Tech Alert: Key Problems and Solutions for Business Data Silos

Experts at Aparavi address security, storage and collaboration challenges of isolated data repositories

SANTA MONICA, Calif.--()--Businesses of all sizes contend with data ‘silos’ – isolated, decentralized, and often incompatible server, storage, and cloud repositories that stymie the organization’s ability to find, protect, share and utilize its information. These data silos, if not addressed, create security risks and increase costs, say experts at Aparavi, the company behind the award-winning Aparavi Data Intelligence and Automation Platform.

Silos are common in companies where different departments use independent hardware systems and applications, each with their own files. Outdated legacy applications often operate as silos, as can stores of data in vendor-proprietary formats. Silos also result from employees using personal cloud storage drives for work files. Expansions, mergers and acquisitions typically create data silos until IT infrastructures are combined, deduplicated and streamlined.

Below are the top challenges caused by data silos, followed by Aparavi’s recommended solutions:

Unchecked growth

Data silos tend to grow, but not in their importance. Much of the data is redundant, obsolete, or trivial (ROT). ROT data, and backups of ROT data, takes up valuable space even though it is useless to the organization.

Runaway cost

Data silos increase IT costs if organizations must purchase more servers, storage, and licenses than necessary. When silos are managed separately by departments instead of a centralized IT team, it’s an inefficient use of human resources too.

Poor collaboration

It’s difficult to function as a team when participants don’t all have access to the same information. A company culture that doesn’t encourage or incentivize data sharing, and the tendency for departments and workgroups to be territorial, leads to poor decision-making.

Bad quality

Siloed information that is not universally shared and updated results in inconsistencies, inaccuracies, and integrity issues, especially as data is created, moved, copied, and versioned across different locations. This data is not usable by analytics applications, nor is it useful for most operational needs.

Security risks

Perhaps the biggest concern of all, data silos, including endpoints and personal cloud drives, leave information vulnerable to attack, loss, and leak. Ensuring security and privacy of siloed information is complex if not impossible.

Opportunities to address data silos and correct the problems are both technical and cultural. Cultural shifts include prioritizing teamwork and collaboration, (re)training employees and departments on data management policies, and engaging with team leaders to establish their distinct needs. Technical steps that should be taken include:

Find silos

Scan all systems on premise, at the edge, in the cloud, across departments, facilities, and business locations. Understand what silos exist, where, and why, so those issues can be addressed in the overall strategy.

Discover data

Then understand the data itself – how it is used and accessed, by whom, when, what it contains. Identify sensitive data such as proprietary IP or personal data that may be subject to regulatory oversight so it can be handled in accordance with various data security/privacy requirements, and protected from breaches. Identify ROT data and delete as needed.

Centralize IT

Integrate disparate platforms into a central repository or virtual data lake that crosses the boundaries of systems, protocols, and locations. There are multiple approaches and tools for this onerous task, but the result is more open and secure access for new applications, collaboration, AI/ML, and more.

Set guidelines, but stay flexible

A comprehensive cradle-to-grave data management policy is critical, including what to retain, for how long, and where. One that is flexible and dynamic can be updated as needed to accommodate changing business requirements, technologies, and other variables, so evaluate policies frequently. A good data governance strategy helps eliminate silos and prevents new ones from forming.

Automate day-to-day management

Once policies are in place, use software that automates tasks such as enforcing retention periods, copying or moving data to its appropriate repository, identifying and deleting redundant data, and moving stale data to offsite archive. This not only saves staff time, it leaves less room for error.

“When silos or islands of information are flung across an organization, that information cannot be tapped for value, insight, and business advantage,” said Adrian Knapp, CEO and founder of Aparavi. “Nearly every business, large or small, contends with data silos, but the problems compounds with time until it is nearly unmanageable. Following good data hygiene, consolidating where possible, and automating data management chores can go a long way toward addressing the issue before there’s a crisis.”

Aparavi’s data intelligence and automation platform addresses data silos by giving managers insight into data by location, owner, content/keyword, creation, last access, extension type, and dozens of other criteria. By presenting a “big picture” of data, wherever it resides, organizations can take meaningful action to safeguard sensitive files; eliminate ROT data; and automatically apply governance rules such as move to cloud/offsite storage or delete when retention periods expire, which often reduces the on-premises storage footprint by as much as 40 percent.

Aparavi empowers organizations to find and unlock the value of their data, mitigate risks, and reduce storage requirements and costs, but also transform data into a competitive asset that is more accessible for data analytics, machine learning and other tasks. To understand more about the platform, request a demo via Aparavi’s demo page.

About Aparavi

APARAVI® is the trusted disrupter in unstructured data management, helping organizations find and unlock the value of data, no matter where it lives. Aparavi is a SaaS platform with deep intelligence that rapidly discovers, automatically classifies, and optimizes highly distributed data to mitigate risk, reduce costs and exploit data value. Aparavi ensures secure access to modern data demands of analytics, machine learning, and collaboration, connecting business and IT to transform data into a competitive asset. Aparavi is a privately funded company headquartered in Santa Monica, Calif. For more information, visit, and stay informed by following Aparavi on LinkedIn and Twitter.


Mark Smith
JPR Communications


Mark Smith
JPR Communications