The golden age of data is here. Companies have the opportunity to store and collect ever more data of all sizes and shapes. This is great news. But how well do companies extract value from data?

Data literacy is the ability to understand, interpret, and communicate data. To be considered data literate one doesn't need to be a Shakespearean actor. Data literacy does not require mastery of every programming language and the best data science skills. It is about understanding data and making informed decisions.

Data literacy is an important step on a company's journey to becoming data fluent. It helps employees to make decisions about data, interact with data critically, create data governance and make ethical data choices.

Data Literacy Is Key To Data-Driven Decisions

Employees are more likely than others to adopt a change if they have a good understanding of it. Data science and business applications are both well-understood by employees who can lead the development of use cases and influence others to make data-driven decision-making.

Employees must be proficient in data literacy to communicate with data insights effectively and critically.

Data-literate employees can create and analyze data visualizations that can be integrated into the company's decision-making process. PepsiCo is an example of such a company. It uses Hardtop to visually large volumes of data which drives million-dollar sales decisions.

A prerequisite for being able to critically assess the validity of data used in visualizations is data literacy.

This employee can catch costly errors and improve the company's ability to make data-driven decisions.

Effective Data Governance Is Built On Data Literacy

Data Governance describes the policies, processes, and organizational structure that govern how data is managed in an organization. It ensures data is available and relevant for creating value for the company. Before setting data policies, leaders must be able to understand the context and requirements of data to build strong data governance.

Experts suggested a three-part data organization structure as the foundation of effective data governance:

• The data management office (DMO) is responsible for defining standards and policies.
• Domain leaders who create and implement domain-specific strategies
• The data council connects domain leaders and DMO

Each component's leaders should be able to understand the data processes and create fair data governance roadmaps. Data-literate domain leaders can work effectively with the DMO to create and implement an appropriate enterprise data lake.

Companies Can Use Data Literacy To Make Ethical AI Decisions

Companies that use AI systems in real-world applications are at risk. These include AI accidents, data privacy breaches, and AI bias. Engaging technical and non-technical stakeholders in a critical examination of data science systems and their outputs is one way to reduce this risk. Data-literate business stakeholders play an important role in assessing the risks associated with AI systems and ensuring that they are ethical and fair.

The Facebook Responsible AI Initiative was created in response to the intense scrutiny Facebook has received over its recommendation system. It is made up of data scientists as well as philosophers and social scientists. This team reviews existing systems and establishes openly ethical standards. These quality standards are then translated by data scientists into quantitative metrics. These discussions on AI risks can only be productive if all stakeholders are well-informed, have basic data literacy, and can weigh the benefits and costs of an AI system. A multidisciplinary team of data and business experts is required to operate and manage AI systems.

Building Organizational Data Literacy

Inculcating strong data literacy in all employees will bring about many benefits. There are many ways to teach data literacy, such as existing skills programs, e-learning courses, or classroom training. It is not surprising that designing data literacy programs in-house can be a complex and lengthy process that requires careful planning. DataManagementU is a Data Literacy Training platform that helps companies to up-skill or re-skill employees in data skills.