Creating a data strategy has become a top priority for most leading organizations. That’s because with any major business initiative, from creating new customer experiences to building new revenue streams, leaders must be able to quickly gather insights and get to the truth.
They want to know the truth about how effective their operational processes are, what customers think about their products and services, and how they compare to competitive alternatives. To do this, they need to build a data-driven organization.
The data-driven organization
Data-driven organizations seek truth by treating data like an organizational asset, no longer the property of individual departments. They set up processes to collect and store valuable data. Their data is democratized, meaning it’s available to the right people and systems that need it. And their data is used to build new and innovative products that use data and machine learning to deliver new customer experiences.
When opened up across the organization, data can help organizations make better decisions, respond better to the unexpected, enhance the customer experience, uncover new opportunities and improve efficiency.
Data-driven organizations in action
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 machine learning 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 health care systems, clinicians, and patients. Using AWS tools, Cerner created the Cerner Machine Learning Ecosystem. It can ingest patient and hospital data, as well as making near-real-time predictions about patient care and hospital operations — such as hospital capacity and length of individual patient stay — that health care systems and clinicians can use to make more informed decisions.
Becoming a data-driven organization
There are three steps we look at in the journey to becoming a data-driven organization. The first step is for an organization to move its data and applications to the cloud. In the cloud, organizations access IT resources like storage, database, analytics and machine learning, over the internet instead of buying, owning and maintaining physical data centers and servers themselves. With the cloud, organizations can 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 step is for organizations to use these tools to liberate 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 or analyzing log data. This allows users in the organization to seamlessly discover, access and analyze all their data, regardless of where it lives, in a secure and governed way.
The third step is to innovate with that data using analytics, artificial intelligence, and machine learning. Machine learning is one of the most disruptive technologies of our generation. From predicting manufacturing issues to tailoring medical experiences, organizations are using machine learning in new and creative ways to innovate and build a competitive advantage.
Data-driven organizations 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, which 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. Its experience, ‘purpose-built’ tools and data infrastructure, and a strong partner ecosystem help AWS customers on their journey to becoming data-driven organizations, and to reinvent their businesses.
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.
To learn more about data-driven organizations on AWS, click here. In addition, you can discover how to transform your organization with machine learning here.
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