Top 10 Must-Have Features and Capabilities for Embedded Analytics Platforms

Julian Alvarado

Sr. Content Marketing Manager, Sigma

In a world where data drives everything from personal goals to business strategy, providing your customers, partners, and employees self-service analytics to data relevant to them is a competitive advantage. Customers and partners crave convenient access to their data and need the ability to explore it to derive insights. Offering them highly-functional embedded analytics and dashboards in the applications and portals you provide to them delivers several benefits to both you and them. Benefits to you include higher customer satisfaction and retention, the ability to monetize your data and create new revenue streams, and differentiation from competitors.

But your success with embedded analytics and dashboards depends on your customers’ ability to easily accomplish what they want to. Let’s look at the essential features to look for in an embedded analytics platform to maximize your ability to experience the benefits available.

What is Embedded Analytics?

Embedded analytics is the embedding of analytics dashboards, visualizations, and data into internal, external, or public applications, portals, or web sites. A robust embedded analytics strategy enables end users, or viewers, to quickly and easily access data and discover insights from it. Users are authenticated through those applications while maintaining data permissions directly from the embedded analytics platform. With the most modern embedded analytics platforms, you can extend these analyses beyond employees to partners and customers. Additionally, embedded analytics offers organizations a way to develop new data products or innovate on existing ones to create and optimize revenue streams.

Challenges to Implementing Embedded Analytics

When implementing an embedded analytics platform, you have a couple of options: build your own or buy an off-the-shelf solution. But there are challenges associated with each of these options.

Embedded dashboards can be a pain to build

Without a platform that allows you to easily generate dashboards that users can drill down into for further detail, building embedded dashboards takes too much time and too many resources to be scalable. Not to mention, manually managing authentication, governance, and security for embedded dashboards isn’t feasible for time strapped teams.

Many embedded analytics platforms are limited

Most analytics platforms that include embedding capabilities just aren’t as robust or as easy to use as they need to be. Many require proprietary coding knowledge that isn’t practical for non-technical business users to learn. Others offer only dashboards that are non-interactive or lack the ability for the viewer to drill into a visualization and get to the underlying data to do deeper analysis.

10 Features to Look for in an Embedded Analytics Solution

To fully benefit from what embedded analytics has to offer, you’ll need specific features in your analytics software. Here’s what to look for in an embedded analytics platform to ensure your application builders can easily use it, and your customers and partners can get value from the resulting analysis.

  1. Unconstrained drill paths. The insights revealed by high-level dashboards almost always trigger additional questions. Why is this pattern showing up? Why is that trend happening? What would happen if we changed this variable? For valuable analysis, end users and viewers must have the ability to drill down into the live data underlying the dashboard to find answers to these questions in a timely manner.
  2. Spreadsheet-like, intuitive interface. To be truly data-driven, end viewers must be able to explore data and find answers quickly, on their own. And they shouldn’t have to learn SQL or a proprietary coding language to do so. A good embedded analytics platform will have an intuitive and familiar user interface, such as a spreadsheet, that’s simple for even non-technical users to engage with.
  3. Row-level detail. With a spreadsheet-based interface, users can dive down into row-level detail using familiar formulas, functions, pivot tables, and so on. Without this level of detail, users will be limited in the value they can get from a high-level dashboard.
  4. Direct connection to the CDW. For most forms of data analytics, the freshness of data impacts the accuracy of the insights derived from it. The analytic platform must have the ability to connect directly with the cloud data warehouse to access and show live data and take advantage of the power of the cloud for fast and scalable ad-hoc data exploration.
  5. SaaS, not on-premises. A SaaS-based embedded analytics solution requires minimal deployment and maintenance resources. There’s no need to procure hardware or deal with configuring, maintaining and backing up software.
  6. Lightweight modeling and configuration. To maximize the creation of embedded analytics by application developers, the embedded platform should be easy for them to use, dashboard development should not require code to build, and the platform should provide light-weight and fast data modeling capabilities. Additionally, analytics should be easy to embed in both private and public websites and applications with a single URL.
  7. Robust access permissions. For privacy and security purposes, an embedded analytics platform should offer granular control over what viewers can see and do, including seeing and exploring only their data. Must-have security features include access permissions, object and row-level security options, and one-time signed URLs.
  8. Authentication options. Another crucial security feature is providing multiple authentication options, including through external applications. Users need to work quickly and adoption will increase as friction is reduced.
  9. Flexible dashboard builder with pre-built content. Dashboards should be customizable and interactive so viewers quickly get the data they need, but they shouldn’t take a lot of time to build. A good embedded analytics solution will offer pre-built or custom themes and layouts, chart types, data tables, colors, and fonts. Additionally, users should have the option to display a full dashboard or just a single visualization or data table in a dashboard.
  10. Multiple filtering options. For efficiency, an embedded analytics solution should also offer filtering capabilities via drop-down menus, input parameters, or visual filtering via a single click on a chart element. It should not take users more than a moment to filter.

Experience the Benefits of Embedded Analytics

Companies are experiencing significant benefits by innovating with embedded analytics dashboards that offer customers, partners, and employees the ability to easily dive deeply into their data to find the answers they’re looking for. But without a strong embedded analytics platform, they struggle to experience these benefits. The features listed here will empower you and your customers and partners to make the most of embedded analytics.

Ready to embrace embedded analytics?