How to make your Business Intelligence Tools work on Big Data?
Do you know how easily your organization’s business intelligence can turn into a lost opportunity? Well, it is just a matter of TIME. Intelligence is of value if, and only if it arrives on time.
Imagine you have all the data you need to but cannot use it to make your business decisions simply because your business intelligence tools slow down when the size of your data increases. In fact, this is one of the most common reasons why organizations fail to derive value from their Big Data infrastructures despite the heavy investments.
Why do traditional BI tools fail on Big Data?
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, QlikView, 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. 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 the Big Data platform 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
There are several approaches that have been tried by organizations to resolve this problem. One of the most common method is to pull data out of the 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 on BI tools on Big Data 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 designed specifically for Big Data? That’s not a desirable option for most organizations.
Instead of switching to Big Data BI 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 is by creating a semantic layer between your BI tools and the Big Data platform that enables quick access to Big Data. It uses its innovative Elastic OLAP on Big Data technology to create an Enterprise BI Consumption 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 Big Data platform.
Now, instead of connecting directly to the Big Data platform, business intelligence tools can connect to this layer and get instant response 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. You can work with any BI tool that offers the visualization capabilities you need, without worrying about its ability to deal with Big Data.
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, QlikView, MicroStrategy, Power BI, Excel, or even a custom application, to access Big Data 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, organization can keep adding more data, more users, and get ready to meet the future requirements of their business.
If you want to learn about the technology behind the Kyvos platform that makes your BI tools work on Big data, read our blog:
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.
Watch our webinar recording to learn about our latest offering, Kyvos 5: