Data literacy tools: Understanding how they work together
Introduction to data literacy tools
If your career trajectory includes data-driven decision-making, you’ll need to prioritize becoming data literate. Whether you’re already a business professional or manager, or currently a student, data literacy tools are the key to developing an understanding of data and how to work with it.
This article introduces three kinds of data literacy tools, what they do, and how to get the most out of them.
To understand what data literacy tools are, we should first define data literacy. Gartner’s Data and Analytics Leaders’ Guide to Data says “Gartner defines data literacy as the ability to read, write and communicate data in context, including an understanding of data sources and constructs, analytical methods and techniques applied, and the ability to describe the use case, application, and resulting value.”
Data literacy tools are software, platforms, and training programs that enable users to access, understand, manage, use, and communicate data in context.
Types of data literacy tools
We group data literacy tools into three broad categories:
- Data analysis and reporting software that helps business users make data visualizations (graphs and charts), create business intelligence dashboards, or perform data analytics tasks
- Data management and access platforms that IT teams, data scientists, and data analysts use to get business data to the people who need it, with appropriate context and governance controls
- Data literacy training resources that build data literacy skills, ranging from free tools and datasets to internal programs to university classes or Massively Open Online Courses (MOOCs)
How data literacy tools work
Data literacy tools serve learners and end users differently depending on their working relationship with data.
- Data literacy software as we define it automates data analytics: finding patterns, crunching numbers, and populating reports for you
- Data literacy platforms make data available across an organization, integrating and governing data from multiple sources, and may include powerful automation and metadata management features
- Data literacy training resources empower individuals and teams with education to build their skills and gain confidence to do more with data
Building and sustaining a strong data culture requires all three types of data literacy tools.
Data literacy software
Everyday business software like Microsoft Excel, Looker, and Tableau puts data at business users’ fingertips. While these tools don’t always call themselves data literacy software, they fundamentally support the comprehension and communication of data. Business intelligence platforms like Qlik, product intelligence tools, Google Analytics, Airtable, or any other dashboard creation tool could also qualify.
Consider the real-world benefits of data literacy software:
- Supports data analysis without requiring a data analyst — no need for knowledge of statistics
- Helps business users generate data visualizations — make great graphics, charts, and infographics without graphic design skills
- Gives decision-makers the means to make data-driven decisions — no more guessing or going on instinct
Data literacy software also has some drawbacks:
- May have a difficult learning curve and require extensive training
- May promote vanity metrics, or make outdated or inaccurate information look more convincing than it is
- May lead to data silos if teams hold their own data in their own tools
Decision-makers in the business make better decisions when they have ready access to healthy data. The trouble is that basic data literacy software doesn’t do anything to ensure data health. Data-literate users will mostly know to avoid those pitfalls. Getting there will require the other types of data literacy tools: data literacy platforms, and data literacy training tools.
Data literacy platforms
When we talk about data literacy platforms, we’re talking more about governance tools. The right data management platform will enable access, create transparency, and ensure accountability across datasets. With a platform like that, a Chief Data Officer can promote data literacy across the organization. A complete data integration and management solution will support data literacy while giving central IT full visibility and governance controls.
Benefits of a data literacy platform
According to McKinsey, 87% of companies have a technical skills gap now, or anticipate facing one in the near future. Data platforms that reduce the need for technically skilled workers can alleviate the impact of this shortage.
A full-service data literacy platform reduces the need for shadow IT to access and understand data. It also reduces reliance on central IT, because business users don’t have to ask data scientists every time they need access to data. Algorithms can now perform matching and quality checking tasks that used to require data scientists.
With a full-featured and well-managed platform, everyone in the organization will learn to speak the same language of data. Decision-makers with broader access to trusted data can make better decisions to save money, raise revenue, and reduce risk. A governed data literacy platform also builds privacy and compliance into workflows, protecting you and your sensitive data from risk.
What to look for in a data literacy platform
Look for these elements in a data literacy platform:
- Data inventory with built-in governance so more users can self-serve business-critical data
- Data catalog or governance catalog with collaborative metadata management, full data lineage, and a UI built for business users
- Data stewardship capabilities to make data management an interactive team sport
- Business glossary or data dictionary to establish a common language for communicating about data
- Quality and trust metrics that help users evaluate data and build data trust
- Artificial Intelligence and Machine Learning (AI and ML) features to automate manual data management and analysis tasks
Demo: Building data literacy with a data literacy platform
It should be no surprise that Talend’s data literacy program relies on our own platform. We teach Talend employees to find, trust, and use internal data with Talend Data Catalog and Talend Data Inventory.
Talend Data Inventory provides a user-friendly web interface for datasets we’ve made available internally. Data engineers and citizen integrators alike can find, share, and collaborate on those datasets without relying on IT or writing any code. The built-in Talend Trust Score™ delivers metrics that build confidence in company data — or help point to problems that need solving.
Talend Data Catalog is ideal for privileged datasets that include personally identifying information (PII) or other sensitive data. Most Talendians are assigned consumer or read-only access. We can assign data producers read-write access to certain features based on their role. For example, data owners and stewards for particular datasets will have producer access that lets them update the glossary and add notes.
The Business Glossary helps eliminate ambiguity in conversations about data. It’s our source of truth for documenting definitions for terms across the organization. That way, no one has to wonder about internal acronyms, metric definitions, or industry terminology.
Try Talend Trust Score™ for yourself with the Talend Trust Assessor tool. You can upload your own .csv file or use our sample dataset.
Data literacy training resources
The data literacy software and platforms above are sophisticated tools. To benefit from them, users will need training.
If you want to learn how to get the most out of your favorite software, you have several options. Data literacy software usually includes some training or tool tips. The most popular tools are also supported with third-party trainings and how-to videos. There are even community education and college courses focused on learning popular software including Microsoft Excel and Tableau. Browse online courses, for example, through Coursera to see what is available.
Some data management and governance platforms also provide their own training resources. For example, Talend provides a developer community, technical blog, Talend Academy, on-demand webinars, and a YouTube channel to support learners — not to mention resource pages like the one you're reading right now.
Software-specific trainings won’t always teach foundational data literacy skills, however, such as how to read different types of graphs or how to evaluate data quality. Hands-on learning is typically best for learning data literacy skills.
Consider these steps to start evaluating data literacy tools:
- See what training your software vendors offer to get the most out of your favorite data analysis tools and dashboards
- Look for third-party training for your favorite data-related tools
- Teach yourself data literacy using free tools from Data Education in Schools' List of Apps & tools to support data literacy
- Find a data literacy course on SolutionReview’s list of The 9 Best Data Literacy Courses and Online Training for 2023
- Develop your own data literacy tools with MIT Lab’s Designing Tools and Activities for Data Literacy Learners
Some data literacy software providers can support entire upskilling initiatives in a business. Data literacy assessments can help gauge your baseline understanding of data.
Learn more about data literacy training in our guide to data literacy training.
Data literacy programs
In Talend’s 2022 Data Health Barometer, 74% of respondents were not certain that everyone at their company understands the data they work with and how that data applies to their role. It’s no wonder that 65% of companies say they’ve started a data literacy program.
If you’re just getting started, learn best practices for implementing your data literacy program in our article on building a data literacy framework.
Consider these options to support continued data literacy learning on your team:
- Gamify team learning with data literacy activities and trivia games that can earn participants badges, kudos, or other prizes
- Leverage internal expertise with skill-share sessions or mentorship matching programs
- Weave data literacy into company culture by including data literacy in onboarding sessions, lunch and learns, and internal training videos
Benefits of data literacy tools
Data literacy tools provide countless benefits across an organization:
- Build confidence in decision-makers when they trust in the data they work with
- Free up central IT resources when they stop serving as gatekeepers and focus on technical debt and bigger-picture issues
- Streamline organizational compliance when everyone shares a data culture
- Reassure stakeholders with better-communicated data, more accurate predictions, and roadmaps that stand the test of time
- Establish the real value of data by making sure data is understood and used, not just gathered and stored
Most of all, data literacy tools address costly skills gaps. According to Accenture and Qlik’s report The Full Human Impact of Data Literacy, only 21% of employees are confident in their data literacy skills. That lack of data literacy costs employers 43 hours of time per employee each year — that adds up to more than $100 billion US dollars wasted in just one year.
For individuals, an added benefit of developing data literacy skills is the ability to use data literacy skills in your everyday life. Once you start building up data competencies, you’ll want to use your skills for more than work. Good news: a lot of datasets are available to the public. Look up free datasets that you can download or access via API, and see what you can do with public datasets.
How else can you have fun with data analysis? If you’re a data novice, find simple ways to use data for fun or to make better decisions beyond work. For example, the next time you’re shopping for a big-ticket item like a new car or a vacation to New York, make a spreadsheet in Excel or Airtable to track features and prices. Practice building a data-driven business case to show which purchase is the right choice.
If you’re further along in your data literacy journey, consider using Talend Open Studio to control your Spotify playlist or building a Talend job to access and explore FitBit data.
Conclusion and further resources
By now, you’ll know that you don’t need a data science degree to become data literate. We’re living in a big data world, and there are data literacy tools around every corner. The tools you choose will depend on your particular needs.
Any software that can easily perform basic data analysis and create data visualizations is a data literacy tool. The more tools you learn, the more you grow as a data-literate citizen of a big data world.
Remember that data literacy is not a one-size-fits-all skill set. Explore a variety of data literacy training resources to individualize data literacy learning paths. You can find data literacy trainings for all kinds of learners, or design your own.
There are many data management platforms to choose from, but they’re not all good data literacy platforms. That’s because many data platforms rely on existing expertise, lack governance to enable business users, or don’t surface metadata that business users need. Industry analyses like Gartner’s Magic Quadrant can help you evaluate the best data platforms for your needs.
Ultimately, a central solution is the best way to meet your organization’s data literacy needs. Make sure it comes with training and connects to all your favorite data literacy tools. You can customize your own complete, flexible, and trusted data governance platform with Talend. To learn more, try Talend in the cloud free for 14 days.
Ready to get started with Talend?
More related articles
- Data literacy benefits: Understanding the advantages and disadvantages
- Developing and applying data literacy in business
- Mastering data literacy: Developing data literacy skills
- The ultimate guide to data literacy training
- Data literacy framework: A guide to creating an effective data literacy program
- Data literacy: What is it? And why is it important?
- Data literacy in education: Understanding the benefits, advantages, and barriers