Kyligence Brings Simplification to Data Processes for Analytics

Data platforms are designed to manage and analyze big data, enabling organizations to leverage their data to operate with greater efficiency across on-premises, hybrid and multi-cloud environments. Our Analytics and Data Benchmark Research finds that while 58% are using big data in their analytics processes, less than one quarter (23%) are satisfied with their technology’s support for big data. Looking at the statistics, it is safe to say that organizations have been slow to adopt modern technology that was built to help manage and organize big data so that it can be used for analysis. With advancements in technology, organizations are now able to provide a platform that makes it easier for line of business workers to access and analyze big data.

One of those platforms is Kyligence Cloud 4.5, a self-tuning analytics platform that powers interactive data applications, dashboards, ad-hoc analytics and real-time streaming data. It was designed to address the problem of data failure between different application systems, disorganized data and data management processes amongst the growing variety of KPIs. Kyligence Cloud 4.5 comes with a variety of new enhancements: Smart Tiered Storage is designed to use different types of storage based on the frequency with which data is accessed; an artificial intelligence (AI)-augmented analytics engine will identify the most valuable data from SQL history, analyst behavior, data profiles, and runtime metrics automatically; real-time capabilities provide data monitoring and a hybrid analysis of historical and current data. The platform also has the ability to sync the Kyligence semantic layer to several major BI tools to reduce confusion and human error by providing data teams with consistent definitions and business views of data. The software is built as a stand-alone offering. It works in conjunction with many mainstream BI products on the market to help data teams, analysts and business users transition interactive big data analytics to the cloud. It is available through Microsoft Azure and Amazon AWS. Support for Google Cloud Platform is scheduled to be provided soon.

The broader value of using cloud-based analytics is speed, agility and cost savings. Cloud-based applications provide flexible scaling and the ability to request resources on demand. This alleviates the need to reconfigure systems as requirements change. Complete monitoring capabilities make it convenient to understand system usage in order to control costs and maintain service levels. Additional benefits of using a single platform include accelerated analytical queries and ad-hoc analysis to respond faster to opportunities and threats. With the increase in availability of data, advances in modern technology are helping data teams dismantle the challenge and complexities of processing analytics. Decision makers can now rely on data teams to provide insights quickly. Kyligence offers a hybrid analytics model that can analyze both historical data and real-time insights. Decision makers can keep track of changes and potential improvement over time, plus the forecast for future performance.

A cloud-based system that unifies an organizations’ data and analytics can help streamline analytics and significantly improve workflows across all departments. We assert that through 2025, 7 in ten organizations will migrate on-premises workloads to cloud data platforms, shifting focus to solving business needs rather than maintaining systems. In the past, before this type of technology was available, data teams were so busy collecting, organizing and maintaining data that they simply did not have the time to play a strategic role in the business.

Kyligence should continue to expand upon its tiered storage model with data virtualization capabilities to access data in place as organizations will continue to face more and more restrictions on where data is stored. Organizations in the market for a data platform should consider a further investigation of Kyligence. There is no reason business professionals should be spending hours digesting data. Make data work for the organization, so that it can start reaping the benefits.