Embedded analytics integrates data insights within the context of business applications, providing visualizations directly into workflows. Although some applications include summary visualizations of data, embedded analytics applications offer additional analytics capabilities and historical data, making it easy to see and understand data via dashboards, charts, and reports.
Benefits of Embedded Analytics
Embedded analytics allows you to provide data to your team and customers within familiar workflows. Embedding analytics into your product delivers benefits, including:
- Live Data: Reports aren’t static but dynamic, based on live data.
- Interactive Reporting: offers more granular views of data and more flexibility over how data is presented versus predetermined data views.
- Contextual Insights: Unlike traditional business intelligence (BI) in which reports and dashboards are accessible only within BI-specific tools, embedded analytics provides insights inside transactional business applications.
- Data-Driven Decisions: The shared nature of embedded analytics allows your marketing, sales, finance, and other teams to access real-time data and derive impactful, actionable insights.
- Increased Productivity: Teams with embedded analytics can access and shape data to suit their needs without relying on BI expertise, expediting their analyses and allowing them to focus on their areas of focus.
- Competitive Advantage: Natively embedding analytics can differentiate your applications from those of competitors reliant on semi-regular data dumps and offline reports.
- Embedded Reporting: Embedded reporting added to your existing business applications allows for the efficient presentation of data. By embedding, you and your employees can extract important insight from data within the applications you regularly use at the moment of relevance.
Uses for Embedded Analytics
- Third-party applications: Embedding analytics directly into the applications your teams use allows team members to access and engage with dashboards, charts, and reports within their workflows — so they don’t need to switch between separate systems.
- Internal web portals: By embedding dashboards, charts, and reports into your organization’s intranet, the entire company can access teams’ and the overall organization’s data, giving everyone opportunities to interpret and draw insights in context.
- Public website pages: With a bit of HTML, you can share embedded analytics in dashboards, charts, and reports based on your data with your current and prospective customers, providing useful, engaging, and up-to-date information they’ll appreciate.
Embedded Analytics versus Business Intelligence
BI aggregates data from multiple sources, prepares the data for analysis, and provides reporting and analysis on that data separately from typical workflows. Typically, BI is handled by specially trained data professionals and provides high-level data views across teams or for an entire organization.
Embedded analytics, on the other hand, integrates your data into your own applications, providing real-time context and analytics when and where it is most useful. It can be specific to individual teams and systems, giving everyone the targeted information they need to make informed decisions
Ultimately, embedded analytics empowers your teams and customers to access data-driven insights within the context of the applications they use every day, keeping them focused instead of dependent and distracted by separate BI applications.
Snowflake and Embedded Analytics
Developers of data-intensive applications differentiate themselves from the competition by offering embedded analytics applications to reach new audiences within their customer base. Embedded analytics applications provide users deep insights within the context of their current activity without having to rely on centralized BI teams to run reports on stale data. Snowflake’s cloud data platform offers key advantages for developers building embedded analytics, including virtually unlimited concurrency, fast and consistent performance, margin protection, native support for semi-structured data, and near-zero administration. Developers can leverage embeddable BI tools from Snowflake partners and open source libraries, so they don’t have to build analytics applications from scratch.
The Snowflake platform is the ideal data warehouse and analytic engine to power next-generation data applications. Snowflake’s cloud data warehouse not only relieves data warehouse managers from the burden of deploying and managing infrastructure but can also scale painlessly as usage or as concurrency grows.