A beginner’s guide to data literacy and the skills your employees need

What is data literacy?

Data literacy is the ability to read, understand, and use data to make better business decisions.

• It covers data types, sources, analysis, and simple tools.
• You do not need to be an expert to build it.
• It helps teams work smarter and cut risk.

Data has become a crucial tool for success in global firms. In fact, it helps companies make sharper choices and test their plans. Gathering data is easy. However, turning it into useful insight takes real data literacy. Most firms still do not call themselves “fully data-driven.” In fact, only 24% of organizations claim to be one.

With tight competition, the need for data literacy keeps rising. So this article explains data literacy and how firms can improve it. Data literacy refers to one’s ability to understand and interpret data. In general, it works like reading. So a person should know how to read, write, and apply information in different ways.

You do not need to be an expert to gain data literacy. Rather, you only need the basics, such as the following.

• Types of data
• Data sources
• Types of data analysis
• Tools and techniques for data interpretation

Why data literacy is crucial for a company

Gartner projects that data literacy will keep growing as a driver of business value. Yet “poor data literacy” is still a top roadblock for a chief data officer (CDO). Still, strong data literacy is the key to digital transformation. So it helps firms sharpen their edge in a fast, aggressive global economy. At the same time, it helps them achieve the following.

Better data-driven decisions

Data-literate teams help firms improve their processes and plans. As a result, they make informed choices instead of acting on gut feel. So digital change gets easier when everyone is on board. This matters because, according to McKinsey, staff agree to change more readily when they understand it. To see the payoff, look at the impact of data analysis on daily work.

Mitigated risks in artificial intelligence (AI)

Firms that use artificial intelligence (AI) face real risks to their data. For example, they may hit breaches, AI biases, and handling errors. So data literacy protects them from these threats. In fact, a CDO and their team can spot risks early. As a result, they can troubleshoot and prevent problems in advance. This keeps AI and machine learning systems safe and fair.

Added employee productivity and competency

Data-literate staff are more productive and more competitive at work. In fact, a recent survey by Qlik shows that 85% of workers say they perform well on the job. At the same time, more workers want to build their data skills. So the demand for data-driven firms keeps rising worldwide.

Data literacy skills your employees should learn

To become data-literate, firms should train and empower their staff. So teams need the following skills to handle data well. It also helps to know the difference between a data scientist and a data analyst.

Data analysis

Data analysis, also called data analytics, turns raw data into informed choices. So it involves gathering, checking, cleaning, and transforming data. Several types of data analysis exist. In fact, the right one depends on the purpose and the tech in use.

• Statistical analysis. Applies most to quantitative research. It studies trends in a large group by using a sample.
• Descriptive analysis. Deals with “what happened” in the past. So it describes the data without explaining the cause.
• Diagnostic analysis. Finds the root cause of a result. So it spots anomalies and responds to them fast.
• Prescriptive analysis. Looks at future outcomes and the steps to shape them. So it weighs each path and its likely result.

Data wrangling

Also known as data cleaning, data wrangling turns raw data into a usable form. Data wrangling can be done in many ways. For example, it may remove errors or merge sources. Firms with large volumes must clean their data often, usually with automation. So many also use data entry outsourcing to keep records clean.

Data visualization

Data visualization shows information in visual form, through text or images. So it aids understanding through charts, graphs, and maps. As a result, teams track trends and patterns with ease. In fact, it is key to making data clear for everyone inside and outside the firm.

Data ecosystem

A data ecosystem is the mix of infrastructure, apps, and tools used to collect and store data. Each firm reads data in its own way. Still, most use similar apps, such as online tools and cloud storage. An example is Hubstaff’s “tech stack,” a set of apps used to build websites and mobile apps.

Data governance

Lastly, data governance is the full system for handling and securing data. So it follows the standards and policies of the firm. It is usually written as a “data policy.” As a result, it keeps company data secure, complete, and trustworthy.

Building data literacy in your business

Data literacy is now a second language for firms worldwide. Yet most leaders still do not value their data enough. So they miss what it can do for growth. Many feel sure their teams can handle data. However, only a few teams are truly data-literate. This creates data literacy gaps that can hurt the whole operation.

Building data literacy is a smart move in a data-driven economy. So firms can improve it with the following steps.

Assess data literacy within teams

Leaders can assess data literacy by asking a few questions:

• How many people can interpret data in your team?
• Can your managers and staff explain their system outputs?
• How many teams can build decisions from real figures?
• Do your clients understand the data you share?

Establish training programs regarding data literacy

These days, employers must train their own workers on data literacy. So data officers should set up training programs for staff. As a result, this builds a culture of learning that rewards curiosity. You can also partner with an outsourcing firm to help train your staff. In fact, data management outsourcing can speed up this work.

Eclaro is a BPO company in the Philippines with data analytics professionals. So they guide clients to draw insights from their data through a thorough process. In fact, their help covers data profiling, governance, security, and management.

Choose a tool or system that’s easy to use

Data-driven staff work better with easy data processing software. Learning curves are normal with complex data. So a user-friendly tool helps them learn faster.

Include data in your company culture

Firms should make sure teams have the skills to use data well. Technology is not the only driver of data literacy. Rather, firms should add training and guidance for every skill level. As a result, data becomes part of daily work.

Frequently asked questions about data literacy

What is data literacy in simple terms?

It is the ability to read, understand, and use data. So it helps people turn raw numbers into useful insight.

Why is data literacy important for businesses?

It leads to better choices and lower risk. As a result, teams work smarter and grow faster.

What skills does data literacy include?

Key skills are data analysis, data wrangling, and data visualization. Data ecosystems and data governance matter too.

How can a company improve data literacy?

First, assess your team’s current skills. Next, set up training programs. Finally, choose easy tools and build a data culture.

Key takeaways

• Data literacy is the ability to read, understand, and use data.
• It drives better decisions and lowers AI risk.
• Core skills include analysis, wrangling, visualization, and governance.
• Training and easy tools help teams build these skills.
• Outsourcing partners can speed up data literacy work.