
How to drive trusted decisions without changing your current data infrastructure.
Learn more about DataOS® in our white paper.
I have the great pleasure of handling marketing strategy for The Modern Data Company. We recently refreshed our brand, which includes a completely revamped website and marketing materials.
Branding is a labor of love. I work for one of the most exciting companies in the world right now. Modern has a data operating system unlike anything else on the market — one that reimagines how companies approach their data and how data companies deliver results. One of the biggest challenges, when you’re working with something unprecedented, is telling its story correctly.
Telling the right story was the catalyst for the change, and I think we’ve nailed it.
Modern built the very first data operating system, but in the beginning, we didn’t know what exactly to call it. We knew it changed how non-tech users approached data-driven decision-making. We knew we’d ruffle some feathers by making dependence on ELTs and ETLs optional. We knew most companies needed a better governance solution before they could even think about unlocking their data from rigid silos. We just didn’t have a term for it.
So, we settled on “data fabric” because that seemed to be something our customers and the industry could hold onto while we asked them to change everything that they thought they knew about data management. Our branding at the time reflected this exploration.
When everyone in the industry was using “tech blue” to build their websites, we chose a bright, bold color palette to distinguish ourselves. We chose to represent key pieces of Modern’s mission using animation-style images. We even incorporated a fabric pattern into our logo. It worked well at the time, and we gained traction with some wonderfully forward-thinking companies who were ready to untangle their data.
The story wasn’t quite the right fit, however. First, we outgrew the label “data fabric.” Companies can still get a data fabric through Modern’s DataOS, but it’s only one of many configurations DataOS can enable. We also outgrew the look and feel of our website. It was too limited and didn’t contain all the resources and initiatives needed to encompass the full potential of DataOS.
We needed to tell the real story. Our refreshed brand features a grown-up, expanded color palette, images that harken back to the expansive possibilities of DataOS, and more resources for companies looking to find exactly what Modern’s data operating system can do for them. We’ve even overhauled our logo –– it uses composable pieces to create the “M” in “Modern,” paying homage to the truly composable capabilities of DataOS.
When everyone else was thinking up new storage solutions for customers to upload their data, we decided that customers don’t need to move their data at all. When everyone else was thinking of ways to justify the disruption that companies face when adopting a new data solution, we decided to integrate with the systems customers already have. When everyone else charged ahead to take control of a customer’s data for them, we put control back in the customer’s hands.
Our new look reflects exactly how much we value flexibility and thinking outside the data box. DataOS is a striking, boundary-pushing concept that puts companies back in control of their data, and we hope that our brand encourages you to think about data in new and revolutionary ways.
And speaking of stories, let us know if there’s a story we still haven’t covered from your industry or your situation. DataOS and Modern can solve nearly any data challenge in nearly any industry, and we’d love to prove it to you. Also, let us know what you think about our new look. This is the Modern story, but guess what? It can also be your new data story.
Be the first to know about the latest insights from Modern.
In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions, we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Remember to read part one if you need a quick refresher. ...
Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. Each has unique advantages and drawbacks, and the right...
What is a data operating system? On the surface, it's an operating system designed specifically for managing and processing large amounts of data. It typically provides a scalable and flexible infrastructure for storing, processing, and analyzing big data and should...
Prevention and early intervention are essential to building an effective healthcare approach that supports patients from start to finish. The critical component of this approach is predictive analytics — analyzing big data gathered from patients, consumers, and...
Technical debt is something that many companies are aware of and are attempting to address. It is a big enough issue that several of our recent blog posts (Lessons in Technical Debt from Southwest Airlines, Start Paying Down Your Technical Debt Today, and A Better Way...
Data Mesh + Patient360: A Modern Revolution for Healthcare DataHealthcare organizations are sitting on a treasure trove of customer data. Operationalizing that data makes it actionable and usable, helping improve services, costs, and patient outcomes. However,...
The Modern Data Company BriefThe Modern Data Company is radically simplifying data architecture with its paradigm-shifting data operating system, DataOS. We're replacing overwhelm with composability, reinventing governance, and connecting legacy systems to your newest...
DataOS® – The Fastest Path from Data to DecisionDataOS is the world's first fully-integrated data operating system designed to move from companies from data to decision in weeks instead of months. Discover what makes DataOS different from the competition and how...
Not Getting Value from Your Data Transformation? Fix itImplementing customer lifetime value as a mission-critical KPI has many challenges. Companies need consistent, high-quality data and a straightforward way to measure CLV. In the past, organizations have struggled...
DataOS® Solution:AI/ML 70% of AI initiatives fail and teams spend the vast majority of their time simply prepping data for platforms, leaving very little left over for gaining insights and driving business value. But an AI/ML platform powered by DataOS can achieve...