Building a bridge between AI and BI to maximize business outcomes
By Zohar Bronfman, contributing writer for Forbes.com
Every company gathers data and lots of it—customer data, market data, competitor data and industry data. Cloud systems, software as a service (SaaS) and business intelligence (BI) tools process zettabytes of data each year. But how many companies are able to make the best use of this data using the tools and teams they have today?
Data science vs. Decision science: What’s the difference?
By Chris Dowsett, contributing writer for Builtin.com
At Instagram, we had many different job roles that analyzed data. A few of the data job titles included: data scientist, analyst, researcher and growth marketing.
Four ways Big Data analytics can add to profits
By Umme Sutarwala, contributing writer for Enterprisetalk.com
In recent years, big data analytics has gained a lot of attention in the commercial world. The growth in popularity appears to have no end in sight. As the physical world fell quiet and individuals spent more time online than ever before, the COVID-19 pandemic prompted businesses to start or increase their usage of data analytics.
Global experts: 5 areas where ML could enhance health economics and outcomes
By ISPOR, contributing writers for Medicalxpress.com
Value in Health, the official journal of ISPOR—the professional society for health economics and outcomes research—announced today the publication of new guidance for health economics and outcomes research (HEOR) and decision makers in the use of an important class of artificial intelligence techniques. The report, “Machine Learning Methods in Health Economics and Outcomes Research—The PALISADE Checklist: A Good Practices Report of the ISPOR Machine Learning Task Force,” is published in the July 2022 issue of Value in Health.
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