Roughly 2.5 quintillion bytes of data is produced every single day. In an ideal world, organizations would leverage that data to build better products, provide better services, and even create new revenue streams. Yet, there’s a fundamental problem holding organizations back from leveraging the treasure trove of data that’s available to them. Despite the fact that 62% of organizations say that self-service business intelligence is “critical,” most only analyze 12% of their data.
Embedded analytics play a key role in democratizing data access and driving adoption outside of data and BI teams. It also can accelerate time to value for data applications by allowing teams to work together to build applications faster with better user experiences – and reduced development costs.
This comprehensive guide will look at precisely what embedded analytics is, the benefits organizations can expect, best practices and essentials for success, popular use cases, and five must-have features for embedded analytics platforms.
Table of Contents
- What Is Embedded Analytics?
- How Embedded Analytics Is Different From Traditional BI: Access and Participation
- Why Embedded Analytics Platforms Accelerate Time To Value For Data Applications
- 5 Immediate Benefits of Embedded Analytics For Data-driven Organizations
- 4 Popular Examples of Embedded Analytics
- 5 Keys To Success In Embedded Analytics
- 10 Must-have Features For Embedded Analytics Platforms
- Experience the Benefits of Embedded Analytics
What Is Embedded Analytics?
Embedded analytics tames cumbersome workflows and increases the speed and ease of data discovery by adding dashboards and visualizations directly into internal and external applications. Most commonly, organizations take the reports, visualizations, and dashboards that they build in BI and analytics tools and embed them into:
- Customer or partner-facing applications: Many companies are leveraging embedded analytics solutions to monetize their data and quickly deliver high-quality data products that drive customer and partner satisfaction.
- Internal business applications: Embedding relevant analyses directly into business workflows increases the ease and frequency of data-driven decision-making across the organization.
- Public-facing web pages: Companies may choose to share research they’ve done around particular industries or global events to garner press coverage and brand awareness.
How Embedded Analytics Is Different From Traditional BI: Access and Participation
Traditional BI requires that real-time reports and visualizations be viewed natively within analytics tools, which are most often unfriendly to business users. Embedded analytics makes reports and visualizations available within existing workflows, software, and systems — allowing non-technical users to work with and benefit from data insights easily.
With traditional BI, only those with technical expertise and SQL skills can participate in modeling, querying, and creating visualizations. With embedded analytics, on the other hand, users of all types can leverage their company’s data to reach their goals. For example:
Product and development teams can monetize their data and provide customers with business insights by embedding a third-party solution, saving significant time and resources. Traditionally, this process would be a heavy lift with many infrastructure, compliance, and security considerations.
Data and BI teams can embed specific reports and dashboards directly in the context of relevant business workflows, which encourages data-driven thinking within an organization — and can also reduce the volume of ad hoc requests.
Marketing and public relations teams can leverage first-party research by embedding survey results or research analyses across public web pages or publications.
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