What are Data Silos?

A data silo is a collection of data held by one group that is not easily or fully accessible by other groups. Data tends to be organized by internal departments. Finance, administration, HR, and other departments need different information to do their work, and those individual collections of often overlapping-but-inconsistent data are in separate silos. As the quantity and diversity of data grows, silos continue to grow too. 

Data silos hinder the process of gleaning deep, actionable insights from organizational data, and create a barrier to a holistic view of company data. To harvest the full benefits of data analysis, organizations need a 360-degree view of their data in order to get an enterprise-wide view of hidden opportunities (or threats!).

To better understand if data silos are holding back your potential for holistic data analysis, you can learn more about data silos, how they hinder getting the full benefit of data, and what you can do to achieve data integration.

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Where do data silos come from?

Data silos occur naturally over time and stem from conditions common to most businesses. As each department collects and stores its own data for its own purposes, it creates its own data silo.

Organizational structure

Before big data and the cloud revolutionized business, it wasn’t considered a bad thing for different departments to create and manage their own data. Each department has its own policies, procedures, and goals. Teams developed their own ways of working with and analyzing data in ways that suited their needs. Silos were built around company departments because that's how the data was collected and stored. 

Culture

Operations, HR, admissions, and other departments are accustomed to working in their own worlds. Each has its own lingo, processes, and challenges. They work in physically separate areas, so each department naturally considers itself separate from the others. This culture of separation ties over to data. Since company-wide data sharing is a relatively new goal, departments haven't been motivated to share. 

Technology

Departments tend to support their operations using different technology solutions and tools, such as spreadsheets, accounting software, or hospital management software. Each solution stores and manages data in different ways — many of which are proprietary to the vendor that created the solution. Legacy systems were not designed to easily share data. So the tech tools many organizations use every day have pushed them into data silos by the proprietary nature of their data management processes 

4 ways data silos are silently tearing down the organization

Each department exists to support a common goal. While departments operate separately, they are also interdependent. At least some of the data that the finance department creates and manages, for example, is relevant for analysis by administration and other departments.

Competition, the need to cut costs, and the desire to seize opportunities are driving organizations to do more with their data. Access to enterprise-wide information is necessary to maximize operational efficiencies and discover new opportunities.

But at some point, data silos will pose a barrier to success. Here are four common ways that can happen:

  1. Data silos limit the view of data

Silos prevent relevant data from being shared. Each department's analysis is limited by its own view. Discovering enterprise-wide efficiencies can't happen without an enterprise-wide view of data. How can you find hidden opportunities for operational cost savings, for example, if operations and cost data aren't consolidated? 

  1. Data silos threaten data integrity

When data is siloed, the same information is often stored in different databases, leading to inconsistencies between departmental data. As data ages, it can become less accurate, and therefore, less useful. For example, if data on the same patient is stored in different systems, this data can become out of sync over time. 

  1. Data silos waste resources

When the same information is stored in different places, and when users download data into their personal or group storage, resources suffer. Streamlining data into one source frees up precious storage and relieves IT stress in buying and maintaining storage that may not be needed. For example, many workers download data to analyze in a spreadsheet, and each download is a redundant copy of existing data. 

  1. Data silos discourage collaborative work

Culture creates silos, and silos reinforce culture. Data-driven organizations are embracing collaboration as a powerful tool to find and leverage new insights. In order to encourage collaboration, departments need a way to share their data. When data is difficult or impossible to share, the ability to collaborate suffers. 

How to break down data silos

Centralizing data for analysis has become much faster and easier in the cloud. What took weeks, months, or years can now be accomplished in days or hours with tools that streamline the process of gathering data into a common pool and format for efficient analysis. The solutions to silos are technological and organizational.

  1. Change the culture

Communicate the benefits of data sharing so that workers understand the shift. Also communicate the problems with silos, including data integrity and the inability to be competitive. Culture change is a challenge, so management must show commitment.

  1. Develop a way to centralize data

The best way to bust silos is to pool data into a cloud-based data warehouse or data lake — central data repositories optimized for efficient analysis. Data from disparate sources are homogenized and consolidated, and access can be easily granted to individuals or groups.

 

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  1. Integrate data

Integrating data efficiently and accurately is a guaranteed method to preventing future data silos. Organizations integrate data using different methods.

Scripting

Organizations can task IT with writing scripts in SQL, Python, or other scripting languages to move data from siloed data sources and into the warehouse. The downside to scripting is it can be complex, and as data sources grow, complexity grows. Changes in data sources require scripts to be updated, so maintenance becomes a cost and time burden for IT professionals.

On-premises ETL tools

ETL (extract, transform, and load) and ELT tools automate the process of moving data from various sources to the data warehouse. These tools extract data from sources, transform data into a common format for analysis, and load the result into a data warehouse located in the organization's data center.

Cloud-based ETL

The cloud and data go hand-in-hand, and sophisticated cloud providers are making the ETL process easier and faster. Cloud-based ETL takes advantage of the cloud provider's infrastructure — including a data warehouse and ETL tools designed to work efficiently in their environment. ETL breaks down silos by providing the technological means to gather data from different sources into a central location for analysis. ETL helps handle data integrity issues so that everyone is always working with fresh data. 

  1. Establish governed self-service access

When data is centralized, you also have the opportunity to centralize data governance. These access policies facilitate self-service analysis, so those with permission can easily access the data as needed.

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The cloud and the future of data storage

The cloud has emerged as a natural way to centralize data from diverse sources to make it easily accessible from the office, at home, on the road, or by branch operations.

The cloud helps eliminate the technology barriers to collaboration and offers a ready solution to data silos. Using an established ETL process to strip away irrelevant data and eliminate duplication, organizations can add new and updated data to a cloud data warehouse quickly. This enables finance, administration, HR, and other departments to work collaboratively with fresh, clean, and timely data in a single, accessible platform that scales to meet demand.

Cloud technology and cloud data warehouses facilitates collaboration and gives analysts a 360-degree view of the organization through access to enterprise-wide data. Data analysts get a better view of how their work affects the whole organization, and how others' work affects theirs.

Tearing down data silos

Data silos undermine productivity, hinder insights, and obstruct collaboration. But silos cease to be a barrier when data is centralized and optimized for analysis. Centralizing in the cloud has advantages in that cloud technology has been optimized to make centralization practical.

Centralizing data in the cloud with Talend Data Fabric has advantages because Talend simplifies data integration ETL, data governance, security, and regulatory compliance while providing silo-busting access to data by every department. For example, Travis Perkins—a building materials supplier — razed their silos in order to better collect, govern, transform, and share data. In the process, they increased sales by 30 percent.

Talend Data Fabric enables users across the organization to collaborate using a comprehensive suite of apps — one solution for simplifying the process of busting silos forever.  You can try Talend Data Fabric to see for yourself how Talend can partner with you to banish silos, improve operations, and boost profits — ensuring you have trusted data to guide your business strategy.

| Last Updated: August 31st, 2019