
Data is the fuel of the fourth industrial revolution. Data is the lifeblood of the enterprise. Data powers the information age. We’ve heard these statements so many times that they’ve almost lost their meaning. But what if I were to tell you that you are only using 10 to 20% of this fuel to power […]
How Data Automation Is Reshaping Pharma Regulatory Publishing
Pharmaceutical regulators are facing ever-evolving, complex, and stringent requirements for the regulatory approval of new and existing products on the market. What’s more, as technology changes our ability to capture data from more sources, the volume of data in the life sciences sphere is growing exponentially, creating a challenging data analytics paradigm. The key is how to […]
How to Start Using AI at Your Company
So you want to start using AI at your company. Now what? First, evaluate if it has an appropriate place in your company. Many organizations hire a data scientist or an entire AI team with an anticipation of a fast, massive, magical gain. Even though by now most people realize that these expectations are naive, […]
Integrated Deployment – Deploying an AutoML Application with Guided Analytics
Welcome to our collection of articles on the topic of integrated deployment, where we focus on solving the challenges around productionizing Data Science. So far, in this collection we have introduced the topic of integrated deployment, discussed the topics of continuous deployment and automated machine learning, and presented the autoML verified component. In today’s article, we would like to […]
Edge Computing: An Overview
Edge computing (EC) allows data generated by the Internet of Things (IoT) to be processed near its source, rather than sending the data great distances, to data centers or a cloud. More specifically, edge computing uses a network of micro-data stations to process or store the data locally, within a range of 100 square feet. […]
The Intersection of Self-Service Analytics and Machine Learning
The terms “self-service analytics” (SSA) and “machine learning” (ML) are frequently used interchangeably, but the concepts behind these terms are a world apart. In self-service analytics, specific tools are designed to aid the user in inputting data or interpreting results (output). On the other hand, a machine learning algorithm is a special software that has […]