Data sharing – why it matters

Data sharing helps companies facilitate better collaboration, maintain greater transparency, and make smarter strategic decisions. Here’s how your business can benefit from it.

What is data sharing?

Data sharing is the process of distributing data between individuals, organizations, or systems.

It involves providing secure access to data sets specifically for the purposes of collaboration, research, or decision-making. This can either be done internally within an organization or externally to multiple parties or entities.

When conducted effectively, data sharing allows authorized users to access information that can help them improve a company’s efficiency, innovation, and transparency. It also enables them to do this while remaining compliant with privacy and security regulations.

Why is data sharing important?

Effective data sharing is essential for businesses because it allows them to break down silos, meaning teams and third parties can work better together, while reducing the potential for duplicated efforts.

The more securely businesses can exchange information, the better equipped they will be to tackle complex challenges that are beyond the capacity of a single entity. That said, there has traditionally been reluctance and a general mistrust when it comes to sharing sensitive data. 

However, new technologies are making it easier and safer for companies to do so in a way they can trust. When done well, sharing data can lead to better customer insights, smoother business operations, and smarter strategic decisions.

Examples of data sharing in action

Data sharing is a common practice in businesses across a wide range of industries. It's used to unlock new opportunities, strengthen partnerships, and drive organizations forward through innovation.

Here are some real-world examples of how companies are performing data sharing activities today:

Industry collaboration

Companies operating in the same sector can share data for the benefit of all, allowing them to discover market trends, safeguard themselves against fraud or cyberattacks, and develop more competitive strategies.

Customer engagement

By sharing relevant product information and service updates, enterprises can build trust and deliver more personalized customer experiences.

Scientific research

For researchers, exchanging data sets can make their work a lot more successful. It can also potentially speed up the process of discovery, validate their findings, and facilitate quicker breakthroughs in science and technology.

Public sector efficiency

Government organizations share data to refine their decision-making process. They can also use it to improve their resource management function. In doing this, they can deliver better services to the public.

Healthcare advancements

Hospitals, research institutions, and healthcare providers rely on sharing patient and clinical data. This helps them to improve diagnostics and develop new treatments, ultimately providing their patients with better care outcomes.

Common types of data sharing models

Typically, organizations can choose between a fully open or controlled access data sharing model. The model they pick is influenced by their goals, the sensitivity of the data, and what regulatory requirements they have to follow.

Here are the key differences between the two.

Fully open access 

In a fully open access model, data is made publicly available through repositories that have no restrictions imposed upon them. 

This model tends to be adopted by organizations and within industries, where such openness drives innovation. It allows for greater transparency, accelerating research and facilitating better collaboration across industries.

When executed successfully, the general public benefits greatly from what businesses create or achieve.

Controlled access

In a controlled access model, data is only shared with authorized users. Usually, this is only done after a screening or approval process.

This model is designed to safeguard sensitive or proprietary information that needs to be kept private and secure. It is widely adopted in industries like healthcare, finance, and other sectors.

Within them, compliance and ethical considerations need to be salient when handling personal data or intellectual property.

Top benefits of data sharing

For businesses that employ it, data sharing offers tangible advantages that drive progress and deliver results. Here are some of the main ways the practice can benefit both an employee or individual and the organization.

More effective collaboration

Sharing data breaks down silos, which allows teams, organizations, and researchers to work together more effectively toward achieving common objectives.

Make better decisions

Providing staff and management with more accurate and up-to-date data enables them to make better, more evidence-based decisions.

Increased innovation

The more access a business has to data, the more new ideas it can spark. This can help them achieve faster research breakthroughs and quicker product and service development.

Cost savings

Sharing existing data minimizes the risk of duplicated effort, data collection and storage, which can save a business a tidy sum in operational costs.

Greater transparency

If a company shares data openly, it can build greater trust with stakeholders and the public. It also demonstrates an openness and receptiveness on their part.

Competitive advantage

Organizations that share data put themselves in a position to potentially discover new products, services and market opportunities. This can help them to stay ahead of their competitors.

How does data sharing work?

Data sharing works through a series of coordinated technical processes that are designed to ensure information is transferred securely and used appropriately.

It starts with data preparation, which involves raw data being collected, cleaned, standardized, and organized. This ensures it is consistent and qualitative. 

After this, well-structured metadata (the information that describes the content, quality, and structure of the data) is then added to make sure the shared data stays relevant and meaningful for everyone involved.

Once the data is ready, businesses put access controls in place, which define who can retrieve the data and what they can do with it. Permissions are then assigned to various people or entities based on user roles and the sensitivity of the information that is being accessed.

Technologies like secure cloud data platforms, file transfer protocols, and APIs (application programming interfaces) help move the data efficiently and securely between systems and users. As data travels, it moves through secure channels, often between on-premises servers and cloud storage environments.

Encryption protects that data at every step. Monitoring tools track who accesses the data and how it is used, which helps companies to meet their obligations with regard to data compliance and security.

Important considerations before sharing data

Before sharing data, it is important for organizations to carefully weigh up several key factors, which primarily revolve around protecting sensitive information and ensuring regulatory compliance.

By addressing these factors, businesses can help build trust with their stakeholders and maximize the value and potential return on investment (ROI) of their data sharing initiatives.

Here are three factors worth considering:

Data security

One of the top priorities for companies is to protect the confidentiality and integrity of the data that's being shared.

To do this successfully, strong encryption protocols will need to be implemented along with secure storage solutions. In addition, real-time monitoring should be put in place to guard against unauthorized data access or breaches.

Overall, to be most effective, any security measures businesses adopt must cover the entire data lifecycle. It will need to include everything from preparation and transfer to storage to help them maintain the highest levels of data integrity. 

Data privacy

It’s essential for businesses to respect privacy rights. This is best achieved by complying with regulations such as GDPR, HIPAA, and CCPA. However, it's also important to anonymize or pseudonymize personal data wherever feasible and set up mechanisms that control who has access to it.

In addition, data sharing practices must be transparent and ethical, so informed consent should be gained from data subjects when required.

Data governance

Companies need a strong governance framework to define how data is managed, accessed, and shared. Clear policies need to be devised and rolled out to clarify exactly who has ownership rights, usage permissions, and responsibilities concerning the data.

Overall, good governance policies are important because they strengthen trust internally and externally. They are also responsible for ensuring that data is compliant with regulations and is being used appropriately.

Best data sharing practices you should follow

For data sharing to work most effectively, companies need to make sure they are adhering to best practices. Typically, these revolve around being efficient, secure, and compliant.

The first step is for them to establish clear data sharing agreements that outline responsibilities, access permissions, and the intended use of data. In addition, it's vital that they enable strong data access controls. Regularly reviewing permissions to avoid vulnerabilities is also crucial.

Where possible, personally identifiable information should be removed to protect privacy. At the same time, secure technologies such as encrypted cloud platforms and APIs must be adopted to transfer data safely between systems.

Like with any system, the process of data sharing should be continuously monitored and audited to help identify and address any issues early. However, equally important is the need to educate those who have access to the data on how to use it.

A good way to do this is to provide regular training on privacy laws, security protocols, and the ethical use of data. Doing this will strengthen your organization’s practices.

Lastly, companies should avoid common pitfalls like failing to standardize data formats, neglecting metadata management, or assumall users understand their responsibilities. Failure to do so can negatively impact the success of their data sharing activities.

Emerging trends shaping the future of data sharing

Data sharing technologies are constantly evolving. As such, a number of emerging systems and programs are starting to redefine how they work.

One major trend is federated learning, which enables organizations to collaboratively train artificial intelligence models without transferring raw data. This can go a long way towards better maintaining privacy and security.

Additionally, privacy-enhancing technologies (PETs) are also gaining traction. These tools include techniques like homomorphic encryption and secure multiparty computation. They have the potential to solve critical challenges around privacy compliance and trust. This can be achieved by allowing individuals to analyze data without exposing sensitive information. 

It's conceivable that open-source initiatives like Delta Sharing will make it easier to share large data sets more seamlessly and transparently. They are currently developing an even more robust ability to securely exchange data across different platforms. If successful, companies will soon be better able to standardize their protocols.

Summing up

Data sharing is an important business tool. It helps enable collaboration with others, innovation, and smarter decision-making. RecordPoint offers secure, scalable solutions to help you govern, protect, and maximize the value of your shared information.  If you're ready to transform how your organization manages data, take a tour of the Recordpoint Platform today or contact us to see how we can help.

FAQs

What are the biggest challenges of data sharing for organizations today?

The biggest challenges of data sharing are balancing data protection, avoiding security risks, and providing data securely to data consumers. As well, organizations must navigate a complex legal framework to allow public access or external data sharing without risking a data breach.

How does a data marketplace help improve business insights?

A data marketplace or enterprise data marketplace enables businesses to access external data, internal data, and research data from trusted data providers.

This access enhances data analysis and delivers more accurate business insights and business intelligence.

Why is data quality important in modern data environments?

Ensuring data is clean, integrated, and consistent is critical for data analytics and maintaining data trust.

High data quality supports better data processes. At the same time, it minimizes the risks of data sharing and strengthens collaboration across business units. Often this is done through the use of modern data systems like data stacks and data warehousing.

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