How to Combat Data Silos
Here are common issues with data silos and how to get rid of them.
Technical, organizational, or cultural roots can all be found in data silos. Large corporations frequently experience these organically since many business divisions may run independently and have their objectives, top priorities, and IT budgets. In the article, Adrian Knapp, CEO & founder of Aparavi, discusses the issue with data silos and how they are problematic.
If a company doesn’t have a solid data management strategy, it may wind up with data silos. Organizations must deal with the data silo issue and manage vast amounts of data, especially unstructured data. Intelligent data management platforms can help with the numerous drawbacks of data silos. But first, it’s crucial to understand what data silos are, how they develop, and why eliminating them is necessary.
What is a Data Silo anyway? A data silo is a group of data isolated from the rest of an organization by a single department or business unit or occasionally by a few of them.
Why is a Data Silo Problematic? The issue? The compartmentalized data is unknown to those within the organization who are unaware they could benefit from it.
Why and How do Data Silos Develop?
Data silos can form due to poor organizational control, company expansion, mergers, and acquisitions. However, they frequently happen due to the decentralized management of company units and departments.
Departments and business units tend to each gather, store, and handle their data without sharing it or even letting anybody know that it exists without an organization-wide system for data management. This occurs more frequently in larger corporations, but that does not mean that small and medium-sized enterprises are exempt.
Information exchange is challenging because these technologies don’t always work well together, especially if they’re legacy apps. Additionally, the organizations that use them don’t always consider sharing their data with others, especially those who benefit from it.
For example, the sales team might choose NetSuite as their CRM platform because the marketing department might find a great use for the data it produces. However, if the marketing staff does not use NetSuite or the sales team does not share their data, they will not just miss out–they will probably acquire similar data on their own, duplicating efforts and adding extra expenses for data collection and storage.
Shadow IT increases security issues as well as the problem of data silos. That data isn’t secure if IT doesn’t have access or control over sensitive or confidential corporate data kept on unapproved cloud-based applications.
Data silos are sometimes attributed to organizational cultures, particularly those where data exchange is not valued or encouraged. The inclination for departments to be territorial, though, might be the bigger offender. They don’t want to share their data because they see it as a valuable resource that they possess.
See More: 5 Ways to Eliminate Customer Data Silos
More Problems Resulting from Data Silos
As was previously mentioned, it is expensive and a waste of time and resources to collect and keep the same information as another department. The data silos keep expanding as all of this data is backed up.
Data that is redundant, obsolete, or trivial (ROT)
Data silos frequently expand, and they are unchecked. There are often no rules dictating what should be kept or for how long. There may be many duplicates, errors, or meaningless pieces of data. It constantly backs up, using important storage space and draining resources.
Data integrity
The same data may be collected and stored by multiple entities, but it may not constantly be updated or corrected by all of them. This makes it impossible to establish a single “source of truth.” Additionally, inconsistent data can lead to data correctness and integrity problems that harm end users in both operational and analytical applications.
Incomplete sets of data
Users may make decisions based on inadequate or erroneous information due to data silos that can prohibit them from accessing all accessible data.
Slow and expensive data analysis
Even when data from different data silos can be gathered, it is frequently stored in inconsistent formats. Before valuable insights can be produced, a lot of labor-intensive cleanup work must be completed.
Duplicate platforms and procedures for data
By requiring businesses to buy and operate more servers and storage devices than necessary, data silos can raise IT expenditures. Additionally, departments rather than a centralized IT team may implement and administer those systems independently, thus resulting in inefficient use of IT resources.
Enduser cooperation is lessening
Data silos limit the potential for users in many departments to collaborate and share information. When compartmentalized data is unavailable to everyone, collaboration is challenging.
Data protection and adherence
This one is significant. Organizations may find it challenging to protect against, reduce, or otherwise address data security and privacy issues because of the “unknown” nature of data silos, what they contain, and where their data is housed. It cannot be protected when you don’t know what you have or where it is located.
Data silos may easily contain sensitive data since there may not be any rules or checks on the data stored. Unsurprisingly, data silos increase the likelihood of data breaches in enterprises. They also make it challenging to follow data retention regulations and comply with data privacy and protection laws.
See More: Data Management Easier as AWS Opens Lake Formation Service
Getting Rid of Data Silos
Eliminating data silos is not simple, but it is doable. Create a culture of data ownership across the entire organization. Encourage the use of a single source of truth, high-quality data exchange, and other business practices that will help employees by making their jobs easier.
Implement the essential adjustments and aid in their adoption by departments and business divisions using change management. Encourage and honor the implementation of sound data management strategies. Create a system that will be used throughout the entire organization to manage data, from its creation and storage through its distribution and disposal. Make sure it’s simple to communicate with, comprehend, and use.
Data silos can be eliminated with the help of a solid data management and governance plan. Integrating data silos with other systems is one of the most excellent methods to destroy them. Data warehousing, middleware data integration, data consolidation, data virtualization, data federation, and data propagation are common data integration strategies.
The answer is to make your data more transparent by spotting redundant, obsolete, and trivial data. Technologies available can help shed light so that your business may regain control of your data through intelligent data management platforms that support the deletion of ROT data. These sophisticated tools assist in analyzing unstructured data and suggest what should be retained, removed, or sorted. The best thing you can do to eliminate data silos and overall data health is to take ownership of your data.
Which best practices have you considered to get rid of data silos? Share with us on Facebook, Twitter, and LinkedIn. We’d love to know!
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