Stay up to date with the latest trends, innovations and insights.

Data Silos FAQ: What Executives Need to Know

Rafael Dourado

In this article, explore and understand what is a vector database, this promising and innovative trend in the data market.

In companies of all sizes, it is common for individual teams to make decisions based on data only accessible to them. We call these data silos, separate collections of information available to a particular group of employees that are hard to access by others in the organization. While these divides are common, they are not advantageous to operations. 54% of companies identified data silos as the top reason they could not make data actionable, according to a recent survey.

These silos cause confusion and inconsistent decision-making throughout companies. It can be hard to know why other departments make certain choices without looking at the same information. Plus, one team may be keeping vital data away from another department without even realizing it.

As a business leader, you may be seeing these data silos emerging within your organization. In some cases, these walled-off sets of data may have even been there before you joined the company. In this article, we’ll answer some frequently asked questions about data silos. By the end, you’ll know how these silos emerge, their disadvantages, and how you can encourage a more open and consistent flow of information throughout your company.

Why Do Data Silos Occur?

Data silos often emerge when individual teams discover they need specific information related to their initiatives. By itself, this is not a problem. However, they failed to coordinate this effort with other departments. Plus, there is often no company-wide data platform where they can input their collected information. These circumstances, a less-than collaborative work environment and the lack of a definitive data platform across departments, are a perfect environment for data silos.

This often leads to one of two outcomes. First, the team could create a set of data that is largely a duplicate to one another department already had. This is a major blow to efficiency, wasting hours or even days on redundant tasks. Plus, there may be consistency issues between the data points each team collected, hurting future integration efforts. Last year, over 60% of data scientists, c-suite executives, and others told O’Reilly that their organizations suffer from inconsistent data.

In other cases, the team might collect mostly original information. While this sounds like a better scenario, it means this department now has exclusive access to data that other internal groups would also want to leverage. By compartmentalizing access to insights, your company limits the potential benefits.

Three young professionals looking over data on a laptop.

Why Are Data Silos Bad?

As you likely can already tell, data silos are a major setback to innovation in many companies. With each department operating with its own information, it is difficult to come together to make macro-level decisions that set your company apart. “As a business leader, you have very limited capability to make good decisions and drive results,” Vyaire Medical CIO Ed Rybicki told Forbes.

If each team is embarking on duplicate efforts to gather and input data, this also costs your organization massive amounts of time. A more collaborative, company-wide effort to collect and sort through data would help efficiency.

These silos also lead to splintered decision-making. With little universally agreed-upon data within a company, it is hard to form a consensus between departments. One team may not understand why another one operates the way they do or why they’re advocating for certain processes at a company-wide level.

How Do You Solve Data Silos?

There are two important steps to dismantle data silos. The first is creating a more collaborative work environment, and the second is consolidating data into one definitive platform.

Let’s start with the former. Your organization can spend time and resources creating a database where everyone can enter and access the information they need. However, if your company does not have a culture of open and frequent communication, teams will still leave insights hiding away in spreadsheets.

Ensure departments have plenty of opportunities to come together and share their latest projects. And, when those meetings happen, empower each team to communicate fully and honestly. Here’s a great TEDx Talk about fostering collaboration, even when it’s not easy.

Professional gathering data for meeting with other departments.

As your organization begins addressing cultural silos, you can also respond to the physical data silos. The best option is to create a centralized platform where all employees can access, input, and edit the data pertinent to them. That way, all departments make decisions and resolve disagreements using the same data source.

Programmers has the expertise necessary to build these integrated data platforms for your organization. We structure your systems in the way that best fits your company’s needs, whether it be a Data Lake, Data Warehouse, or even both. Learn more about how Programmers helps you effectively leverage insights throughout your organization.

This repository can come in many forms including a data lake and data warehouse. Below, learn more about these two solutions. 

What Is a Data Lake? 

Data lakes are fluid repositories that can contain both structured and unstructured data. This information usually reaches the data lake “as is.” That means someone with a strong background in data science in your company will need to make sense of this information before the rest of your employees can leverage it.  

“Structured” data is the type of information you’d traditionally associate with a database, numbers neatly filed away in columns and rows. “Unstructured” data is everything else, such as videos, audio files, documents, or raw, real-time data that contains vital information for your business. Being able to handle unstructured data is one of data lakes’ key advantages.

Let’s look at an example. If you were a CIO at a telemarketing company, recording employees’ sales calls (with the permission of everyone involved, of course) could be pivotal to tracking overall sales performance. You could take these recordings and store them in a data lake, where someone could later find key information to turn into structured data, such as the number of times prospective buyers hung up on each sales associate per day.

What Is a Data Warehouse?

A data warehouse is a structured repository full of mostly historical data. Employees without a background in data science will find it intuitive to search for information within a data warehouse. However, they will not be able to leverage real-time data or find videos, audio, documents, and other unstructured data that could contain key insights.

How does a data warehouse make it so easy to find historical data? Following an ETL (extract, transform, and load) process, data warehouses pull information from pre-established sources at routine times, transform that raw data in a way that makes sense for business users, and then load it within the warehouse.

As you learn about data lakes and warehouses, it may be difficult to decide which is best for your organization. There are also solutions like the emerging data lakehouse that offer a blend of both repositories. Learn more about data lakes, warehouses, and lakehouses in our recent e-book. The book outlines the key pros and cons of these repositories and provides real-world examples of their benefits from a senior business intelligence expert.

Journey to Becoming Data-Driven

Dismantling data silos is just one step on your longer journey to becoming data-driven. While the term gets used often with little explanation, being “data-driven” means empowering employees throughout your organization to find and leverage insights that streamline processes, improve the customer experience, and unlock innovation that puts your organization ahead of competitors. According to a recent study, only 24% of executives would describe their company as data-driven.

So, what are your next steps on the journey? Right now, you are focused on getting rid of data silos with a stronger data culture and a centralized repository. Next, you can expand your employees’ ability to create reports. You can also begin leveraging predictive and prescriptive analytics with AI to ensure your organization is one step ahead of market shifts. Begin charting your journey to becoming data-driven with our recent blog post.

In Conclusion

Data silos can be a profound issue for organizations. They make it difficult for leaders throughout your company to make decisions with a complete view of the situation. Plus, as departments operate with fragmented information that only they can access, they’re likely pulling your organization in opposite directions.

Getting rid of data silos requires fostering better collaboration between teams. As you begin dismantling these cultural silos, it’s also important to build a centralized data repository that can be the single source of truth for your company. Ensure this repository, whether it be a data lake or warehouse, or anything in-between, makes your employees’ jobs easier and empowers them to build their data skills.  

Looking at the bigger picture, all these are steps in your larger journey to becoming data-driven. Seeing this journey through to the end is vital if you want to make fast, informed decisions throughout your company based on the most high-quality, up-to-date information possible. Programmers can help every step of the way, from understanding your current capabilities to unlocking predictive and prescriptive analytics. Learn more about our data analytics solutions here.

Want to see how Programmers turns data into actionable insights? Learn how we helped a popular fast-food chain discover the perfect coupon combo for its customers.

Stay up to date on the latest trends, innovations and insights.