What are Data Silos and What Problems Do They Cause?

What are Data Silos and What Problems Do They Cause?

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by Micah James — 3 months ago in Security 4 min. read
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Is your organization having problems with data consistency? Are you getting complaints about incomplete or duplicate data?

You could have data silos bogging down business operations.

It’s a common problem not just for big organizations with multiple departments, but also small businesses that mismanage their data.

To get to the bottom of this sticky situation, you must first understand what data silos are.

What is Data Silos?

As the name suggests, a data silo is like a stockroom of data owned and managed by a single department.

That doesn’t sound so bad — until you realize that data silos are isolated from the rest of the business.

Data silos may occur whenever departments prerogatively acquire new technologies by themselves. Some companies allow this to help business units streamline their operations without involving the upper management.

As a result, the newly-adopted technology may include databases that aren’t natively compatible with existing systems.

Other than that, data silos may also form due to the following reasons:

  • Business Expansion – Rapidly growing companies assume a speedy stance when deploying new technologies to address their changing needs. This could lead to the creation of new business units and, in turn, siloed databases.
  • Decentralized Business Units – In large companies, data silos are widely common since departments are often managed independently of each other. As such, creating a more consolidated data infrastructure for the entire organization becomes a tremendous challenge.
  • Misguidance – In some cases, departments or even individuals willingly create data silos simply because they’re unaware of the implications. Rather, they’re fixated on the idea that they’re free to manage their department’s data as they see fit.

Now that you understand what data silos are, let’s talk about what it means to your business.

Also read: Best Online Courses to get highest paid in 2021

Why Data Silos Suck

Having data silos in your organization has numerous, costly consequences.

1. Inaccurate and Inconsistent Data Quality

Data silos can result in out-of-sync, inconsistent data sets between two or more departments.

This can lead to a slew of problems. Customer data may appear erroneous due to different formats, one department’s database may get outdated, and so on.

Due to the isolated nature of data silos, it’s also difficult to track and correct issues related to data quality.

2. Harder to Make Data-Driven Business Decisions

Business decision-makers need all the data they can get to function properly.

But since data silos block access to other departments, decision-makers will be forced to work with incomplete data. Unless, they’re willing to go through a more time-consuming, manual retrieval method.

3. Collaboration Problems

In the world of digital transformation, seamless data management is crucial to the success of interdependent business units.

Data silos are unnecessary roadblocks that prevent different teams from achieving optimal collaboration. Not only is access to siloed data restricted, but there’s also bound to be a lack of integration between each department’s business applications.



4. Impact on Profit Margins

Data silos can affect profit margins in different ways.

For one, it has a major impact on an organization’s operational efficiency.

Data silos can also lead to duplicate data — effectively wasting data storage space and forcing the organization to purchase more.

5. Data Security Risks

A business culture that proliferates data silos probably has poor data management and safety protocols.

Employees may be haphazardly storing data on their own through Google Sheets or some cloud storage service. Small teams may also have their own mindset and strategies when it comes to sharing their data.

This inevitably increases the likelihood of cybersecurity breaches as more potential attack vectors are introduced to the data infrastructure.

Also read: Top 10 Successful SaaS Companies Of All Times

How to Break Down Data Silos

It’s clear that data silos are detrimental to business operations — affecting not just data quality but also profit margins.

The question now is, what can businesses do about them?

Here are some of the ways businesses are uprooting data silos:

1. Data Warehouses

A data warehouse or cloud data warehouse could completely deconstruct data silos by building a central repository of consistent, accessible
data.

It works as a single data storage environment especially configured for BI (Business Intelligence) and analytics purposes.

Data warehouses are also different from data lakes, which is another form of a unified data repository.

Unlike data lakes, data warehouses have organization. Incoming data will be cleaned, transformed, and saved in a structured interface — ready to be pulled whenever needed.

On the other hand, data lakes will keep data in their raw form. This greatly reduces the costs and time needed for deployment.



2. Better Data Management Culture

An organization-wide data management reform may not directly break down existing silos, but it can prevent new ones from forming.
Remember, some departments could be keeping their data to themselves as means of boosting their performance. This incentivizes the idea of building data silos — unless departments are made well aware of the consequences of data silos.

That’s why every arm of your organization should be aboard your new data management initiative. Make it the entire organization’s job to ensure that each department is complying with data protocols.

3. Data Integration

Data integration methods, namely ETL (Extract, Transform, and Load), can help organizations deal with data silos upfront.

It works in precisely three steps: extracting data from multiple systems, cleaning data for consistency, and loading it to a target database.

ETL can be done to directly consolidate data from multiple source systems into a single business application. Other data integration methods include data virtualization, uniform access integration, and data federation.



Conclusion

Data silos can drain your organization’s productivity, IT budget, and team collaboration. And now that businesses depend on tons of data for day-to-day operations, the urgency to address data silos is greater than ever.

Remember, it all starts with a culture shift towards better, cleaner data management. Once your isolated departments adopt a more transparent approach to data, your company is ready to use data warehousing or data integration techniques to break down data silos — once and for all.

Micah James

Micah is SEO Manager of The Next Tech. When he is in office then love to his role and apart from this he loves to coffee when he gets free. He loves to play soccer and reading comics.

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