Getting to High Performance Analytics for Enterprise BI
One of the major challenges with enterprise-ready embedded business intelligence and reporting is how to manage performance and scalability without impacting production databases, applications, and budgets. Users need to get right to their data and analyze them in real time rather than waiting around for hours or days. With high performance analytics, you can enable users to get the right data at the right time.
Our recent eBook discusses these challenges at length, and we outline the main highlights below. We encourage you to download and read the entire eBook for the full details.
Powerful Reporting Engine
You shouldn’t be spending thousands of dollars on dedicated servers or software to reach peak performance. Any analytical engine that is fine-tuned for high performance analytics should be able to access millions of rows of data for thousands of concurrent users without choking.
Visualizations tool that dynamically shape queries on-the-fly based on the context allow for the best performance. This is due to not accessing all of the data in the query, but rather retrieving only the data that is needed by the visualizations.
For those that need true power and scalability, clustering is the key. However, clustered systems need to provide the power to combine sets of physical or virtual machines into a cluster of nodes. Adding and removing nodes to achieve scalability should be transparent without requiring restarts, going offline or impacting users.
There should be no single points of failure in the system. If any server node crashes or goes offline, another server nodes needs to dynamically take over and fulfill requests without any manual intervention.
Monitoring and Management
An enterprise-class BI and analytics platform should provide browser-based monitoring and alerting so administrators can be notified if server or process health is failing or not responding. The monitoring tools should allow system-wide visibility into usage by users, queries, or reports. Management tools should display running processes and allow administrators to add or remove server nodes as required for increased performance and more efficient use of compute resources.
How Does High Performance Analytics Work?
High performance analytics works in a diverse array of ways depending on the type of tool and the type of analysis being performed.
In the case of embedded analytics, the core functionality which denotes this form of analytics is its embeddability. And the key functions which must perform as usage scales have to do with not only meeting customer demand but also making sure the administrative tasks necessary to manage a growing user base are available to your development team. This means that high performance embedded analytics relies on the ability to scale both from an architectural perspective as well as an administrative one.
This can work in a number of ways depending on the base application’s architecture. But for the sake of brevity, let’s focus on scale architecture first. As mentioned, an embedded analytics application should have some way of scaling. In the case of JReport, we have independent node-based architecture, meaning there is no single point of failure. It’s flexible enough to meet peak demands by scaling up and down as needed and includes load balancing capabilities to make the most of the servers running at any given time.
The second part of high performance within the context of embedded analytics is the ability to properly administer complex user groups without the administrative process becoming overly tedious. This can mean having lots of security capabilities built in on the backend, as well as resource sharing, and features such as bursting control to deliver a singular report type to multiple user groups easily.
JReport’s Embeddable High Performance Embedded Analytics Tool
JReport’s high performance embedded analytics solution enables development teams to provide the day to day analytics their application’s users require easily and at scale. JReport’s main focus has been on embedding since day one and therefore has been designed for the main purpose of embedding. Its scale architecture allows you to scale up and down as previously mentioned, and it’s advanced administrative capabilities allow you to run a multitenant environment with 1000s, 10000s, and even 100000s of users. Its advanced API set allows you to have a deep integration with your application matching both the UI and business logic your users come to expect.
How JReport Empowers OEM
We’ve talked a fair amount about high performance analytics, and even some about high performance embedded analytics. But why do software vendors choose to embed a third party platform into their software?
There can be several answers to this, but some of the big reasons are that embedding a third-party product has a lower total cost of ownership, brings the analytics capabilities your users want to market quicker than developing in-house, can create a competitive advantage compared to competitors which may only have basic reporting capabilities, helps future proof your application’s analytics, and helps you focus on your core capabilities. All of this means you save time, effort, and capital while maintaining the branding and user experience of your application.
Read the full eBook to understand all 10 points to help you reach the full potential of enterprise analytics.