In a world where 2.5 quintillion bytes of data are created every day, it’s not surprising that organizations want to harness the power of being data-driven.
In our 2022 Data Health Barometer, 99% of companies surveyed recognized that data is crucial for success — but 97% said they face challenges in using data effectively. Perhaps in response to those challenges, 65% of companies reported that they'd started a data literacy program.
Maybe you’ve been tasked with starting a data literacy program, or maybe you have read the research and want to be a champion of data literacy for your organization.
If so, this video will walk you starting a data literacy pilot. This 6-phase plan for starting a data literacy program can be scaled once you develop traction and prove the value (look at you, already being data-driven).
For our purposes, data literacy includes the ability to read, work with, analyze, and argue with data.
How to build your own data literacy program pilot
Phase 1: Planning and vision
Roles and responsibilities
The first question that might come to mind is, who should own the program? Typically, data literacy programs reside within the CDO office, but every organization is different. If you don’t have a CDO, it might belong with IT or another centralized data office. At Talend, our data literacy program originated from our centralized data office, which includes governance, data management, and analytics in one team.
Data literacy goals
As with any initiative, you should start by defining your end goals. What is it that you want to achieve by having a data literacy program? Start with the vision. Being data literate means that employees can read, interpret, and understand data in context. Context is foundational — how can an employee read data in context without knowing the context of your data? Or said another way, where does your data come from, who or what uses it, and how is it created or transformed?
Data literacy tools
Governance tools are important in laying the foundation of data literacy because they provide metadata management — the data about your data. Focusing on this foundation can help you identify your stakeholders and pilot participants and the value your program can bring. What tools exist within your organization, or need to be procured, to achieve your goals? Your participants will need user-friendly access to data, with tools that provide enough data context while also protecting sensitive data.
Once you’ve defined data roles and responsibilities, goals, and tools for your data literacy pilot, you can build the rest of your data literacy framework around it. This framework will be monitored, iterative, and scalable.
In Talend’s own program, we decided to start at the foundation — data context — and enrich our metadata through tribal knowledge. So, we started with the analysts who work with the data day in and day out. We communicated the value of their knowledge, not just to new members on their team but to all employees across the organization who want to make better decisions based on the analysts’ work.
Phase 2: Communication
Phase 3: Increasing access — with the right access
Whatever the goals of your program are, you’ll need to give employees access to the data you’re training them to use. Is that data well-understood, documented, and trusted? We recommend focusing on a tool that helps you answer those questions and provides a means for data shopping, what’s sometimes called a data mart. Further, you’ll need a way to govern access through policies and other authentication tools. But more importantly, you can’t just give access to all data, especially protected data — this is where data masking and encryption can be useful. And many users will need more than read-only access; you’ll want them to be involved in data stewardship and able to share data with one another.
Phase 4: Enablement
It isn’t enough to have access to data and tools — you must also enable the participants. The effort involved could be minimal if you’re using tools that are easy to adopt or already being used by your organization. On the other hand, if your tools have a steep learning curve you might have to develop training yourself. Either way, it will help if your organization has an intranet site or similar central location for employee education.
Phase 5: Sustaining adoption via building a data culture
You’ll need to maintain sustained adoption and continuous learning. This is where it’s helpful if you already have a one-stop shop for employee training. I recommend regular sync meetings with participants plus providing tips and tricks on a weekly basis of new ways to discover data. You can also gamify the experience, giving participants badges or kudos for enriching metadata or completing learning plans. Sustaining adoption creates a data culture within your organization, one that promotes the value and use of data to improve decision-making.
Phase 6: Evaluating and reiterating
Your program will get better and smoother as you learn from your own experience. We recommend that you assess participants’ knowledge prior to the start of the program, midway, and then at the close of the program to measure impact and value. You’ll want to include measures to assess the change management. A great methodology to follow is ADKAR, which assesses if participants are at the Awareness, Desire, Knowledge, Ability, or Reinforcement stage of change management.
Scaling up a data literacy program
The progress of your pilot and success stories that come out of it will help build the momentum to scale the program to other business units. You may also increase the scope of the program, to build employee skills on data analysis, storytelling with data and data visualizations, or any other data competencies relevant to your industry.
I hope this blog post and accompanying video are helpful as you consider starting or furthering your organization on a path to data literacy.
Get started today
At Talend, we use our own tools for metadata management, data governance, and data stewardship. Learn how Talend can enable your data literacy project: talk to a Talend expert.
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Data Integration