There is little doubt machine learning has become one of the most powerful technologies in the last decade. The emphasis on “learning” in machine learning allows computers to make better and better decisions, based on previous experiences. Advances in this technology have allowed for recent breakthroughs that promote faster and more efficient business intelligence, using […]
2020 DATAVERSITY Top 20
With 2020 now behind us, we here at DATAVERSITY are taking a moment to look back on the hits and misses of this unprecedented year. What content did you, our readers, seek out most during challenging times? Which topics helped you succeed as a data professional, and what should we focus more on in 2021 […]
Data Versioning Matters to Data Science
Amazon Web Services (AWS) recently published a case study about how the Allen Institute for Cell Science — which was founded by Microsoft’s Paul Allen to research how the human brain works in health and disease — is taking new steps to make its data and metadata easy to access, search, and redistribute for internal […]
Data Science Trends in 2020
The exponential growth of data, partly generated by sensor-driven devices, is making Data Science and machine learning (ML) market differentiators in global business-analytics solutions. With the rising demand in Data Science and ML skills, 2020 may well be a witness to several new trends in the field. According to IDC: “[I]f our digital universe or […]
2019 DATAVERSITY Top 20
It is once again time to look back and evaluate the struggles and successes of the previous year and then build those lessons into the year to come. Part of how we do that here at DATAVERSITY is to look at the content consumed by the community over the year and evaluate what was hot […]
It’s Time to Productionize Data Science
To make Data Science part of business value creation, business users have to be part of the Data Science lifecycle. They need to be able to go back to Data Science teams and provide feedback so that the Data Science process reflects their requirements — and quickly. Models may need to be updated or functionalities […]
The State of Data Science: Expertise Shortage Creates a Need for Innovation
The world’s most valuable resource is no longer oil but data. As a result, the skills required to convert data into insights that generate revenues are in high demand. Unfortunately, one of the biggest hurdles companies face when trying to capitalize on their data sets is a lack of data scientists and machine learning practitioners. […]
2018 DATAVERSITY Top 20
As we wrap up 2018 and prepare ourselves for 2019, it’s time to take a moment to review and reflect. And while in review, we take the opportunity to look at the content published, produced, and consumed over the last year. In looking at the top 20 published articles and blogs of the year, Machine […]
Data Science Trends in 2019
When it comes to major Data Science trends to watch in 2019, the co-founder and CEO of Kaggle, Anthony Goldbloom, has predicted that very soon Data Centers will be replaced by departmental or business-specific Data Science teams. As discussed in Data Science Trends in 2018, last year’s major trends continued from 2017 as the growth […]
The Future of NLP in Data Science
According to many market statistics, data volume is doubling every two years, but in future this time span may get further reduced. The vast portion of this data (about 79 percent) is text data. Natural Language Processing (NLP) is the sub-branch of Data Science that attempts to extract insights from “text.” Thus, NLP is assuming […]