Unlocking the power of data collaboration

It’s almost a cliché now – businesses regard data as their most valuable asset. But companies only truly realize the value of their data when stakeholders have access to all relevant data sources, both internal and external. So how can your business unlock its power to generate more valuable insights from the full range of data available?

Let’s look at how businesses can improve their data collaboration practices to improve results. 

What is a data silo?

A data silo is a data source or repository that's controlled and accessed by a single department or business unit, rendering the data inaccessible to others in the business. When data silos exist within an organization, everyone is less able to access the valuable data their company holds.

As an example, consider the common scenario that occurs when sales teams store customer or prospect data in a system that can't be accessed by other teams. While this data could potentially provide a source of truth to people on other teams — perhaps marketing teams or finance departments — they aren't able to access or leverage it. This is a data silo.

What is data collaboration? 

Data collaboration is a process that involves gathering, sharing, and exchanging data in a unified manner from multiple sources so that domain experts, teams, and data-sharing partnerships can use combined insights to create new value. From this definition, it’s important to understand that data collaboration can happen both internally and externally.  

Benefits of data collaboration 

Access more internal data 

Internally, collaboration across business units can help domain experts to combine information and together derive new insights. These insights could improve customer experience, help understand the performance of new technologies, or help solve any number of business problems. In a world where 68 percent of enterprise data goes unused for analytics projects, data collaboration brings teams together to identify and leverage the full range of internal data that can help meet business objectives.  

Leverage the power of external data 

Externally, collaboration with a strategic partner lets both parties benefit from the abundance of useful information that often exists outside of their own respective IT environments. Partnerships could be with resellers, vendors, companies with which your business shares an interest, channel partners, consultants, or even commercial data provider platforms. Combining external and internal information potentially unlocks new insights about customer behavior, markets, supply chains, and the competitive landscape in which you operate.  

Get insights faster 

Fostering an environment of data collaboration inherently brings people together from different areas of expertise, different business units, and different organizations, providing a single source of truth regarding your company's data. The result is that shared perspectives and expertise on a wider variety of information help to identify opportunities and unearth insights faster, improving your ability to make strategic business decisions. In an increasingly fast-paced and dynamic digital world, speed matters in getting data-driven insights.   

Obstacles to data collaboration 

If data collaboration were easy, every business would be doing it and getting the most value from the information assets at their disposal. In the real world, several obstacles hamper effective data collaboration efforts—here are three of the most persistent challenges, including one that might look familiar by now.

Data silos 

A crucial factor in data collaboration is the ability for employees across your organization to be able to access internal data, no matter where it resides. The reality for most companies though is that data silos exist everywhere, with information being scattered across and locked into a disparate variety of SaaS and on-premises applications used by different business units. Each of these apps creates its own database silo. This is all made more challenging when organizations adopt new data sources, as many did during COVID-19, leading to related challenges caused by data sprawl. 
 
When there are internal silos, data is hard to discover and access. In an IT environment defined by internal data silos, data consumers (people or applications that use data) don’t know about or cannot access highly relevant data locked away in other parts of the business, including first-party data directly collected from customers.   

Security and privacy challenges 

The default attitude of many business leaders in a tightly regulated data privacy landscape is to exercise extreme caution around how data is shared and with whom, both inside and outside the company. This attitude is understandable given that a breach of sensitive customer information comes with hefty costs from penalties, legal issues, and reputational damage.  
 
Beyond threats to customer information, there is also the potential to reveal trade secrets that only privileged individuals should see, sensitive company or employee information, and more. These security and privacy challenges arise with both internal and external sharing. Sharing data with the right security and privacy controls in place (e.g. sharing only portions of a table, encrypting data in motion and at rest) is imperative in overcoming this obstacle.  

Lack of trust 

The goal of data collaboration is to bring all available data together to enhance business outcomes. Naturally, this involves exchanging data with third parties, and more importantly, trusting those third parties with a valuable business asset. Hesitance to trust a third party can limit data collaboration and lead to missing out on useful insights. Critical in overcoming this obstacle is to exercise due diligence and tightly control the information shared.  

This trust challenge works both way: data consumers might have difficulty trusting the quality of information shared with them by external partners. It’s essential to understand how this data was compiled, how accurate it is, and how up-to-date it is. Without trust in the data, you may not want to use it.  

How RecordPoint can help 

RecordPoint provides a modern, intelligent data management platform that directly help you limit data silos and build data collaboration

Step 1:

Automated data discovery tools help you create a comprehensive data inventory using our flexible connector framework, allowing you to integrate with any data source. AI-powered auto-classification instantly identifies the location and contents of sensitive data pieces. 

Step 2:

Improve the way new data is classified using custom rules or machine learning models securely trained on your own data. Automatically remove ROT for proactive minimization and enjoy full visibility over every piece of data.  

Step 3:

Create and apply custom retention schedules, automating the process of data minimization. Find trends and disruptions to your data with custom or pre-built reporting dashboards. Take compliance obligations from headache to hands-free with proactive, automated data management.  

By leveraging the strategies we’ve discussed today, along with the support of a partner like RecordPoint, you can operate with confidence, knowing your organization is taking the right steps to enable data collaboration and avoiding the issues that come along with data silos.