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What is Data Sharing? Overcome Data Sharing Obstacles

Due to the fact that technology has made our world more interconnected and dependent on one another, it is now more vital than ever to exchange data in order to maintain a competitive advantage. Nevertheless, many businesses continue to see the sharing of data as only a data function rather than a business goal, despite the fact that data sharing is associated with several competitive benefits.

Data sharing is, at its most fundamental level, the capacity to provide identical sets of data resources to many users or applications while ensuring data integrity across all entities consuming the data.

The study "Data Sharing Is a Business Necessity to Accelerate Digital Business" that was published by Gartner states:

"By 2023, firms that support data sharing will outperform their counterparts on most business value indicators".

Data may come from the enterprise's multiple software applications, ranging from website visitor behavior to signals from IoT devices as varied as household appliances or power grid sensors. In today's digital age, data sources seem almost limitless, which also means data quantities are astronomical.

In the commercial world, data sharing has become an increasingly significant problem. Traditionally described as a notion in academic research, data sharing as technology has become very important for organizations of all kinds, whether they need to distribute data across a huge, worldwide company or supplement internal data with wider market data to achieve superior insights.

Until recently, the most difficult aspect of data exchange was shifting ever-increasing data quantities. Both internal and external data sharing have been hindered by data transfer, which typically involves resource-intensive extract, transform, and load (ETL) operations. Maintaining data quality and best practices for data governance has also been a difficulty.

Throughout this article, we'll discuss what data sharing is, how it works, the benefits and drawbacks, the relevance of data sharing, types of data sharing, and whether data sharing is safe.

What is Data Sharing?

Modern data sharing is the provision of real-time access to controlled data across business divisions inside the same company or between external companies. A data provider is a corporate unit or external entity that distributes its data. Data consumers are organizations that seek to utilize shared data. Any firm may be both a data source and a data consumer.

Some data sources share data. Others share data services that make use of the data. For instance, a company may complement its own customer data with third-party data to get a deeper understanding of the age and income of groups that have made purchases from its website. The same firm may subscribe to a data service that cross-references online purchase activity with extra third-party demographic data, allowing for a more tailored understanding of each consumer group or segment.

In the current world, many data-producing scenarios exist, generating a vast amount of data from an ever-growing variety of internal and external data sources. Data markets are online transactional platforms that allow the buying and selling of data and data services. Moreover, it is now simple to obtain data from various second and third-party sources and to share your own data throughout your business and with external stakeholders in a safe manner.

How Does Data Sharing Work?

Modern cloud-based data sharing is expanding the possibilities for data sharing with cloud-based file sharing. Companies may facilitate the following:

  • Data sharing as a product (data provider):Provide data customers with direct access to certain data sets as a for-profit service to complement their current data.
  • Data sharing as a product differentiator: SaaS companies may give direct access to the petabytes of data produced by their B2B customers.
  • Create a single source of truth for all internal data and share it with thousands of internal data consumers across hundreds of business units inside a single company in order to eliminate data silos.
  • Share live data with internal and external company partners in order to optimize expenditures, deliver improved customer service, and simplify processes.

To effectively use cloud-based data sharing, organizations need a platform with speed, power, governance, security, and usability.

What are the Advantages of Data Sharing?

The primary advantages of data sharing are as follows:

  • Data sharing improves company outcomes: By 2023, Gartner expects that firms that support data sharing will outperform their counterparts on the majority of business value criteria. Gartner expects that by 2022, fewer than 5% of data-sharing platforms will properly identify and discover trustworthy data sources and data.
  • Innovative Technologies: implement AI/ML for accurate predictive data analysis.
  • Unified View: Create a unified source of the truth across all departments.
  • Transparency: Develop openness and transparency among stakeholders for improved decision-making.
  • Speed: Widen the area of analysis for an organization's data consumers.
  • Flexibility: Create new analytic reports swiftly and with fewer interruptions.
  • Synergy: Data sharing has intrinsic advantages for the researcher and research sponsor. Making the data accessible to their colleagues and the general public encourages academics to better manage and assure the quality of their data. Sponsors of research might gain from the sharing of data by generating interest and driving the continuation of study in their scientific area. Thus, data sharing may assist both the researcher and the study sponsor to gain notoriety and popularity.
  • Improving Science and Decisionmaking: Sharing data enhances data circulation and usage within the scientific community by fostering more openness, facilitating the reproducibility of discoveries, and enlightening the scientific community at large. In turn, this may be of considerable advantage to the public, since better and more widely distributed information can lead to more informed environmental planning and policy decisions.
  • Collaboration: Sharing data stimulates more interaction and cooperation among academics, which may lead to significant new discoveries in the area. In an era of decreased funding for science and research, data sharing is more effective since it enables researchers to pool their efforts. Sharing data enables academics to build on the work of others rather than repeating previously conducted studies. Sharing data also helps academics to do meta-analyses on the present subject of study. Meta-analyses are essential for identifying broad geographical or topical patterns. Therefore, data sharing assures that these sorts of studies will continue to be conducted.

What are the Disadvantages of Data Sharing?

The sharing of data is associated with a number of hazards, both to people and to organizations. These include the dangers of breaches in confidentiality and privacy, as well as the violation of other legitimate private interests, such as economic interests. Other hazards include the invasion of other legitimate private interests.

The main disadvantages of data sharing are listed below:

  • The more data openness the higher digital security risks: Typically, sharing needs information systems to be open so that data may be viewed and shared. This may expose further portions of an organization to digital security risks that may result in events that compromise the availability, integrity, or confidentiality of data and information systems upon which economic and social activities depend.
  • Higher impact of personal data breaches: Where data is accessible and shared, personal data breaches are more probable. They will not only create damage due to the invasion of privacy of the persons whose personal information has been compromised. They may also result in substantial economic losses for the afflicted firm, such as a loss of competitiveness and reputation.
  • Violation of privacy, intellectual property rights, and other interests: The hazards of increased access and sharing extend beyond breaches of digital security and personal data. They include risks of breaking contractual and socially agreed-upon conditions of data re-use, and therefore risks of acting against the reasonable expectations of users.
  • Data reuse in violation of agreed terms and expectations: Even when people and organizations agree to and consent to particular conditions for data sharing and data re-use, including the reasons for which the data should be re-used, there is a high danger that a third party would deliberately or accidentally use the data differently.
  • Loss of authority over data and the significance of permission: Unless certain data stewardship and processing rules are in place, once data are accessed or shared, they will leave the information system of the original data holder and therefore be out of his/her control. The same is true for those who supply their data and agree to its reuse and distribution. Then, data owners and people lose control over how their data are repurposed.
  • The limitations of anonymization and the growing potential of data analytics: Once connected to sufficient additional information, it is possible to forecast an individual's chance of possessing certain qualities in order to construct a profile. Even if the inferences are valid, there is a possibility that they might be exploited against an individual's best interests, desires, or expectations.

What is the Importance of Data Sharing?

Before diving into the importance of data sharing, it is necessary to first examine the reasons why data is not shared. Barriers to data access and organizational silos are the leading causes of non-sharing.

  • Data access restrictions. Access hurdles exist when workers do not have the authorization to see certain data, or if they do have, it is difficult for them to locate the information they want. These access obstacles are the result of conventional IT procedures that prioritize protecting sensitive data from unauthorized users. However, this technique might backfire since it inhibits staff cooperation. And when multiple departments want the same information but are unable to get it, it eventually slows down the company's production and efficiency.
  • Organizational silos. Also known as "data silos", these are internal procedures that block workers from seeing information that is important to their function but not part of their typical workflows. A sales manager, for instance, may not need to see an accounting report while conducting sales tasks. However, if they could obtain this data during an after-hours meeting or when confronted with a high-priority decision, they might use this knowledge to improve the company's results.

Today, organizations are under growing pressure to distinguish themselves from both conventional rivals and new entrants with digital expertise.

Your data is one of the keys to achieving a competitive advantage. The problem is gaining access to your data and gleaning insights that may lead to meaningful corporate benefits. It is practically difficult if everyone views their information independently.

Here comes data sharing into play.

Today, data, analytics, and associated reports are essential for making sound business decisions. Exceptionally actionable and helpful data is wasted if it is not used by the appropriate parties. If they never see relevant data, the money spent on data collection was squandered. Both data and insights must be disseminated and comprehended within your business and team. This will result in improved, more engaging consumer experiences and more actionable business choices and activities.

Data sharing allows everyone to have access to the same data, which reduces disinformation and guarantees that you can see the full picture of your organization. It minimizes inefficiencies, enhances cooperation, and provides business leaders with new possibilities.

According to Gartner, "Data and analytics executives who shared data externally had higher quantifiable business results than those who did not share".

Sharing information is crucial because it enables companies to:

  • Enhance openness and confidence among stakeholders.
  • Enable more efficient use of company resources. Essentially, data sharing may give the organization the appropriate data at the appropriate time, foster trust, and eventually generate real, concrete advantages.
  • Improving employee collaboration and productivity
  • It reduces duplicative efforts and costs.
  • Unlock precious data assets

What are the Different Kinds of Data Sharing?

There are two types of data sharing:

  • Traditional Data Sharing: Traditional data sharing systems are fraught with issues, making it difficult to identify, capture, and use all this data. In many instances, these conventional methods are expensive, generate human overhead, and restrict the amount of data a business can exchange.

Popular data exchange and transmission techniques include:

  • Email: A data file is sent from a provider to a customer via mail service.
  • File transfer: Data files are transferred and downloaded using File Transfer Protocol between two computers or the Internet (FTP).
  • Application Programming Interfaces (APIs): A proprietary API is used to start and control the data transmission.
  • Extract, Transform, Load (ETL) Software: ETL software pulls data from the provider's database, converts it into a consumable format, and then loads it into the consumer's database.
  • Cloud Storage: The provider keeps a copy of the data and gives the user access credentials to retrieve it.

Traditional Data Sharing

Figure 1. Traditional Data Sharing

Figure 1 illustrates how firms have typically shared data by duplicating and delivering it to their data consumers. The data consumers then download the data to analyze or combine it with their current data in order to get a greater understanding of their customers, the efficacy of their company's operations, and new market prospects. Unfortunately, these conventional means of data exchange are sluggish, difficult, expensive, and often only permit the transfer of limited quantities of obsolete data.

  • Modern Data Sharing: Figure 2 depicts a modern data sharing scenario in which a data supplier makes live, ready-to-query data accessible to its data consumers. The data may be exchanged among data cloud providers and countries without the need for ETL or other conventional techniques and is automatically updated, thereby reducing the administrative burden for both the data supplier and the data consumer. When sharing live read-only data, a data consumer may quickly access and integrate the shared data set without altering the original version from the data source. When the provider modifies a data set, the data consumer's read-only copy is almost instantly updated.

Modern Data Sharing

Figure 2. Modern Data Sharing

With modern data sharing technologies, a data provider may offer regulated access to the data it wishes to share without having to manage onerous data pipelines. Even when data consumers span several clouds, end-to-end security, multiparty governance, and metadata management services are consistently implemented. Automatic updates eliminate the need to connect apps, configure file-sharing protocols, or periodically upload fresh data in order to keep data updated.

Who Uses Data Sharing?

Researchers, research sponsors, data repositories, the scientific community, and the general public gain from data sharing. It promotes more interaction and cooperation among scientists, and better science leads to improved decision-making.

Is It Safe to Share Data?

Yes, but only under limited circumstances. Assuming your company has enough safeguards in place to protect users' privacy and prevent unauthorized access to their information, the potential advantages of data sharing clearly exceed the potential dangers of doing so. 54 percent of firms report that they are exchanging data more often than they did a year ago, despite the fact that privacy standards are constantly changing, high-profile data breach instances have occurred, and public opinion toward data privacy is negative.