5 min read
Part of my job is to learn from the many CxOs in our customer base and to understand more about their current and future data challenges. Based on all those discussions, a common picture started to emerge over time with the core challenge being where best to invest in order to leverage modern tools and technologies.
Organizations want to maintain their status-quo and combine legacy and new technologies. They also want data to be made available to everyone in a secure, easy-to-use fashion. Essentially organizations need to do more with less. One of our customers explains the challenges faced by many organizations today:
"Data is stored on all layers in the stack, and there is no way to manage data as one digital asset independent of workloads, infrastructure, or applications"
- CIO Global Logistics Company
The classic IT landscape consists of three different foundational layers:
Even today these fundamental concepts haven’t changed, but the construct of these functional layers has.
Applications have evolved over time from being monolithic to multi-tier to today’s connected network of distributed services weaved together through microservices.
Middleware has evolved from being purely a runtime layer for applications to being a layer for computational frameworks, orchestration engines, and modern database technologies.
Hardware has shifted from being physical to virtual to delivered as a resource through a cloud-consumption model.
None of those evolutionary steps considered data as a first-class enterprise citizen. As a result, organizations are faced with the challenge of data still being stored across all layers without a universal way to manage and access it. Everystep of abstraction in each of those foundational layers significantly increased data silos and complexity. This made data management difficult because data was not explicitly decoupled from its dependencies.
MapR has reimagined the foundational layers and introduced a new layer in the stack called dataware. Dataware explicitly decouples data from the modern constructs of applications, middleware, and hardware. As a result, organizations get end-to-end control over data security, data placement, data access, data tenancy, and data controls completely independent from any other layer in the enterprise IT stack.
Dataware solves the challenges of managing the complexity of today’s data environments by letting you consistently manage data and its ecosystem across multiple clouds and containerized infrastructures. As a result, you can focus more on how you leverage the data instead of being distracted by the management of multiple data technologies needed to support distributed applications and analytics across locations.
Dataware is a critical layer within the enterprise IT stack for three key reasons:
Dataware optimizes the entire data lifecycle – from ingestion to processing – to enable applications that simultaneously require real-time analytics, machine learning, and AI. Dataware gives complete flexibility in leveraging the underlying infrastructure (on-premises, cloud, or containerized infrastructure) and deployment patterns (hybrid or multi-cloud).
MapR gives you the power of dataware as both a functional layer and an operational platform. The MapR Data Platform provides you with the ability to manage data as a resource independent of any other framework, tool, or infrastructure service.
The MapR Data Platform helps organizations realize the significant business benefits of dataware in the following ways:
If you want to learn more about how the revolutionary concept of dataware delivered through the MapR Data Platform can help your organization become data-first, please email us at firstname.lastname@example.org.
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