When data is accessed and shared, people, organisations, and governments all have similar difficulties. Numerous of these issues were raised during the Copenhagen Expert Workshop, Joint CSTP-GSF, and Stockholm Open Government seminars.In order to facilitate and promote improved access and sharing, policymakers must solve many significant difficulties, which are summarised in this chapter. The following three important topics, each of which is covered in a separate section below, have been combined together:

1. Weighing the dangers and rewards of increased data access and exchange while taking into account genuine individual, national, and public interests. To achieve this, cross-border data flows may need to have unnecessary obstacles removed.

2. Increasing the value of data reuse through fostering community building, proactive stakeholder involvement, and trust-building among users in order to promote data sharing. Significant expenses could be incurred for maintaining community engagement as well as for developing data-related infrastructures, standards, and skills.

3. Considering the constraints of (data) markets while promoting the production of data through sensible incentive structures and viable business models. In order to do this, it may be necessary to address questions about who owns the data and to clarify the roles of privacy, intellectual property rights (IPRs), and other rights that are similar to ownership. These tasks should ideally be handled by the appropriate expert agencies and organisations.

These problems are connected. For instance, allowing people to manage some of the risks associated with increased access and sharing can strengthen trust. Additionally, incentive structures must take into account both private and public interests in order to ensure their coherence.Policymakers must avoid the 'data policy fallacy' while tackling these matters of policy, which, as was discussed during the Copenhagen Expert Workshop, is the propensity to search for a single panacea to a complex issue. Frameworks for flexible data governance that are sensitive to domain and cultural specificities and take into consideration the many types of data and the contexts in which they are used are essential.

Data Access difficulty

1. Incompetence

Data security and access management takes a long time to complete. Actual security procedures are now ineffective for the majority of businesses that are even aware that their data access protocols are a problem, whether you are manually securing unstructured data or whether it is data that is being dealt with automatically.Enterprises must determine where their data is located in the environment, how much data is lost due to the use of file servers and NAS devices, and even create an inventory of the SharePoint deployments' accessible features in order to secure it effectively. You'll agree that it's all incredibly time-consuming.

2. Lack of efficacy

The second important question is whether they should have a certain amount of access or not after addressing the issue of who has access to your data. Should this decision be placed in the hands of the IT department at all? Does IT know what level of access should be provided to employees?The likelihood is that they shouldn't be permitted to make a judgement, given this is ultimately a commercial one. But, as with the majority of businesses, there is no explicit policy regarding who makes the decisions. In this circumstance, there's a good chance that there will also be a lot of unstructured and orphaned data laying about with no one to take responsibility for it.

3. Lack of Flexibility

In an ideal world, everyone would utilise predictive analytics to foresee problems before they arise. However, the reality is different, and the majority of businesses are reactive—they respond to issues as they arise. It is quite tough to be agile, and we have already observed that agile firms are successful companies, if you simply react to a problem as it arises.For instance, what happens if data is attributed to a certain person and that employee leaves? Where does that data go, and who becomes the owner of it, if your company acquires another business?These problems are addressed by a wide variety of products from a wide variety of suppliers, including access governance software.

Final Remarks

The goal is to have complete visibility over all of the data in your system, including a perspective of what you have, who has access to it, and even how and where it is being utilised.In general, these are the most important considerations, which may be summed up by highlighting the importance of preparation in all matters involving data, however there may be more factors that should be taken into account for specific situations.

Data sharing difficulty

1. Management of Data

A key element of successful data efforts is effective data management. Organisations are able to make sure that any data they gather and create is accessible and being utilised properly by developing standardised, centralised processes around ingesting, classifying, storing, organising, and managing data.It's simple to lose track of how data is utilised and shared, especially internally, without a solid data management strategy and methodology. Teams are more likely to make copies of data that governance teams can't access when they don't know where or how to get the data. As a result, there is a risk of illegal access and insufficient data access control procedures.

2. Security Risk Evaluation

How do you know data privacy and security safeguards are operating as planned once they are in place? Your data may not be safeguarded just by using data de-identification procedures. The ideal place to start with anonymization techniques is with risk-based evaluations, but many businesses lack the capacity to do so, especially as the number of data sources increases.Understanding your organization's level of data risk can be challenging, especially if there is no obvious way to close gaps. As a result, CDOs identified data security risk assessments as the main impediment to sharing data, especially externally.

3. Insufficient Technology and Tools

We have already discussed how technical tools help data engineering and operations teams overcome some of the major obstacles to data sharing. Insufficient tools and technology were mentioned by CDOs as the main problem with data sharing despite their recognition of the need of these resources.Technology is frequently seen as reducing complexity and streamlining data-related activities. But there are now numerous different cloud data providers that each offer a unique set of data access rules. This patchwork of inconsistent capabilities frequently doesn't scale uniformly across various cloud data platforms as data teams continue to adopt several cloud data platforms at an accelerated rate.

Conclusion 

Conclusion According to analysts, teamwork and data sharing will become more and more crucial to an organization's performance and competitiveness over the next two years and beyond. The top five data sharing roadblocks have solutions right at your fingertips, despite the fact that 70% of study participants in the Harvard Business Review stated they were “not particularly effective at exchanging data.”

You will be in a better position to outperform rivals in terms of generating revenue and achieving business objectives by emphasising data sharing and management as essential business functions, rethinking your organization's strategy for sharing data both internally and externally, and investing in the tools and technology that facilitate secure, effective data sharing.