Data sharing is when a company chooses to make the data they’ve collected available at a broader level. The sharing of information is a practice that has been done in the academic field for a long time, but it is also a widely-used practice in non-academic areas, like retail.
Data-sharing consists of four main parts: data collection, data preparation, and data analysis.
Data collection can be completed using interviews, questionnaires, polls, visual observations, tests, records and documents, and surveys, among other things. Some of these forms allow you to collect data more quickly than others. For example, standardized test responses are recorded using a computer or using a Scantron. Both of these enable the data to be collected and organized almost instantaneously. On the other hand, visual observations require you to extract the data you feel is relevant and input it manually.
Once data has been collected and entered into a data management system, it is time to prepare it. Data preparation “prepares” data for analysis by cleaning up and structuring it in a way that makes it usable. Data is entered into the system and cleaned during this step, which involves removing any empty responses, correcting any errors, and reformatting.
Data analysis is the process of taking prepared data and interpreting it, making that data usable. During data analysis, analysts inspect data, highlight trends, make predictions, and translate the data into usable information.
There are many reasons why an organization would choose to share its data. The three main reasons are collaboration, education, and the sharing of resources.
Using data to create partnerships with other companies or organizations can lead to better product development. For example, if a popular restaurant chain chooses to collaborate with a supermarket, that restaurant chain can use its market trends to expand its business into retail. This type of collaboration means both companies will profit in the end. The restaurant chain will see increased revenue through the grocery store chain, and the grocery store will be able to wield the restaurant’s popularity to boost their own profits.
Sharing data can also allow companies to show complete transparency concerning their business practices, revenues, and spending. Transparency can increase consumer confidence in the company and appease shareholders who hold a financial stake in the company.
The sharing of data and research is essential to many industries because it can increase the overall value of the data.
In for-profit industries, data from one company might be shared with another field to increase profits. For example, data mining from search engines can allow companies to target advertising and increase revenue.
Sharing data can increase innovation in the academic or science fields by widening the pool of experts studying the data. For example, when one pharmaceutical company develops a medication or vaccine, they might share their data and research with other agencies. Sharing in this way can also allow medications to be made available to broader swaths of the world.
Selling or auctioning data to other companies is one way to share data. For example, when a person visits a website, their activity can be sent to advertisers, who will then decide whether or not they want to make a bid to show that person targeted advertising.
When one company hires another company to perform a service, that service provider then gains access to all of the company’s data. For example, if a website collects the DNA of users to reveal their heritage, that company will typically use a privately owned DNA laboratory to test the samples. When data is sent from the collection company to the testing company in the form of customer information, two organizations now have access to that set of data.
Data sharing can have many uses, making it essential for companies to understand how and why it should be shared. Being able to broaden the scope of research, identify cross-market trends, and combine resources can benefit all parties involved.