Sisense excels in empowering small teams of enterprise users to create insights from complex data. The out-of-the-box application is well suited for contained use cases supporting the data discovery needs of BI analysts.
But it is not designed as “embedded first.”
Simply put, embedding analytics requires a different approach than that of data discovery. Embedded offerings reach more users, must support complex multi-tenant security schemes, and need to put the application’s brand first. So, while Sisense has invested in interesting features – such as Amazon Echo integration – for its standalone solution, those investments aren’t paid off in their embedded product. The result is a less capable, more expensive, and harder to scale retrofit of their data discovery offering.
For companies that need robust customization options, solid product support, and a solution that scales to handle complex capabilities and security needs over the long term, they may have to consider Sisense alternatives. Consider these three Sisense limitations.
1. Not designed to scale
As is the case with most data discovery tools, Sisense was designed for small groups of users, resulting in significant hardware requirements for any company with a larger implementation. Sisense’s own documentation references user groups of “tens,” revealing a product that’s ill-equipped to cope with the large user groups most embedded solutions serve.
The result is that large deployments experience a reduction in database performance. To return to acceptable performance, Sisense requires much more hardware and expertise, which is expensive to build, deploy, and maintain.
Additionally, Sisense’s per-user pricing structure is designed with small user groups in mind. As the number of users increases along with your business and your expanding reliance on the tool, the product fails to afford the financial economies of scale necessary to support hundreds or thousands of users. Many software companies we speak to tell us this is a non-starter.
2. Security is difficult (if not impossible) to implement
For embedded analytics, security must support complex requirements and often needs to operate in a multi-tenant environment. Almost all applications have restricted access based on the roles and rights of the users accessing the system, which means the ability to restrict access in a granular way is crucial.
Unfortunately, with Sisense, setting up security is time consuming and will take efforts from your best developers. Row- and column-level security require extensive IT resources to build into the semantic layer because the product was not designed for embedding. IT admins must define the roles and rights on a per-report basis for every user individually, one at a time. This approach is simply not scalable.
Replicating those processes for larger user groups in which every team needs a different level of access will take time. Developers will also struggle to implement single sign-on, which demands additional time and use of SDKs to implement because the product was not developed for embedding.
3. Limited Customization & Embedded Capabilities
The Sisense experience is designed for small teams of analysts. But for companies embedding analytics, white-labeling is a requirement. Without the ability to completely customize the look, feel, and branding of every aspect in your application, your embedded analytics solution will not be differentiated.
For embedded analytics to be useful, it must do two things: First, support real-time insights so your users are always using the latest data. Real-time data integration relies on features such as drill-down, drill-through, and linking. To create drill-down and linking capabilities with Sisense, you must create hierarchies of the data for each “ElastiCube” you create. You’ll also have to sacrifice linking to other reports or external applications/URLs.
Second, embedded analytics must support more advanced capabilities such as database write-back. Sisense struggles to support the custom experiences and workflow integration that modern analytics users are demanding. Instead, it has invested in data discovery capabilities such as Philips Hue Lighting integration—which, while flashy (pun intended), does not help software companies differentiate their applications.
Sisense Alternatives: Consider Logi Analytics Instead
If you require customized embedded analytics and you’re expecting your business to grow, expand, and change over time, consider partnering with an analytics development platform that can adapt and grow with you while supporting a breadth of developer-grade analytics requirements. Logi Analytics has been focused on embedded analytics for over a decade, helping over 1,800 application teams create more valuable software products, engage their users, and differentiate their applications. Logi has been ranked #1 in embedded analytics by Dresner Advisory Services and recognized by Gartner for our strengths in embedded.
Logi’s dedication to embedded analytics shows in our unique abilities to:
- Connect to Any Data Source: Logi works with the data you have, wherever you have it. No need to invest in proprietary data layers or recreate what you have.
- Embed Sophisticated, Customized Capabilities Faster: We let our customers combine pre-built elements and customize every aspect of their application’s look, feel, and functionality to create one-of-a-kind experiences.
- Support Adaptive Security: Logi integrates with your existing security framework—instantly enabling single sign-on, multi-tenant deployments, and control over user access down to the row and column level.