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 also include features that support data management, data protection, and data governance. Its goal is to provide an integrated platform with a single view so businesses can leverage data assets to drive business value.
Many products and services have claimed to offer a data operating system in recent years. However, a peek under the hood will reveal a patchwork of products that address different aspects of a data operating system but nothing that provides one holistic data platform. Much like the horrifying series of tangled wires attached to a power strip behind entertainment systems of the 1990s, these systems create more problems than they solve.
DataOS is a data operating system unlike anything else on the market — it's so different from other solutions that we're confident it's the world's first true data operating system. Let's look at what DataOS offers.
A Paradigm Shift in Data
We are changing the way companies interact with their data assets and technologies.
Pre-integrated and Composable
One of Modern's core pillars is "A modern data ecosystem out of the box." DataOS makes integration worries obsolete by integrating data from any source, app, tool, or service. Other solutions require a complex set of steps and checkpoints to integrate each tool separately, and many lead only to more troubleshooting as reconfigurations weaken pipelines.
Integration can be a severe problem for many piecemeal approaches because of the following:
- Heterogeneous data sources, particularly if the data sources have different data formats, structures, or protocols
- Data silos make it difficult to consolidate and integrate data from different departments or business units within an organization
- The complexity of big data environments
- Technical limitations, particularly with legacy systems
Data operating systems often overcome these challenges by providing APIs, data connectors, and other tools to facilitate integration with other systems and technologies. Additionally, organizations may adopt a data integration strategy that involves defining data standards and processes to streamline data integration across different systems and sources. However, many of these processes require manual involvement and troubleshooting efforts that aren't sustainable in the long run.
DataOS is an operational layer that simplifies the data stack. It allows all users access to the data they need for real-time decision making and prioritizes automation to ensure that the highest levels of governance make data safe and trustworthy. It does this as one out-of-the-box solution — not many different solutions pieced together — bypassing integration worries and delivering a transformed data ecosystem in a fraction of the time.
Modern Layer over Legacy Systems
Many data management systems require modernizing legacy systems by decommissioning them entirely or in part. This requirement creates complications for companies that still rely on legacy systems but feel hampered by their lack of integration.
However, many companies can't simply offload their legacy systems to fix the issue. Replacing them can become prohibitively expensive depending on how much companies must invest in new technical equipment. Legacy systems may also have too many dependencies to risk the switch. Their technical debt would be too high to replace them without creating serious further problems.
At The Modern Data Company, we wondered what would happen if we removed the pressure to replace legacy systems and instead accepted that working with them would be an inherent part of any operating system. So we designed DataOS to integrate cleanly with legacy systems, creating a modern layer that revitalizes their usefulness for the organization without ripping and replacing them.
No Data or Vendor Lock-ins
It's common for companies selling data products and services to want sole custody of their customers' data. However, this significantly restricts the customer's choices to adapt to changing business needs. Additionally, vendor lock-ins can leave companies with less control over vital data and analytical processes, making it difficult to customize or optimize solutions.
In some cases, this leaves companies extremely vulnerable. They're at risk of increased costs for premium services that they can't change. They're also at a loss if their chosen provider experiences a breach, undergoes unplanned downtime, or ceases services altogether.
We strongly believe in open-source data contracts. They provide companies with the agility required for modern operations and allow DataOS to act as a common link rather than a gatekeeper. Data contracts align with another Modern pillar: data-as-software. Companies can leverage flexible APIs, declarative primitives, and in-place automation (all within a secure, well-governed environment) to discover and transform data as necessary with no red tape or workarounds necessary.
Companies ultimately need control of their data and processes to become truly data-driven. No organization should have to rely solely on systems integrators to build their infrastructure, and no company should have to request their own data back from whatever service claims to operationalize it.
A New Era of Self-Service
Data democratization is critical to business operations. Making data accessible, understandable, and usable to a broad range of people within an organization — regardless of their technical expertise or role — leads to better decision-making and greater innovation.
Unfortunately, the complexity of an infrastructure that relies on point solutions puts prohibitive obstacles in the path of the everyday user. In this environment, governance policies are challenging to keep consistent across the board, leading to restrictions and cumbersome access requests. The technical expertise to build appropriate pipelines rests only on IT, bottlenecking business requests and taking up valuable time they could spend elsewhere. It can even lead to the dreaded "shadow IT" as business departments search for their own solutions outside the purview of IT oversight.
DataOS takes an entirely different approach. First, it uses native attribute-based access controls (ABAC) to make data available consistently and safely, regardless of source or user. Company-wide, users can quickly and easily find data available to them. Once they find the data they need, a right-to-left approach to engineering allows users to select the outcomes they want and drag and drop these components in their dashboard while DataOS builds a trustworthy, reliable pipeline behind the scenes.
Think Differently about Your Data with the Only Real Data Operating System, DataOS
DataOS does not rely on piecemeal solutions to operationalize data. Instead, it provides a single connective tissue that modernizes even legacy systems without ripping and replacing and allows access for those who need data in everyday decisions. It is the only data operating system to offer the speed and flexibility required for companies to discover real data value in just days — without the massive disruptions typical migrations cause.
To see it in action, talk to one of our data experts today.
