Whether you need to distribute data across a large organization or need to augment your internal data with outside data sources to gain better insights, data sharing is an increasingly important component of a successful business.

According to Gartner, data sharing is a “business necessity to accelerate digital business” and companies that promote data sharing will outperform their peers on most business value metrics. In fact, a recent Gartner study found that data professionals who share data externally generate about three times more measurable economic benefit. 

What is data sharing? 

In a nutshell, data sharing is the act of making data available to other individuals or groups within an organization. Data sharing as a technology makes it possible for data to be easily distributed across an organization. 

Companies that share data make better informed business decisions, provide better clarity across their organizations, and unlock new revenue stream possibilities. However, many organizations discourage data sharing and place restrictions on access to data sources, which limits the capability of data to reach its full potential. 

Restricting access to data is like blocking important communication between departments of an organization. It’s forcing companies to operate in the dark, when instead they could be connected enough to see better strategies and solutions. Companies must adopt the mindset that data is meant to be shared in an organization and that it is a necessity that data is accessible at all times to those who need it.

Why is data sharing important?

Organizations require more and more data to solve problems, refine operations, and make the best informed decisions for growth and success. However, data can get complicated. An enormous amount of data is being generated all of the time—roughly 2.5 quintillion bytes of data every day. “Sharing is caring” when it comes to all of that data. Companies need a way to make sense of and access all of the data that is generating, or else the true potential of data will be lost. 

With so much information and so many new avenues to make use of that information, data is becoming a language that everyone in the organization must understand in order to operate as efficiently and effectively as possible. It is the guiding light that data science, marketing, operations, planning, and all other aspects of a business should be analyzing and following. 

In order for that to be a reality, that data must be accessible and understandable for everyone. Everyone within an organization needs to be fully aware and invested in not only their department’s data, but other departments as well, or else many important discoveries and insights might never be made. 

The challenges of data sharing

If data sharing is so beneficial, why are some organizations not implementing the practice? It comes down to a few hurdles. 

The first big challenge is changing the culture around data sharing. Organizations have traditionally embodied a data “ownership” culture as opposed to a data “sharing” culture, which has made it difficult for some companies to shift mindsets. Fostering a data sharing mindset that promotes collaboration between teams and departments can be a slow burn if departments aren’t used to operating that way. They need an easy and seamless system of data sharing to get the ball rolling in the right direction. 

That brings us to the second big challenge: formatting data so that all departments can access and use it. Data is formatted differently across the various departments of an organization, with each department speaking its own data “language.” One department’s data might not be decipherable by another department’s programs and systems. It can be a tiresome and convoluted process to transfer data from one department or system to another. Data needs to be re-formatted by data engineers to be understandable and usable, which can often take days or even weeks.

The last big challenge is findability. Even if organizations have all of their data accessible in one place, it can be a meticulous process sifting through all of that data to find the points that are relevant to your department. If a marketing department is trying to acquire data from a sales department, for example, they might only be interested in a certain product’s sales or in the purchasing behavior of a specific demographic. It can be difficult to find that exact data in a labyrinth of other data if it isn’t organized or packaged in an easily findable way. 

However, as data technology improves and companies realize the importance of data sharing, these traditional barriers and challenges are crumbling. The latest technology and software available today enables organizations to store data in flexible data lakes, automate data wrangling, transform and transfer data seamlessly, and package data into usable products. Much of this is made possible through a new solution: data commerce platforms.

Using data collaboration platforms for internal data collaboration

A data collaboration platform provides software that enables the cleaning, organization, and transference of data seamlessly. These platforms automate the most time- and labor-intensive aspects of data sharing, such as cleaning and standardizing the data. They also simplify the ins and outs of data sharing so that it is easy for anyone within an organization to master, even if they have no technical expertise or coding experience. Using a data collaboration platform, an organization can set up internal data collaboration between departments and create an easily usable and accessible data ecosystem for their company. 

New software like Rosetta Stone makes it possible for data collaboration platforms to take data as it is natively stored and “translate” that data to be understood by external systems. You won’t need to get data engineers on the job of reformatting data, since it will be automatically formatted for you right out of the box. Instead of waiting days or weeks for data to be reformatted and transferred, it can take mere hours to get the data you need in the exact format you need. 

Other technologies available through data collaboration platforms make it possible to organize data so that it is easily discoverable. Thanks to apps like Data Shops, departments can organize their data into “products” and put them into “shops,” making it easy to browse through and find datasets in a familiar ecommerce experience. 

Other apps, like Buyer Studio, use a simple step-by-step process to find and acquire only the precise data points that match your specific needs, based on your custom filters and parameters. These types of software make it simple and straightforward to share only relevant and actionable data, as opposed to having to comb through tons of unusable data.

Data collaboration platforms are easy to use, highly flexible, and also safe and secure. Organizations can set their preferred access limits, allowing only members of their organization to be able to access and transfer data between each other, creating a safe and easily navigable data ecosystem. Once data sharing is made this simple and secure, it will become the norm and data will flow seamlessly across your organization.

Use Narrative’s data collaboration platform for easy, fast, and seamless data sharing

Narrative’s data collaboration platform provides the tools and workflows that make transferring data easier and more efficient than ever before. Anyone within an organization (even your intern) will be able to use Narrative’s apps to find and acquire precise data or create actionable data products with no technical knowledge required. 

All cleaning and standardizing of data is taken care of on the backend, so that your data engineers don’t need to waste their time, and the latest technologies make it easy to simply point and click your way to the data you need. Narrative’s custom filters, automatic deduplication, and user-friendly interface make acquiring data as seamless and precise as possible, so that anyone within your organization can access the data they need at the drop of a hat.

Want to set up a data collaboration ecosystem for your organization? Contact our team of experts to get started!