How to Solve Common Data Silos Problems
Managing data has become a top priority for modern businesses. With multiple channels of customer interaction and a wealth of internal data, collecting that data and putting it to work can be a challenge. If you don’t plan ahead, data can end up siloed and useless to your company.
What are Data Silos?
A data silo is a group of data that is cut off from the rest of your technology ecosystem. It could be data from a third-party tool that only one department has access to. Or it could be customer data you collect at the point of sale that doesn’t get fed back into your systems.
Wherever it comes from, a data silo can slow down your analytics and cause gaps in your overall view of your business data. Let’s take a look at the main reasons you might end up with siloed data.
What Causes Data Silos?
Most data silos happen due to a lack of forward planning. No one intends to create a store of unusable data, but as departments grow, they implement their own methods for collecting and storing information. If there’s no centralized plan for data, these silos can occur by themselves.
This is often a problem for established businesses with legacy systems. Organizations have moved towards cloud systems for data storage and integrated microservices. Older systems like SAP APIs and their complex integration methods can be a roadblock to this modernization.
If one department gets left behind due to a reliance on legacy tools and systems, then data silos will happen.
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Segregated Organizational Structure
Data silos also occur when departments fail to communicate their data strategies. Having an overly-segmented organizational structure will make this problem worse. Think of it like this, if sales and customer service never shared customer details, how much data would be wasted?
Communication & Company Culture Issues
It’s not just the structure of your business that can affect how data flows through it. Your company culture can change how your departments see collaboration on a day-to-day and business-wide level. Make data accessibility and collaboration a priority.
Why are Data Silos a Problem?
If you know how much modern organizations rely on accurate data, then you can probably already see why data silos are an issue. Just in case, here are the four main reasons you should avoid data silos.
1. Slows Down Collaboration
If data is hard to access, then it’s hard to share. If departments and managers can’t share insights, they can’t collaborate effectively. As information moves up the chain toward the executive level, this makes it increasingly difficult to get a full overview of your business data.
2. Incomplete Datasets
Analytics, especially the kind advanced by new big data technology, rely on complete datasets to be effective. Having parts of your business data end up in inaccessible silos will inevitably lead to incomplete data when you need it for your machine learning pipelines or analytics.
3. Wasted Resources
Inefficient methods of data storage and access can be a large hidden cost. If multiple employees are creating redundant copies of data, for example, then you’re wasting storage space and maybe making unnecessary draw-calls. This can snowball into high costs over time.
4. Limited Company Overview
For decision-makers, having a 360-degree view of your business is essential. It’s the only way you can effectively allocate resources between departments and projects. Any data silos you have are creating a potential blind spot in this overview.
How Do You Overcome Data Silos?
Nobody wants data silos, but they do happen. So, how do you avoid them? These three methods can help you plan ahead and avoid siloed data down the line.
Centralized Data Collection
Accessible cloud storage systems like data lakes have made centralized data management possible even for smaller businesses. Transitioning existing services to the cloud can be a challenge, but the rewards from data utilization and easy integrations are worth the risk.
When you invest in business software, integration should be high on your priority list. Whether your doc control system or a third-party CRM platform, make sure that any systems you implement can communicate with your data center.
Improve Training & Internal Communications
Make collaboration and data sharing a part of your business culture. If your department heads all understand the need for interconnected data systems, then data silos are much easier to avoid.
Final Thoughts: Avoid Data Silos at all Costs
Data silos can be easily avoided with good data management. You just need to look ahead and put data sharing and accessibility at the top of your agenda.
About the Writer
Pohan Lin is the Senior Web Marketing and Localizations Manager at Databricks, a global Data and AI provider connecting the features of data warehouses and data lakes to create lakehouse architecture. With over 18 years of experience in web marketing, online SaaS business, and ecommerce growth. Pohan is passionate about innovation and is dedicated to communicating the significant impact data has in marketing. Pohan Lin also published articles for domains such as MarTech Cube.
Disclaimer: The author is completely responsible for the content of this article. The opinions expressed are their own and do not represent IEEE’s position nor that of the Computer Society nor its Leadership.