
How to drive trusted decisions without changing your current data infrastructure.
Learn more about DataOS® in our white paper.
A couple of years ago, we started working with a fortune 100 retail company in the US. They had invested 100’s of millions of dollars towards data management with no measurable ROI. Basic questions like “how many customers do I have?” were not answered accurately; marketing and personalization was being driven by low quality data that was a week old; frustrated marketing teams created their own shadow solutions to address their team’s needs.
If this sounds familiar to you, you are not alone. 80% of data modernization initiatives failed to deliver positive ROI for companies which in some cases have invested over $500M to solve this problem (McKinsey). Data today is HARD. The biggest reason for this is complexity:
The end result: years spent addressing symptoms of data complexity instead of the disease.
To quote the American anthropologist Joseph A. Tainter, “…in the evolution of a society, continued investment in complexity as a problem-solving strategy yields a declining marginal return”. This applies to data just as it applies to society in general.
We founded The Modern Data Company because we believe that data
Data is a 30% tech problem and 70% people problem. A successful data company can’t be built without immense empathy towards the customer and the people issues within customer organizations. Modern Data is a value-driven company with empathy as a core attribute. These values are what will enable us to deliver consistent value and satisfied customers.
Contact us to find out how Modern’s DataOS—the world’s first operating system—can transform the way you handle your data.
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...