What is an Analytics Translator?
The Analytics Translator is an important member of the new analytical team. As organizations encourage data democratization and implement Self-Serve Business Intelligence and Advanced Analytics, business users can leverage Machine Learning, Self-Serve Data Preparation, and Predictive Analytics for business users to gather, prepare an analyze data. The emerging role of Analytics Translator adds resources to a team that includes IT, Data Scientists, Data Architects and others.
Analytics Translators do not have to be analytical specialists or trained professionals. With the right tools, they can easily translate data and analysis without the skills of a highly trained data pro.
What’s a Data Translator—And Why Do You Need One?
A report from McKinsey shows that by 2026, the demand for data translators will be 2 to 4 million. Clearly, there’s something to it. In fact, companies are creating their own academies to train data translators because there just isn’t enough talent to match the demand. That’s because data translators / analytics translators do more than read numbers. They create a winning strategy behind them.
For instance, in the past, I’ve shared that when starting with analytics, it’s important to start small. Too much data can overwhelm everyone and quickly turns into a pile of nothing useful. When starting out, companies should figure out what their goals are, what they need to find out, and what they plan to with that information when they do. In the past, this role was sometimes left to marketing—sometimes to IT. But the data translator becomes the bridge that brings those silos together.
What Do They Do … Exactly?
In short, they’re strategists. Data or analytics translators are all about structured problem-solving. They’re creative enough to imagine new possibilities for your company, but also technical enough to explain those goals to the data team. They look at the data presented and think—what if? What if we looked at it a different way? Does this data support our current business strategy? What product or update should we be making to maximize the future of our company? And they’re equally comfortable asking these questions in the data den or the C-Suite.
The Ideal Analytics Translator
When identifying possible candidates to perform the Analytics Translator role, the organization should look for skills that can be nurtured and optimized as an asset.
- A power user of Self-Serve BI tools
- Recognized as an expert in a functional, organizational role
- Comfortable with building and presenting reports and use cases
- Works well with technical and management teams
- Manages projects, milestones and dependencies with ease
- Able to translate analysis and conclusions into actionable recommendations
- Comfortable with metrics, measurements and prioritization
- Acts as a role model for user and team member adoption of new processes and data-driven decisions
If this role is recognized as important to the organization, most enterprises will structure a logical program to identify and train candidates to ensure uniform skills and performance.
By combining domain, organizational and industry skills with Self-Serve Analytical tools, the Analytics Translator can help the enterprise to achieve low total cost of ownership (TCO) and rapid return on investment (ROI) for its Business Intelligence and Advanced Analytics initiatives and can encourage and nurture data democratization and optimal analytical business results within the organization.