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Fundamentals of Digital Twins

Digital twins can present a virtual replica of physical components, processes, or systems to enable improved understanding of the performance characteristics of such entities. With digital twins, industry operators can visualize, predict, and optimize the performance of individual components within a system or process, or the entire process from a remote location. According to Microsoft, […]

Data Science vs. Data Analytics

The data scientist and the data analyst represented two of the “most in-demand, high-paying jobs in 2021.” The previous year, the World Economic Forum Future of Jobs Report 2020 listed these jobs at the top of a list representing most in-demand jobs across industries. In data analytics, which is often referred to as business analytics, […]

Case Study: Executing an Effective Data Strategy

Few tasks are more logistically and technologically daunting than providing air, land, and sea transportation for the U.S. military across the entire world. Yet that is precisely the mission of the United States Transportation Command, or USTRANSCOM. According to a Congressional Research Service report, on any given day USTRANSCOM conducts over 240 air missions, sends […]

Self-Serve Advanced Analytics Requires Culture Change

Small and medium-sized businesses (SMBs) are often challenged to satisfy all the roles and responsibilities in the organization, and most team members wear more than one hat. That feeling of being overstretched is typical of growing businesses and, in an increasingly competitive market with businesses fighting for skilled resources, it is difficult to meet budget […]

How to Become a Data Analyst

Data analysts translate raw data into useful insights, and they are also responsible for gathering the data, organizing and analyzing it, and then presenting their findings. Data analysts are in high demand, and there aren’t enough data analysts to fill all the positions. People with the right skills can fill these positions. A degree is […]

Data Science: How to Shift Toward More Transparency in Statistical Practice

Data Science and statistics both benefit from transparency, openness to alternative interpretations of data, and acknowledging uncertainty. The adoption of transparency is further supported by important ethical considerations like communalism, universalism, disinterestedness, and organized skepticism.  Promoting transparency is possible through seven statistical procedures:  Data visualization Quantifying inferential uncertainty Assessment of data preprocessing choices Reporting multiple models Involving […]

Data Science Best Practices

When done right, Data Science delivers a lot of measurable values like improved products and services, enhanced customer experiences, sales growth, new business developments channels, and overall business efficiency. However, according to most reliable industry publications, most Data Science projects fail because the Data Science best practices are not followed. Why Do Businesses Need Data […]

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 […]

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