What exactly is technical debt? When discussing your organization’s technical debt - and possible changes to it - with various audiences, you need to articulate the key issues in plain terms. Here’s expert advice on how to do that.
How to create data literacy: 3 keys
To build true data literacy, empower your employees to speak the language of data with confidence
Data is a pivotal language being spoken in your organization today that crosses every demographic. Employees who understand this subject create a powerful advantage for organizations eager to unlock its value.
Yes, we have more tools than ever before, which seemingly should make it easier to tap the transformative abilities of data and analytics. But the new products and services billed as the answer to your information problems are not likely to get you far without enough employees who have a true understanding of the data itself.
What can you do to get a better return on your data?
A long-term investment in data literacy across the entire organization can get you farther, faster than pointing a select group of experts at data questions. It won’t happen overnight, but it will last, resulting in a pool of skilled data users in every function of your business.
How do you get started? We’ll assume you have trusted data, governance is in place, and a basic dictionary exists for consistent use of terms – or you’ve at least begun work in these areas to ensure your data is clean (fit for purpose) and accessible.
[ Many people misunderstand big data. Read also: How to explain big data in plain English. ]
We believe you can create true data literacy at an enterprise level by investing in three areas: Developing associates’ data literacy, giving them opportunities to use their new data analysis skills, and supporting data conversations across the company. Let's explore how to tackle each area:
1. Learn it: Nail the basics of data literacy
A data literacy program creates associate development opportunities. Say you take three classes in Portuguese and you learn the vocabulary and the basic rules of grammar. You gain an appreciation for the language, you can read it, and you can make basic sense out of what others are communicating.
To this end, we offer classes to help Red Hat associates develop their data literacy skills in a way that’s appropriate based on their role in the organization. Whether they are just starting their data literacy journey, are data practitioners, or are data leaders/advocates, everyone can grow their skills. Not everyone will have the same end goal but everyone can learn from seeing real data stories of business value gained. For example, we have courses ranging from “The Power of Data Visualization” to “Data Storytelling.”
This is a great start, but who hasn’t taken a class and walked out the door (or logged off) with the best of intentions but no real plan for using the new knowledge. What happens? You never really feel confident in speaking the language.
2. Use it yourself: Put it into practice
A data literacy program supports employee enablement. If you visit a country full of native speakers you get to use your new knowledge. You also get a deeper experience of the culture that is a part of the language, the context, the reasoning.
We push out data in a variety of dashboards so everyone can experiment and consume it for their part of the business. We look for ways to integrate terms and definitions into our dashboards, data visualizations, etc., which reinforces a consistent data language at the point of use. We demonstrate the value of verifying data by making the path to certification visible. Not all data is perfect, but where it is on the journey is important for a user to understand.
3. Use it with your teams: Have data-centered conversations
A data literacy program promotes engagement with data throughout the organization. Associates can connect the dots and make informed decisions. You have richer conversations as a team when everyone contributes because they are speaking the same language (using terminology and concepts the same way across the organization.) This creates accountability and credibility for your data analytics.
Increasing the number and quality of data conversations across the organization requires everyone to model this behavior. Not every analyst is going to interact with leadership on a daily basis, but this is where a lot of those conversations begin. At Red Hat, we have communities of practice, user groups, and regular demos where anyone can sign up to present. These are open to everyone who wants to listen, discuss, or share their knowledge. If everyone can speak data, then everyone can contribute, which is a part of our culture.
Data-informed decision-making can be a key differentiator for all organizations. However, the missing piece – the thing that turns all of that information into actual business value – is data literacy. Creating true data literacy requires empowering your employees to speak the language of data with confidence. When you build that understanding, you’ll be more successful at strategically weaving data into the foundation of your company, products, services, and processes.
[ How can automation free up more staff time for innovation? Get the free e-book: Managing IT with Automation. ]