It doesn't matter what area you work in tech—even if you're only tech-adjacent—most organizations lag in efforts to ensure staff has the vital skill of a good grasp of data.
"Bilingual a plus" is a rote standard of job descriptions that now levels up in the tech industry.
The boon of data and analytics capabilities, as well as the increasing effectiveness of artificial intelligence, has made it essential that creators, including every department within the company as well as consumers "'speak data' as a common language," Gartner reported. "Data and analytics leaders must champion workforce data literacy as an enabler of digital business and treat information as a second language."
Data literacy is an organizational asset: Venngage Infographics released some suggestions for businesses to increase data-driven decision making, which in turn will fuel better performance.
"Data literacy is the ability to read data, work with data, and communicate about data by putting it in proper context," Venngage explained. It requires an understanding of how to assess data sources and collection methods and the various applications for a given data set.
SEE: COVID-19 workplace policy (TechRepublic Premium)
The Harvard Business Review stated: "Companies need more people with the ability to interpret data, to draw insights, and to ask the right questions in the first place. These are skills that anyone can develop, and there are now many ways for individuals to upskill themselves and for companies to support them, lift capabilities, and drive change. Indeed, the data itself is clear on this: Data-driven decision-making markedly improves business performance."
It wasn't all that long ago when interpreting data was left to the company's "gearheads," the business' tech specialists, the HBR also reported. Today, all team leaders and nearly all staff need to increase their abilities "inspiring the entire department to embrace data.
An apt example of how data literacy can improve productivity is for everyone on the team to understand projection reports, it better prepares everyone to work together toward a common goal.
In addition to collecting and analyzing data, it's equally important to be able to share it with colleagues and clients and how it is interpreted can mean great success or a slog through processes.
All challenges related to data literacy can be overcome, Venngage's report said, and outlined what it said are the seven things beginners need to know.
- Uncertainty is inevitable, communicate through visuals and infographics, using comparative estimates or projections.
- There are various types of data and it's important to understand what type you're working with: Mixed methods can either be qualitative or categorical and then subsequently nominal and ordinal or quantitative or numerical, which is either discrete or continuous. The latter can be interval or ratio.
- Data sources matter. Is the source reputable? Collection methods include surveys, interviews, observations and experiences. Secondary data access includes open or public, restricted or unavailable. Data can be aggregated or normalized.
- Keep it organized because managing data requires plenty of attention to detail and follow-through.
- Data can tell many different stories. Data itself says nothing, but analysis and insights guide an understanding. Look for patterns. Don't settle on the first one you find. Continue to dig deeper. Pay attention to outliers and anomalies. Be aware of your own cognitive biases and potential pitfalls as you conduct your analysis.
- Share data stories responsibly. Choose a visual to show key takeaways by describing the date, distributions of the data, comparisons in the data, never equate correlation with causation.
- You don't need to know everything. Still, continue to learn, practice working with data and share with others.
The report concluded, simple data visualization templates can build data literacy.
- How to become a data scientist: A cheat sheet (TechRepublic)
- Big data's role in COVID-19 (free PDF) (TechRepublic)
- Power checklist: Local email server-to-cloud migration (TechRepublic Premium)
- Volume, velocity, and variety: Understanding the three V's of big data (ZDNet)
- Big Data: More must-read coverage (TechRepublic on Flipboard)