Building a business that is sustainable for a long period of time isn’t easy. It requires reinvention—likely multiple times over. Only 50% of businesses that were on the Fortune 500 list in 2000 are still there today. The introduction of the cloud set off a generation of reinvention, and now, the next wave of reinvention will be driven by data.
To be a leader that’s going to reinvent, you have to be maniacal, relentless, and tenacious about getting to the truth. And you have to have the tools to stay agile enough to pivot when needed and jump on new opportunities.
To do this, you need to build a modern data strategy.
The ideal data strategy isn’t one size fits all. It’s adapted for your needs. It gives you the best of both data lakes and purpose-built data stores. It lets you store any amount of data you need at a low cost, and in open, standards-based data formats. It isn’t restricted by data silos, and lets you empower people to run analytics or machine learning using their preferred tool or technique. And, it lets you securely manage who has access to the data.
Businesses who are reinventing with data
A great example of a data-driven organization is The BMW Group. When it needed to innovate faster to keep up with consumer demands while also providing employees with more data to make decisions, BMW migrated from an on-premises data lake to its Cloud Data Hub on Amazon Web Services (AWS). The Cloud Data Hub processes terabytes of telemetry data from millions of vehicles daily and makes it easily accessible to internal teams. With its Cloud Data Hub, BMW employees can gain insights from several petabytes of data coming from BMW vehicles around the world. For example, they can monitor vehicle errors to identify potential issues across vehicle lines or apply ML to better forecast the demand for its range of vehicle models and equipment options.
Another data-driven organization is Cerner, a health information technology company providing solutions designed to empower healthcare systems, clinicians, and patients. Using AWS tools, Cerner created the Cerner Machine Learning Ecosystem. It can ingest patient and hospital data and make near-real-time predictions about patient care and hospital operations—such as hospital capacity and length of individual patient stay—that healthcare systems and clinicians can use to make more informed decisions.
Adopting a modern data strategy
There are three stages in the journey to adopting a modern data strategy. The first stage is for an organization to move its data and applications to the cloud. Migrating storage, database, analytics, ML, and other IT resources to the cloud enables organizations to scale up or down at the click of a button, only pay for what they use (at a price virtually lower than any organization could achieve on its own), and have access to more data tools than anywhere else.
The second stage is for organizations to use these tools to unify their data by breaking down data silos and making it more accessible to everyone who needs it. In the cloud, organizations can move their data between a centralized repository, often called a “data lake,” and specialized data stores and analytics tools that are purpose-built to provide the best cost and performance for specific types of analytics, like data warehousing, big data processing, real-time analytics or log analytics.
Adopting purpose-built solutions means you use a service optimized for that workload. The result is you don’t have to compromise on functionality, performance, scale, or cost. For example, Amazon Redshift is 3x faster and at least 50% less expensive than other cloud data warehouses. By unifying the best of both data lakes and purpose-built data stores, users in the organization can seamlessly discover, access, and analyze all their data, regardless of where it lives, in a secure and governed way.
The third stage is to innovate with that data using analytics, artificial intelligence, and ML. ML is one of the most disruptive technologies of our generation. From predicting manufacturing issues to tailoring medical experiences, organizations are using ML in new and creative ways to innovate and build a competitive advantage.
Organizations that adopt a modern data strategy understand that data is the foundation for innovation and transformation. And that in order to reinvent themselves, they need to be able to quickly get to the truth. This requires a data-driven culture that embraces the use of data in decision-making from the top down, and an investment in the right data infrastructure, solutions, and tools.
Today, hundreds of thousands of organizations use AWS to get value from their data. Our experience, “purpose-built” tools and data infrastructure, and strong partner ecosystem help our customers on their journey to becoming data-driven organizations and reinventing their businesses.
Learn more about data-driven organizations on AWS.