Data Literacy

Data Literacy is a term used to refer to the ability to understand, create and communicate data in the context of a given activity or role. It involves understanding the presented data and general knowledge about the sources, methods used for analytics and transformation, and the ability to extract insights or develop new use cases for a given data asset. Data literacy is one of the skills necessary to have a basic level of digital dexterity that empowers users within a given organization to utilize new technologies to drive business value.

In recent years, companies and organizations have been championing initiatives to improve data literacy to create a data-driven culture that makes everyone within that organization use data to sustain business decisions and remove human biases. Regardless of their role, all users can benefit from a clear understanding of the context of data. This is in part thanks to data democratization processes.

Driving data literacy within organizations generally involves the role of a Chief Data Officer who is in charge of assessing the level of data literacy, creating metrics, and championing initiatives that seek to create a data-driven culture.

To develop these initiatives, CDOs can propose a series of questions that later on will be helpful to create metrics that data leaders can use to assess the success of data-literacy programs and workshops. Some of the questions that CDOs can frame are:

  • Within the company, what is the number of people that have a basic understanding of descriptive statistics like average, standard deviation, and so on?
  • Out of the managers, establish how many of them can build a solid business case that substantial numbers can back.
  • Determine the number of managers with a good understanding of outputs generated from business analytics and reporting tools.
  • What are the organization’s machine learning needs, if any? If so, can the data scientists use their outcomes to create a business case that the leadership can interpret?

CDOs can use these questions and others to create KPIs and initiatives that seek to improve the data literacy of a given organization. These questions can also point out skill gaps that organizations can overcome by rolling out training programs and workshops. These programs and workshops should focus on developing skills that are specific to the roles of each user.

To effectively design training programs, the champions of these initiatives should start by defining the intended goals, which can be based on the answer to the previously mentioned questions. Once the plans have been clearly defined, the next step involves identifying native and fluent data speakers who might be data translators and mediate between users and business stakeholders.

Next, it is essential to establish clear communication channels and the barriers that might be impeding the adoption.

Finally, it is crucial to create flagship initiatives that are backed by the leadership. Such initiatives ensure that the adoption is based on a need established by the managers.

To achieve the ambitious goals of the Data Literacy initiatives and address the skill gaps, CDOs should roll out training programs to create an environment where learning Data Analytics skills is a part of the organizational culture.

Cloud Data Security with Satori

Satori, The DataSecOps platform, gives companies the ability to enforce security policies from a single location, across all databases, data warehouses and data lakes. Such security policies can be data masking, data localization, row-level security and more.

Learn more: