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As cloud adoption increases, enterprises tap into the power of scalable and elastic OLAP on the cloud to build a business intelligence platform that can deliver insights at a speed that matches their growing analytical needs.

Increased competition and uncertain market conditions necessitate that enterprises build intelligent environments that can nurture smart decisions and brisk innovations. Every opportunity needs to be exploited, and new ones need to be created, all of this at a speed faster than ever before. In the current global environment, data is the most important tool that can help in achieving this objective. It can reveal real-world trends and waiting-to-be-discovered opportunities that lay the foundation of intelligent business.

To handle the exploding scope and volume of data, most organizations are turning towards cloud computing. Many enterprises already have their data on the cloud, at least a significant part of it. According to IDC, public cloud spending will grow from $229 billion in 2019 to nearly $500 billion in 2023, with a five-year compound annual growth rate (CAGR) of 22.3%.

However, moving to the cloud can solve business problems if and only if organizations can derive value from their data.

OLAP and The Need for Interactivity

As data volumes increase, interactive analysis of massive data on the cloud becomes crucial for the success of any cloud initiative. Enterprises also need the ability to create and process complex data models so that users can get accurate answers to their business questions. However, connecting a traditional BI and analytical tool directly to a cloud platform results in poor performance.

To achieve interactive analysis, many enterprises are tapping into the power of the need for OLAP on the cloud. OLAP uses a multidimensional approach to organize and analyze data, that enables the representation of complex data models. Since data is pre-aggregated, query responses are much faster than any other relational data model. Once the cubes are created, business users can query their data and create reports using the traditional BI tools they are comfortable using.

Challenges of OLAP on the Cloud

Though OLAP is a proven technology that enables high-speed multidimensional analytics, achieving it at a massive scale still remains a challenge. When traditional OLAP technologies are brought into the world of big data on the cloud, they are unable to perform as they cannot deal with the massive increase in the data volume, the explosion of cardinality and dimensions.

Aggregations for selective queries or in-memory OLAP solutions cannot meet the requirements of a modern-day business. Though they are designed to deliver performance for known or warm queries, they fail on response times when new questions are asked. Besides, there are scalability and performance limitations on the amount of data that can be processed.

Further, many OLAP solutions are unable to handle complex data scenarios due to restrictions on the underlying multidimensional data models that they support. The inability to migrate existing OLAP models to the cloud also acts as a deterrent for organizations looking for OLAP on the cloud.

We will now examine how next-generation OLAP technology, designed for the cloud, leverages the flexibility and scalability of the cloud environment to overcome these challenges and build a high-performing cloud business intelligence platform that breaks all performance barriers.

Smart OLAP Powered by Next-Generation Technology

The next-generation Smart OLAP technology developed by Kyvos enables users to analyze massive volumes of data on the cloud instantly and interactively, without limitations of speed, scale, or complexity. By combining the benefits of scalable cloud platforms with the ease of use of OLAP-based analytics, Kyvos makes it possible to achieve OLAP on the cloud at a scale that was impossible before.

Advanced algorithms enable aggregations on huge amounts of data by containing the combinatorial explosion that happens with OLAP at this scale. Kyvos leverages the compute capacity of the cloud to create multi-dimensional cubes and then stores them on the cloud itself, taking advantage of its flexible storage. The Kyvos cubes are fully pre-aggregated and materialized for speed. As all the combinations are processed in advance, they provide instant responses to queries across hundreds of dimensions and measures.

Once the cubes are built, existing tools can connect to the OLAP layer with sub-second response times, enabling the users to get interactive insights from their cloud data.

They can ask any question from their cloud data and get answers in seconds. OLAP on the cloud allows them to slice and dice, roll up and drill down, delve deep into any transaction, and pull out any reports using their favorite BI tools. These cubes eliminate query latency and bringing in the much-needed performance. It creates the necessary environment for thinking, exploring, and innovating.

Ease of Migration to the Cloud

Moving to the cloud becomes easy as Kyvos supports the same structure as traditional data warehouses but at a much larger scale. There is no need to manipulate data or change your complex models. You can add hierarchies and calculated measures in the semantic layer and define different kinds of hierarchies, such as multiple hierarchies, alternate hierarchy, parent-child hierarchy, different ways of aggregating, custom roll-up, and more.

Kyvos fits in your cloud environment without any disruption to the existing data, security, and analytical setups. Your data continues to live on the cloud, and your users are not affected as they can use their existing BI tools.

If you want to learn more about the Kyvos OLAP on the cloud solution, watch the recording of our webinar “How to Achieve Self-Service BI on Big Data in the Cloud at Massive Scale.” In this webinar, our speakers, Andrew Brust, Analyst – Gigaom Research, and Ajay Anand, Chief Product Officer – Kyvos, talk about how you can transform your business with instant BI on big data on the cloud.

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