What is Data Maturity?
Answering questions with data is not a new idea, but modern methods and techniques for answering questions with large amounts of loosely related data are certainly novel, evolving rapidly and spreading widely. Companies across the world are at different stages of experimenting with data and realizing what kinds of decisions can be made via deep analysis. Since these trials and realizations are happening at differing speeds, and often start from scratch within each organization, there are significant disparities in maturity between otherwise similar organizations. We are in a period of widespread change in the role of data professionals. Instead of being an IT-owned resource for rearward-facing reporting, data is evolving into an independent resource for making intelligent, forward-looking predictions and recommendations.
Not even five years ago, data analysts were responsible for a limited range of tasks: modeling predictable data for sales or marketing, building star schemas to enable visual-based data discovery tools, policing business logic, etc. Today, the same people are in charge of curating a single source of truth for the company, flagging abnormalities in data, applying machine learning to find patterns in data, performing exploratory data analysis to answer ad hoc questions, empowering other analysts embedded in individual business units and a lot more. Part of this new range of responsibilities is the creation of full-time data teams, staffed by a generation of highly educated data scientists, analysts and engineers.
Data as the ultimate competitive advantage
What’s behind the change? Part of the story is that compute and storage technology has improved, making powerful analytical tools available to more people without the stringent limitations of previous generations of database technology. Another part of the story is that companies are learning to compete using data, mining their datasets for insights that will move them ahead of their competitors.
Early data innovators are already proving to be dominant in their industries. Companies like AirBnb, Uber and Netflix take data so seriously that it’s more accurate to call them data companies than to consider them traditional competitors in the hospitality, transportation or entertainment industries. Using data to tune business models precisely for their markets, they are storming past the competition.
As the developer of a data platform, every day we deal with companies that are in all stages of their data journey. Some are just realizing that they need to combine all of their data sources into one place, while others are running advanced queries in Python or preparing data for predictive machine learning models. At Periscope Data, we have a unique perspective from which to observe the progress that data teams worldwide are collectively making.
Clarifying the emerging data landscape
From that bird’s eye view, we’ve been mapping the evolution of data teams and data operations. Our goal is to use these observations about the industry in general and successful data companies in specific to create a continuum of data usage that serves as both a diagnostic and prescriptive tool for future-looking businesses.
What we’ve observed is the emergence of five distinct stages along the journey to incorporate data in every decision. We call this journey “data maturity.” It’s more than a simple measure of how many full-time data professionals a company has or what tools it uses in its process. Data maturity looks at what kinds of questions a company can answer with data and what impact data is having on overall business processes. The stages are a way to organize every company along a single trajectory that measures how deeply data has infiltrated various parts of the organization.
The five stages of data maturity are a way for companies to take a look at their overall data processes, ask some difficult questions and start a discussion about how to do more with data. It can also be used as a roadmap for organizations looking to make long-term plans to develop their data team into a more powerful resource.
To learn more about the five stages of data maturity, assess which stage your company is in and find out how to advance further, download our Data Maturity Curve Guide.