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With AWS, you can quickly build a highly scalable and secure data platform. However, the success of your cloud initiative will depend upon the ability to deliver interactive data access to your users so that they can ask their questions and get responses at a speed that makes them relevant to the business. Therefore, once you have migrated to the cloud, the next most crucial step is to build a BI environment that enables your business users to access this data in the easiest and most intuitive way.

This article will explore how our Smart OLAP™ technology can help you create a scalable BI environment on AWS where you can analyze as much data as you need with exceptionally high performance without exploding your costs. Let us first understand the technology and then deep dive into how it can benefit you.

Preaggregation. On the cloud. For the cloud.

If you are dealing with massive data workloads or need to solve complex business use cases, performing runtime computations will typically bring in performance issues. Therefore, if you don’t want to compromise on performance, pre-aggregation becomes necessary. The best way to resolve this is to follow the tried-and-tested OLAP approach. However, the problem is that most OLAP solutions are not designed for the cloud, nor can they deal with the scale and complexity of today’s data.

Kyvos, on the other hand, follows a cloud-native approach. Our Smart OLAP™ technology leverages the store and compute capacity of the AWS platform to build massively scalable cubes that pre-aggregate data across multiple dimensions and measures. Advanced algorithms enable aggregations on huge cardinality and massive volumes, containing the combinatorial explosion that happens while dealing with data at this scale. Once built, these cubes are stored in a distributed manner on AWS itself. Users can now query trillions of rows of data across your data warehouse and your data lake and get instant responses.

The elastic nature of the platform makes it easy to scale analytics up and down depending upon needs. You can add capacity to deal with peak loads and then release resources when they are not needed. This ensures optimal utilization of cloud resources and saves costs without impacting performance.

Faster. Instant responses on massive data.

As all heavy-lifting is done in advance, the Kyvos cubes provide instant responses to both warm and cold queries, irrespective of the size of your data or the query complexity. Users can connect to these cubes using their existing BI tools and explore massive datasets seamlessly with exceptionally high performance. This eases transition pains as users can work in their familiar environment. Besides, with no need to write SQL queries or learn programming, dependency on analysts and IT teams is minimized.

Smarter. Intelligent aggregates on the cloud.

In OLAP, query performance depends on how the data is pre-aggregated. Therefore, cube designs are extremely important to achieve the desired performance. Creating these designs is fairly complicated, especially if your data is large and complex. Our machine learning-powered Smart Recommendation Engine brings in the intelligence needed to build smarter aggregates on the cloud. It helps you understand your data and query patterns and provides recommendations on creating optimized designs without the need for technical expertise. Additionally, advanced Quick data modeling capabilities make it easy to convert complex business logic into data models.

Cost-effective. Auto-scaling for optimal resource utilization.

Designed for the cloud, Kyvos makes it easy for you to reduce resource consumption during lean periods and deliver consistent performance during spikes. You can pre-schedule querying resources in response to predictable load changes and optimize your costs. Additionally, our build-once-query-multiple-times approach cuts down query processing costs on the cloud. Once the cubes are built, the resources consumed per query are minimal as queries are served directly from the cube, and you don’t have to go back to the data lake or your data warehouse to process the information. You can scale out to add more users, and the infrastructure can handle high concurrency without degradation in performance or exploding your costs.

If you want to learn more about the solution and how Kyvos transforms analytics on AWS, download our solution brief.

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