Online survey and guide help organizations evaluate their level of data literacy, offer best practices for improving literacy for enterprises at all stages
TDWI, the leading source for in-depth education and research for analytics and data management, announced an update to its online assessment tool for evaluating an enterprise’s level of data literacy. This questionnaire objectively measures how well employees understand and interact with their data—and communicate the results of their analysis—enabling them to meet their organization’s analytics needs.
The accompanying TDWI Data Literacy Maturity Model Assessment Guide provides a primer on what’s driving the need for data literacy (including self-service and AI-driven analytics, diverse data types, and cloud data management) and explains the key components of a data literacy program. The update examines data literacy levels and results in each of the five data literacy maturity dimensions from over 150 enterprises that completed the assessment since its original release in 2021. It also offers tips for interpreting an organization’s assessment scores and provides guidance for companies at the beginning of their data literacy journey by explaining best practices used by companies that are more mature.
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Today, more organizations than ever before are expanding their data and analytics strategy to larger audiences across the enterprise. Fueled by trends in digital transformation, data monetization, and advances in analytics technologies, these programs are democratizing data-driven decision making and aiming to inform decisions at every level of the business and across every functional area. This trend is reflected in TDWI research, which shows that self-service ranks at the top of organizational priorities, with more advanced analytics (such as machine learning) not far behind.
To drive this expansion, businesses want to improve their overall data literacy. Data literacy involves awareness and recognition of the value of data, how well people understand and interact with data and analytics, and the ability to communicate data-driven insights to impact behavior and achieve business goals. It includes understanding the business, framing analytics, understanding data elements, critical interpretation, and communication skills.
“Data literacy is not only for business analysts; this is a critical skill for individuals across a data-driven organization, although the level of literacy may vary based on role. Whether interpreting visualizations produced by other people or building full-scale analytics models, understanding how to interpret and use data is a critical skill,” according to co-authors Fern Halper (vice president and senior director of TDWI Research for advanced analytics), Chris Adamson (TDWI education director), and Markum Reed (director of research for data management).
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“The Data Literacy Maturity Model can help guide organizations on their data literacy journey. It provides a framework for companies to understand where they are, where they’ve been, and where they still need to go to support data literacy.”
The assessment quantifies an enterprise’s progress toward full data literary across five key dimensions: culture and resources, data infrastructure, skills/talent, tools, and data governance. Because organizations can be at different stages in each dimension, the assessment tool scores each dimension separately and provides an overall score participants can compare with other organizations.
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