Communicating data is an essential skill and it is not just about doing complex coding. Data literacy is about deriving value from data and Dr Kirk Borne who is a data scientist and an astrophysicist and also a leading AI influencer spoke at plugin 2020 about the importance of being data literate for the future of work. He addressed how it is important for both individuals and to organizations to be data literate.
He addressed five aspects of it — data awareness (what is it?), data relevance (why me?), data literacy (show me how), data science (where’s the science?), and the data imperative (create and do something with data). He also discussed why it is important for data scientists to lead the efforts to build data literacy in society, in schools, and in professional development activities for organizations.
As Borne shares, Data Literacy is a way of thinking about numbers and measurement of things in a way that gives meaning. It is interesting how we learn about the world using data. Essentially what we see and the information that we collect is data. “We gather data and information, from which we derive knowledge and wisdom from which we decide what actions to take,” he shared. It is about connecting dots and seeing how it makes sense.
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Data exists in a lot of different ways such as databases, data tables, images, graphs, documents, social networks, phone apps, web clicks, time series, speech, audio and more. And the biggest challenge about it is not volume but the complexity of it.
Organisations in various industries also collect data on many different and complex sources of data, especially financial organisations. These diverse datasets are often stored in separate silos such as customer data, marketing data etc. This inhibits data teams from integrating multiple datasets that when combined could yield deep, actionable insights to create business value. “What we have is a lot of information but very few insights. Data literate is a person who knows data, how to integrate it and combine it to create value” said Borne. Data Literacy includes the ability to read, work with, analyse and argue with data.
“While collecting data is one aspect of it, the next big question is how relevant is it for me. A lot of data is generated in a minute which comes from everywhere and each person creates data. Data relevance is not just about creating value of data and not just showing complex data,” he says.
Data relevance is especially important in today’s era where digital transformation is the most essential technology. Various technologies such as AI, robotics, machine learning, deep learning depend on lots of data to make value for organizations. “Especially in the COVID times, the digital frontier is moving rapidly and has accelerated development in space,” says Borne.
Data Literacy is a way of thinking about numbers and measuring insights from it. For instance, if there are different formats of data, a data-literate person should be able to normalise these data and find a similarity in all these numbers to generate insight. Data literacy is understanding that something can be done with every data. “For every data that was initially thought to be useless, it is possible to normalise it and make sense of it. Data literacy also includes business understanding, data exploration, data representation and more.
Another important component of data literacy is data storytelling. Connecting with data and communicating it in a way that is understood by everyone is the key aspect of it. Communicating stories and insights and data is a powerful tool to convey stories.
Data Science is a crucial part of bringing about data literacy. Data is the fuel whereas science is a process by which patterns are extracted and actions are taken. And when we talk about data science, it is not just about having math skills or engineering skills but understanding to create value out of it.
It is essential to have data and data literacy in place as poor data literacy may cripple the business. “Data is everywhere and data science is crucial to understand data and drive value out of it. Data science is not just a strategy but corporate thinking,” concludes Borne.