Mass data fragmentation is the large and increasing proliferation of data across a myriad of different locations, infrastructure silos, and management systems. This not-used-everyday data is typically low-latency yet it makes up the vast majority of an organization’s data and often has to be held for certain periods of time to meet industry or government mandates. This data is typically contained in data management backups, archives, file shares, object stores, test and development systems, and analytics systems.
Why is Mass Data Fragmentation Important?
As every industry undergoes digital transformation, data has become an enterprise’s most valuable digital resource—a competitive asset. Yet mass data fragmentation has turned it into a costly and risky IT headache for many organizations. Teams that haven’t solved mass data fragmentation can’t use all of their structured and unstructured data to maximum advantage because of its wide proliferation across locations and systems on-premises and in the cloud. Solving mass data fragmentation is a key objective for organizations that want to uncover insights and fully use all of the value of their data for competitive edge. Teams that want to accelerate digital transformation by moving away from legacy infrastructure to hybrid or multiple cloud environments for maximum agility.
What is Data Fragmentation?
Fragmented data is data that is spread across on-premises and multiple cloud environments in different systems and places. Data fragmentation makes it hard for organizations to fully use all of their data value to their advantage.
What is Mass Data?
Mass data is large and increasing amounts of structured and unstructured data stored digitally.
What Causes Fragmentation?
The cause of data fragmentation is often unintentional. Organizations adopt new products or approaches such as multiple clouds and all of a sudden they are now storing data across multiple environments, locations, silos, clouds, and management systems. Organizations that rely on a single multicloud data management platform avoid the causes of mass data fragmentation.
Why Mass Data Fragmentation Matters?
Mass data fragmentation has serious business consequences. At the top of the list: It impedes digital transformation. When data is fragmented across systems, locations, and silos, organizations cannot use it to maximum business advantage without expending more resources, including time, people, and budget.
Why is Mass Data Fragmentation a Major Business Threat?
In a recent survey by Vanson Bourne, on average, IT leader respondents said that mass data fragmentation cost them:
More time – IT teams spend 19 weeks a year managing data and apps infrastructure across public cloud environments
More people – IT teams would need to expand by over a third to glean maximum insights from all the data they store across public clouds
More money – IT budgets would need to increase by nearly half
Why Data Silos Have Become Management Challenges?
Data silos and legacy infrastructure present significant business and IT management challenges, costing teams time, money, and budget to try to gain value from the data they capture and store.
Data silos cause data inefficiency and data to be dark. Because there is no data sharing between functions, organizations can’t optimize capacity. This results in generations of multiple data copies that take up unnecessary capacity, or storage space, which requires more time and energy on the IT side to manage. Data silos compromise operational efficiency, too, because IT staff has to manage and coordinate multiple proprietary systems and UIs, each requiring a specialist, rather than IT generalist, to understand it.
Fragmented data is also often referred to as dark or hidden data. That’s because when there’s no single view into it from a modern data management or data protection solution, IT doesn’t know where all of its data is located, let alone what that data is—structured and unstructured, objects and files, and more. This can make siloed data not only an operational nightmare because there’s no optimization but a potentially serious compliance or security risk.
Cohesity and Mass Data Fragmentation
Three key factors contribute to mass data fragmentation:
Multiple point products managing fragmented data silos and legacy infrastructure, adding complexity
Lack of integration of point products across core, multiple cloud, and edge locations, adding risk
Data copies, adding costs and compliance challenges
Cohesity solves mass data fragmentation with multicloud data management and data protection that converges backup and recovery, file and object services, disaster recovery, development and testing environments, and analytics on a single platform.
With Cohesity, organizations achieve business goals fast by:
Removing point products for data management and data protection, reducing complexity
Seamlessly integrating existing solutions (e.g., VMware, Microsoft, Pure, etc.) and providing native cloud integration (e.g., AWS, Azure, and Google Cloud)
Eliminating data copies, reducing costs and streamlining compliance
Cohesity’s approach removes silos while radically simplifying infrastructure or powering data management and data protection capabilities as SaaS. With Cohesity, organizations dramatically improve CapEx and OpEx and use all of their data for competitive advantage.