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Imagine you have all the data you need to but cannot use it to make your business decisions just because your business intelligence tools slow down when the size of your data increases. This is one of the most common reasons why organizations fail to derive value from their Big Data infrastructures in the cloud as well as on-premise despite the heavy investments.

Why do traditional BI tools fail on Big Data in the cloud?

Business Intelligence tools are designed to enable data visualization in ways that make it easy for users to interpret data and get insights into their business. Popular BI tools such as Tableau, MicroStrategy, Power BI, and more, have advanced visualization capabilities that allow users to explore their data visually, get insights from it, and then ask further questions based on those insights. Their goal is to simplify analysis for business users by letting them interact with their data visually, using drag-and-drop operations, without the need to write complex code or SQL queries.

Most traditional business intelligence tools work well with smaller data sets but face challenges while analyzing Big Data on the cloud. Since these tools were built to work on relational technologies, it is unfair to expect them to deal with massive volumes of data. Direct queries from the BI tools to Big Data in the cloud sometimes takes minutes and hours, instead of seconds. This leads to significant performance issues as they connect to the Big Data platform to fetch results for every interactive query.

As a result, visualizations and dashboards take a long time to refresh, and interactivity suffers. Business users get frustrated as they are unable to get answers to their business questions when they need them.

Few Approaches that fell short

Several approaches have been tried by organizations to resolve this problem. One of the most common methods is to pull data out of the Cloud Big Data platform into an in-memory solution or an external data mart, and then make the BI tools work on it. However, there are several scalability and performance limitations on the amount of data that can be processed this way. Besides this, it is resource-heavy and introduces latency as the data is not live.

In addition, several enhancements have been introduced to improve the performance of BI tools on Big Data in the cloud such as advanced indexing, query optimization, and more, but none of these methods can scale up to match the speed at which the size of the data is expected to grow in future.

Does this mean you need new Business Intelligence tools that are explicitly designed to work on Cloud Big Data? That’s not a desirable option for most organizations looking to reduce operational costs without compromising on speed and accuracy of their data analytics.

Instead of switching tools, what you need is an environment where your existing BI tools can create the visualization that your business users need, irrespective of the size and complexity of the underlying data.

Building a Universal Semantic Layer

Kyvos makes this possible by creating a semantic layer between your BI tools and Cloud Big Data that enables quick access to Big Data. It uses its innovative Elastic OLAP on Big Data technology to create an Enterprise BI Acceleration Layer on your Big Data platform, both in the cloud as well as on-premise environments. This layer pre-processes massive volumes of data into large-sized, multi-dimensional OLAP cubes using the compute and store capacity of the Cloud and leverages its elasticity to optimize resource utilization.

Building a semantic layer helps keep your metadata in a single place and define a single source of truth for all users in your organization. Imagine a huge volume of data landing in your data lake or warehouse. It can be interpreted differently by different users, resulting in inconsistencies and poor reporting. A cloud semantic layer ensures a unified data model for higher speed and performance in these use cases. It offers a consistent view of facts irrespective of data complexity or size.
With our advanced technology, there’s no need to use BI tools to define complex business logic in your big data infrastructures. Our Smart Semantic Layer abstracts data for a comprehensive view.

Instead of connecting directly to the Big Data platform in the Cloud, business intelligence tools can connect to this layer and get instant responses to all queries. This improves the performance of the BI tools in ways that were not possible before and allows you to conduct instant, interactive analysis on your Big Data in the Cloud. You can work with any BI tool that offers the visualization capabilities you need.

Turn your favorite tool into a Big Data BI Tool

The Kyvos platform transforms your existing tool into a Big Data BI tool and makes it work on Big Data with unmatched performance and unlimited scalability. Your business users can use any BI tool such as Tableau, MicroStrategy, Power BI, Excel, or even a custom application, to access Big Data in the Cloud without being concerned about the size of the data or the underlying Big Data infrastructure.

The key advantage of this approach is that it allows business users to analyze Big Data seamlessly and transparently, without disrupting their day-to-day activities. They can continue to use their existing BI tools or any other tool that they are comfortable using. Using the BI Consumption layer, they can even access unprocessed data on which OLAP cubes have not been created.

With Kyvos, users can ask any question from their data and get answers in seconds. They can slice and dice, roll up and drill down, and interact with Big Data in ways that were not possible before. On the other hand, the organization can keep adding more data, and more users, and get ready to meet the future requirements of their business.

More Resources

If you want to learn about the technology behind the Kyvos platform that makes your BI tools work on Big data, read our blog:

Understanding OLAP on Big Data: Why do you need it?

Download our solution briefs to see how Kyvos improves the performance of Tableau, Excel, and MicroStrategy.

You can also watch our video where our customer, Walgreens, describes how they use Kyvos with Tableau to analyze two years of historical data instantly and interactively to get deeper insights into their supply chain.

How Walgreens transformed Supply Chain Management with Kyvos, Tableau, and Big Data?

Watch our webinar recording to learn about our latest offering, Kyvos 5:

Introducing Kyvos Version 5: Instant BI on Big Data with Elastic OLAP

FAQs

Which are the BI tools that Kyvos can be connected with?

Kyvos can work with BI tools such as Tableau, MicroStrategy, Power BI, Excel, Looker, SSRS, or even a custom application, to access big data in the cloud. Our proprietary visualization tool, Kyvos Viz, offers an intuitive drag-and-drop interface for self-service analysis with an extensive library of charts and an auto-visualization feature.

Can users continue to use their existing BI tools with Kyvos?

Yes, Kyvos creates an environment where your existing BI tools can create the visualization your business users need, irrespective of the size and complexity of the underlying data. Instead of connecting directly to the cloud data warehouses or on-prem systems, BI tools can connect to the Kyvos’ Semantic layer and get instant responses to all queries.

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