What is Data Sharing?

Data sharing is the process of making data accessible to authorized individuals, teams, or organizations, either within or outside of an organization. It involves the exchange of data between different systems, applications, or stakeholders, with the goal of improving collaboration, decision-making, and innovation. Data sharing can take many forms, including sharing customer data, collecting data from various sources, and integrating data from different systems.

In today’s data-driven world, the ability to share data efficiently is crucial for businesses looking to stay competitive. By sharing customer data, companies can gain valuable insights into customer behavior and preferences, allowing them to tailor their products and services to better meet customer needs. Additionally, integrating data from various sources can provide a more comprehensive view of business operations, enabling more informed decision-making.

We look at some ways embedded analytics can help your business and customers

Embedded analytics incorporates business intelligence and analytics software into an organization’s operational systems. The goal of embedded analytics is to provide users with actionable insights in real-time to help them make better decisions.

With , you can embed dashboards, reports, and analytic tools within your organization’s applications. This allows users to analyze data seamlessly and develop insights as they work without leaving their application and opening a separate BI tool. Additionally, embedded analytics can help manage consumer data securely, ensuring compliance with regulatory requirements.

So what are some of the benefits of embedded analytics for both your internal teams and also customers?

Integrate Embedded Analytics Into Pre-Existing Applications

One way embedded analytics benefits your business is by utilizing existing applications that you already use daily. This can include CRM software, ERP software, or even custom-built applications. By integrating embedded analytics, you can collect data from various sources, such as sensors on wind turbines, to enhance business intelligence and analytics.

Embedded analytics allows you to integrate reports into these applications to view and analyze data as you work. This can be done by adding simple reporting tools, such as graphs and charts, or by embedding more complex tools, such as predictive analytics models.

Switching between applications is time-consuming and disruptive, causing you to lose focus and, in some cases, valuable insights. Embedded analytics makes it easier for you and your team to pull insights from data as you work without jumping back and forth.

Adding new technology to any work process can add friction to your operations. Your team may already be overwhelmed by the number of SaaS products they’re using daily. However, embedded analytics doesn’t work like most of your other pieces of software. It isn’t separate from your BI platform. It’s implemented as a feature directly embedded within the BI platform, allowing data to be integrated with your existing applications. It’s seamless, so rather than adding to the complexity of the workflow, embedded analytics simplifies it.

Embedded Analytics Allows You to Easily Facilitate Data Sharing Among Your Teams

Embedded analytics allows you to share data more efficiently between and among your teams.

Transparency is vital when it comes to making good decisions. Having access to the correct data makes your team better informed. This aids them in making the right decisions.

Embedded analytics allows you to share data with your employees in an easily accessible way. They don't have to search for data within different applications or folders. The upfront visibility of embedded analytics results in everyone getting on the same page and seeing, for example, KPIs at their fingertips.

Every member of your team should have easy access to key performance metrics. Updated, accurate, and accessible charts and graphs are an excellent way to achieve this goal.

Some companies without embedded analytics rely on ad hoc methods, like screenshots of their BI dashboards, to share data among their teams.

However, these methods can be cumbersome and difficult to use. They also tend to lack the interactivity and accuracy that embedded analytics provides. They're not very robust either. (Where does that screenshot go after it's used? Probably the trash). They're also not transparent. Screenshots of data can easily be cherry-picked to fit a narrative.

With embedded analytics, data is most effective because it provides accountability and transparency, driving employees to reach goals. All team members have access to the same data.

Embedded Analytics Improves Communication With External Vendors, Partners, and Customers

Communication is essential in maintaining good relationships with your external vendors, partners, and customers.

Embedded analytics makes this communication more effective through transparency with the data that is being shared.

Having access to diverse data resources can improve communication and decision-making with external vendors, partners, and customers. Having a centralized location where all the data is stored and accessible is an excellent way to improve communication. Embedded analytics allows you to share data with your vendors, partners, and customers. Again this is a highly visible interface, so stakeholders will not have to search for data within different confusing applications or folders.

Without embedded analytics, your team needs to update your partners manually. This can take a few hours to a few days, making the data out-of-date, error-prone, or irrelevant. With embedded analytics, data is automatically updated and pushed to your partners in real-time.

Embedded Analytics Incorporates Customer Data Into Your Product

To improve your customer experience, you need to understand how your customers interact with your product.

Embedded analytics allows you to incorporate customer data into your product. This means that you can more easily track how customers use your product and where their pain points are. Managing consumer data securely can enhance customer trust and improve the overall customer experience. Embedded analytics doesn’t bury the data somewhere in the backend. It’s easily accessible.

With embedded analytics, you can see what your customers are doing and why they are doing it. This helps your sales team track issues and proactively develop solutions, giving you up-to-date data to anticipate customer needs and improve customer experience.

This also helps you and your team monitor your branding strategy and use gathered data to improve it.

Challenges to Data Access

Data access is a critical component of data sharing, but it can be hindered by several challenges. One of the main challenges is data silos, where data is isolated in different systems or departments, making it difficult to access and share. These silos can prevent teams from seeing the full picture, leading to fragmented insights and suboptimal decisions.

Another significant challenge is security risks. Sensitive data, such as personally identifiable information (PII), is vulnerable to unauthorized access or breaches. Ensuring that data is protected from these risks is essential for maintaining customer trust and complying with regulatory requirements.

Data quality assurance is also a major concern. Poor data quality can lead to inaccurate insights and decisions, undermining the value of data sharing efforts. Finally, documentation and data context are essential for making informed decisions, but they can often be lacking in data sharing practices. Without proper documentation, data consumers may struggle to understand the data’s origin, meaning, and relevance.

Overcoming Data Sharing Challenges

To overcome data sharing challenges, organizations can implement several strategies. First, establishing clear data governance policies and procedures is crucial. These policies ensure that data quality and security are maintained, providing a solid foundation for effective data sharing.

Using data integration tools can also help connect different data sources and systems, making it easier to access and share data. These tools can break down data silos, allowing for a more holistic view of the data and enabling better decision-making.

Robust security measures, such as encryption and access controls, are essential for protecting sensitive data. By implementing these measures, organizations can mitigate security risks and ensure that only authorized individuals have access to the data.

Finally, prioritizing documentation and data context is key. Providing clear and concise information about the data being shared helps data consumers understand its origin, meaning, and relevance, making it easier to use the data effectively.

Best Practices for Data Sharing

To ensure effective data sharing, organizations should follow several best practices. First, establishing clear data sharing policies and procedures is essential. These policies should outline what data can be shared, with whom, and under what circumstances, providing a framework for consistent and secure data sharing.

Using secure data sharing protocols, such as encryption and secure file transfer, is also important for protecting sensitive data. These protocols help ensure that data is transmitted safely and remains confidential.

Prioritizing data quality assurance is another key best practice. Ensuring that data is accurate, complete, and up-to-date is essential for making informed decisions and maximizing the value of data sharing efforts.

Finally, providing clear documentation and data context is crucial. By offering detailed information about the data being shared, organizations can help data consumers understand and use the data more effectively, leading to better insights and decisions.

Get Onboard With Embedded Analytics

Embedded analytics helps make your company more agile. Learnings aren’t buried in inaccessible data archives that are disused and forgotten. Data isn’t siloed in teams that can’t speak a common language.

Effective data collection practices enable better integration of data sources and more informed decision-making. Instead, embedded analytics improves communication between teams, encourages data sharing, aids good decision-making, enhances accountability, and keeps the latest, mission-critical data right where it should be: at everyone’s fingertips.

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