GRC-107 - Building A Data Literate Culture In Your Organization

For many businesses, digital transformation is the name of the game these days. This is based on a diverse and impressive set of new (information and communication) technologies that have an increasingly significant impact on business outcomes. Data, analytics, intelligent automation, and artificial intelligence have advanced to the point that they are now essential in the digital transformation era. The development of a data-driven culture aids in the achievement of these positive business results.

While most businesses are focused on the potential of data-driven technologies (such as data lakes, data platforms, and artificial intelligence or machine learning), these technologies must be carefully nurtured to become a trusted core competence. Scalability, repeatability, and effective deployment, where algorithms are utilized to support humans, and data-driven technologies are embedded into enterprises' day-to-day operations, are frequently the only ways to get the actual value.

To fully enable people, they must have a more excellent knowledge of the insights data may bring through analytics and how they can use it to improve their work. People must learn to 'talk' data and become more data-literate for data to become a native language. Data literacy – the ability to comprehend, engage with, analyze, and reason with data – is critical in establishing a data-driven culture within a company.

Duration: 1.0 day

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After completing this course, students will be able to:
  • Definitions of data literacy 
  • Understanding a data literacy culture 
  • Data literacy culture 
  • Characteristic of a data literacy culture 
  • Data personas How important to have a data literacy knowledge 
  • Why analytics is important Data storytelling


Module 1: What is Data Literacy?
  • The importance of Data Literacy 
  • Data Literacy culture 
  • Characteristics of a Data Literate culture 
  • Data personas 
  • Data Literacy culture implementation

Module 2: Data Literacy Adoption
  • Statistic of Data Literacy adoption 
  • Data inequality 
  • Challenges for enterprise leaders 
  • 6 step Data Literacy Adoption Framework 
  • 4 Data Personas from the Assessment Step

Module 3: Why Analytics?
  • Who should take an analytics course?
  • Define analytics

Module 4: What is Data Storytelling?
  • Visual and context 
  • Key elements to building data storytelling skills 
  • Mechanism of Data Storytelling 
  • Storyboarding 
  • Visuals/diagrams to avoid 
  • Wireframe of Storytelling




No prerequisites.



Course Benefits

  • Career growth
  • Broad Career opportunities
  • Worldwide recognition from leaders
  • Up-to Date technical skills
  • Popular Certification Badges

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