Introducing Sisense Release Q3 2019
Just over two years ago, our CEO, Amir Orad, delivered an internal announcement that Sisense had made the strategic decision to completely re-architect our platform to a cloud-native architecture that would deploy on any cloud — private or vendor-managed — using Windows or Linux.
It was clear during his announcement that this would require significant investment and wouldn’t be a quick hack of porting code to Linux. Instead, it would be purpose-built from the ground up in order to be future proof. It would utilize a modern containerized microservices architecture and incorporate best-of-breed open-source technologies such as Linux, Kubernetes, and Docker for integrated delivery in the application lifecycle.
And while cloud-native architecture is paramount to drive the future of analytic apps, AI is also a critical component in order to reduce manual, repetitive steps during data prep and give business users the ability to gain new insights from which they can take action. Combined, Amir said, we can make it possible to go beyond the dashboard and create AI-powered analytic apps where users can take immediate action on their insights.
Today, I’m excited to announce that the Sisense Release Q3 2019 not only debuts our cloud-native architecture but also major achievements along our AI roadmap.
Our re-architected cloud-native architecture is purpose-built from the ground up with a foundation based on a modern containerized microservices architecture that incorporates best-of-breed open-source technologies such as Linux, Kubernetes, and Docker for integrated delivery in your application lifecycle.
Here are some of the benefits that our cloud-native architecture provides to modern data teams:
- Lower TCO with fewer and flexible hardware requirements.
- Built-in load-balancing and on-demand auto-scaling of data instances, with the option of fine-grained configuration and control.
- Fully leveraged shared storage, distributed architecture, and built-in redundancy.
- Deployment of multiple siloed tenants on the same server or cluster to save on hardware and resources.
If you are a customer, just one of the many performance enhancements you will also come to love is our support of parallel table and high multiple concurrent ElastiCube builds running at the same time. Overall build performance is 2X faster and build and data capacity is 5X greater than Windows (depending on data source and structure, of course!). In addition, you will see a significant improvement in dashboard performance.
Cloud-Native Sisense also represents the first steps of integrating the Sisense and Periscope Data Platforms. The common microservices architecture both companies share allows our respective R&D teams to more quickly integrate each product into an enterprise, end-to-end data team platform. Much has been accomplished already since our merger in May and more will be shared on our progress next quarter.
Our cloud-native architecture is supported alongside our existing Windows-based offerings and is currently in gradual release.
Currently, data-driven decision making is based on the business users’ ability to successfully filter, slice, and dice known KPIs they want to track and improve upon. The inability, however, to get new insights from known KPIs and uncover new relationships from data is one of the many reasons we believe the adoption of analytics has not gained further momentum.
AI Exploration automatically generates visualizations and deeper insights that anticipate the next question from a business user without the involvement of a business analyst. It leverages AI to instantaneously deliver new answers to the questions most users have in mind when looking at their data in order to facilitate new and deeper insights directly within the context of a dashboard.
AI Exploration Paths delivers an intuitive path for business users who are not necessarily data-driven so that they can instantly gain a comprehensive understanding of all aspects of a KPI broken out into multiple perspectives. As an added benefit, dashboard designers can now focus on the most important business drivers and end-users can deepen their understanding of their business as they are guided to answers to questions they didn’t even know they had.
Release Q3 2019 Summary
There is much more to the Sisense Release Q3 2019, including:
- Group Similar corrects data discrepancies found inside of a single column using AI
- Expanded library of certified data connectors
- Greater enterprise scalability with end-user report management
- Live data model support for PostrgreSQL, MySQL, and Oracle
- Live Table Queries that will be available soon in Q3 2019
The journey that we have embarked on over the past two years has laid a new and stronger foundation for innovation, including how you can start to design robust embedded, AI analytic apps.