Solutions Review: Data Literacy Barriers and How to Overcome Them - Expert Advice

machine learning
     Data Society        
machine learning
     May 16, 2022          
machine learning                 News
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Originally published on Solutions Review

This is part of Solutions Review’s Premium Content Series, a collection of contributed columns written by industry experts in maturing software categories. In this submission, Data Society Co-Founder and CEO Merav Yuravlivker offers advice on data literacy barriers and how to overcome them.

Data literacy is far more than the sum of tools and terminology you have at your disposal. This holds true at both the individual level and the organizational level. Beyond understanding data, a data-literate workforce knows how to make optimal use of data assets by effectively extracting and communicating relevant data-driven insights. Organizations keenly aware of the critical role this kind of self-service business intelligence can play in driving their success are wisely investing in data science programs. However, common barriers impede the collective shift that organizational data literacy demands.

A successful transition to a data-driven culture is a function of both the correct skillset and the right mindset. One obstacle many organizations face on the road to data literacy is a limited understanding of how data science skills and tools fit into the larger picture of their industries. Data literacy, storytelling, and other technical capabilities don’t exist in a vacuum. Like other skills, they are elements of a broader collection of tools that are most effective when proficient practitioners combine them with conceptual knowledge about how to leverage them to meet specific industry needs.


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Data Society provides customized, industry-tailored data science training solutions—partnering with organizations to educate, equip, and empower their workforce with the skills to achieve their goals and expand their impact.

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