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14. July 2022

The Data Silo Problem

As if dealing with the massive amounts of data wasn’t enough, particularly unstructured data, organizations also must contend with the data silo problem.

As if dealing with the massive amounts of data wasn’t enough, particularly unstructured data, organizations also must contend with the data silo problem. There are ways to alleviate the many downsides of data silos, and the Aparavi Platform provides several features that can help.But first it’s important to understand what data silos are, how they occur and why it’s critical to break them down.

What Is a Data Silo and Why It's a Problem

A data silo is a collection of data that's created and/or controlled by a single department or business unit ─ or sometimes a few of them ─ but isolated from the rest of an organization. The problem? Others within the organization that could benefit from that siloed data don’t know it exists. And that’s only one of the many issues.

How and Why Data Silos Occur

Data silos can develop due to lack of organizational oversight, business growth, mergers, and acquisitions. However, they most often result when departments and business units are decentralized and managed as separate entities.

Without an organization-wide system for data management, the various departments and business units each tend to collect, store, and control their own data without sharing it or even making its existence known. While this is more common among larger companies, small- and medium-sized businesses aren’t immune.

It doesn’t help that these various entities often use different technologies ─ lots of them, each which may generate its’ own data. According to Statista, organizations worldwide were using an average of 110 software as a service(SaaS) applications in 2021.

These technologies don’t always integrate with one another, especially if they’re legacy applications, making information sharing difficult. And the entities using them don’t automatically think about sharing their data with others, particularly those that could benefit from it.

For example, the sales department might useNetSuite as their CRM system. The information it generates could be extremely useful to the marketing department. But if the marketing team isn’t also usingNetSuite or the sales department isn’t actively sharing their data, the marketing staff not only misses out on it. They’re likely to gather their own comparable data, duplicating efforts and incurring unnecessary costs for both data collection and storage.

Shadow IT contributes to the data silo problem as well ─ and to security risks. If IT doesn’t have visibility into or control of corporate data stored on unauthorized cloud-based applications ─particularly sensitive or proprietary data, that data isn’t secure.

Company culture also gets the blame for data silos, specifically company cultures in which data sharing isn’t encouraged or incentivized. The bigger culprit, however, may be the tendency for departments to be territorial. They view their data as an asset that they own and control, and aren’t willing to share it.

The Biggest Issues Caused by Data Silos

As already noted, having to gather and store the same information as another department is costly and a waste of time and resources. As all this data gets backed up ─ and backup is important, the data silos continue to grow. So do the issues and associated costs. Among them:

Redundant, Obsolete, or Trivial (ROT) Data

Data silos tend to grow unchecked. There often aren’t any guidelines regarding what to retain or for how long. Much of the data could be duplicates, flawed or useless. It gets continually backed up, taking up valuable storage space and eating up budgets.

Data Quality

While more than one entity might gather and store the same data, they may not all update or correct it. That prevents the establishment of a single“source of truth.” Plus, the inconsistencies can cause data accuracy and integrity issues that negatively affect end users in both operational and analytics applications.

Incomplete Data Sets

Because data silos can prevent users from having access to all available data, their decision-making may be based on incomplete or inaccurate information.

Costly Data Storage

Even when data can be collected from various data silos, it’s often been stored in inconsistent formats. A lot of time-consuming cleanup work has to be done before useful insights can be generated.

Duplicate Data Platforms and Processes

Data silos can increase IT costs by requiring organizations to purchase and maintain more servers and storage devices than necessary. Those systems may also be deployed and managed separately by departments instead of a centralizedIT team, further causing the inefficient use of IT resources.

Less Collaboration Between Departments

Data silos reduce the opportunities for information sharing and working together between users in different departments. It's difficult to collaborate when everyone doesn’t have visibility into siloed data.

Data Security and Compliance

This is a big one. The “unknown” aspect of the existence of data silos, what they contain, and where their data is stored can complicate organizations’ efforts to defend against, mitigate or remedy data security and privacy risks. You can’t protect what you don’t know you have or where it resides.

Because there may not be guidelines or checks on the data stored, data silos could easily contain sensitive data. Not surprisingly, data siloes put organizations at greater risk of data breaches. They also make it difficult comply with data privacy and protection laws, and to adhere to data retention policies.

How to Eliminate Data Silos

It’s not easy to eliminate data silos, but it is possible. The following are among the suggestions that most data management experts recommend.

Change the Culture

Create an organization-wide culture that views data as an enterprise asset. Promote the business benefits of data quality, data sharing and establishing a single source of truth, as well as how they ultimately benefit employees ─ i.e., making their jobs easier.

Use change management to implement the necessary changes and help ensure that departments and business units adopt them. Incentivize and reward adoption of good data management practices. Integrate data management best practices into employee onboarding and training. Importantly, make strong data management and data governance part of your organization’s strategic objectives.

Data silos won’t immediately go away, but you’ll see more efforts to dismantle them.

Create a Comprehensive Data Management Strategy

Develop an organization-wide framework for handling all aspects of data, from data generation and storage to data distribution and disposal. Make sure it’s easy to communicate, understand and administer.

It should assign responsibility for creating, implementing and enforcing policies and procedures; define policies for gathering, storing, sharing, distributing and processing data; outline processes for naming and storing data; establish protocols for keeping data clean, accurate and usable; and cover all aspects of data lifecycle management.

Determine if the strategy should be centralized, with one group determining the rules for handling data, or federated, whereby several groups have authority over data. (This works well in organizations in which departments and business units have different data needs.)

Rather than relying on the passive, compliance-oriented frameworks used in the past, develop one that is agile, flexible and dynamic. Include proactive risk management. Make sure it encourages rather than stifles innovation. Revisit and evaluate it frequently, and make updates as needed to account for changing business requirements, technologies, and other variables.

A strong data management and governance strategy not only helps bring down data silos. It will help prevent new ones from forming.

Centralize Technology Infrastructure

Whenever possible, invest in technologies that integrate siloed data from various platforms into a central repository. Don’t just leave the decision making to IT. Involve all potential user groups. Query and evaluate their needs. Bring in outside consultants if necessary that can offer a broader, more objective perspective on what’s needed and offer solution options.

Prioritize Data Integration

One of the best ways to break down data silos is by integrating them with other systems. Common data integration techniques include hand coding, data warehousing, middleware data integration, data consolidation, data virtualization, data federation, and data propagation.

Numerous tools and technologies are available to help with those techniques. You can also take advantage of Integration Platforms as a Service (iPaaS) solutions. Delivered asa service for a fee, IPaaS standardizes how applications are integrated into an organization, making it easier to automate business processes and share data across applications.

Standardize Processes

It’s easy for data silos to form when different departments or business units use different tools and technologies ─ especially for similar processes and workflows. Get a better understanding of how work is done throughout the organization and look for ways to standardize and consolidate.

Learn how data is being generated, processed, stored and managed in general across the organization, as well as what tools and technologies are being used. Get input from all user groups. Consider installing monitoring software to help.Communicate what you’re doing to all users so they don’t see the monitoring exercise as a means of checking on or measuring their performance. The idea is to identify ways to standardize processes to help eliminate the need for so many different tools and technologies. The exercise may also help uncover instances of shadow IT.

How to Approach Data Silos

Aparavi offers a few additional, very important features that not only make dismantling data silos even easier. They also help mitigate security risks, lower storage costs, and contribute to better data quality.

Find Data Silos

One of the problems with data silos is that you may not know they exist, at least not all of them. The Aparavi Platform takes care of the issue. It enables you to scan across all systems on premises, at the edge and in the cloud, and across multiple departments, facilities and geographies to locate your data, including unstructured data.

The scan results will provide information about your data by location, owner, creation data, last access data, extension type, and modification date, all presented on the platform’s easy-to-use dashboard. You can use this information to further assess how the data is being used, by who and for what purposes. Knowing who the data owners are also makes it easier to learn more about your organization’s data.

Eliminate ROT Data

As noted earlier, data silos often contain a lot of duplicate data. The Aparavi Platform enables you specifically search for and delete redundant data, wherever it exists. You can also use the creation date, last access date and modification date generated by your scan results to identify obsolete data that can be removed.

In addition, the Platform allows you to define custom tags that can be applied to help identify and clean up ROT data.It also offers a data actions feature that allows you to delete (individually or in a batch) specific files, or move them to a location where they can undergo data cleaning as needed.

Side benefit to eliminating ROT data:it helps generate better quality data, speeds up data analysis, and lowers the cost for data analysis.

Locate Sensitive Data

The Aparavi Platform includes an extensive collection of classification policies that can be used to identify specific types of data that fall under the sensitive, proprietary and/or PII categories. Among them:bank account number policies, specific regulatory compliance policies, SWIFT codes policies and others.

Finding sensitive data, even when it’s in data silos, enables you to take action to protect it ─ helping to avoid data breaches and comply with various data security and privacy requirements.

Know Your Data

One of the biggest benefits the Aparavi Platform offers is that it enables you to know your data – where it is, what it contains, who’s using it and more. That knowledge is helpful on numerous levels.

First, it empowers you with the insights and information to take appropriate actions for moving and/or centralizing data. As already noted, it helps you locate and protect sensitive data. And it enables you to lower overall storage costs by identifying ROT data.

In addition, the more you know about your data, the better you’re able to implement the other recommendations for eliminating data silos. For example, creating a data management and governance strategy requires knowing as much about data across your organization as possible. The same goes for making changes to company culture.

Integration and Standardization

The Aparavi Platform includes an API that enables you to integrate your existing applications with the platform.That means you can teach your programs to use Aparavi to organize the data, and provide seamless integration across your organization.

The platform also helps you standardize file management by creating rules for your files. For example, you require employees save all files on cloud storage, rather than on local machines. You can also limit access to sensitive information simply by tagging a file and letting the system do the rest.

Eliminate Data Silos With Aparavi

The Aparavi Platform not only helps take down data silos. It makes overall data management and governance easier. The best way to learn what the platform can do is to see it in action. Schedule a no fee, no commitment, no obligation demo today.