The business end users of today’s software applications need a specific set of numbers answering a specific question to make their analysis of the company’s data. They don’t want to go through enormous sets of data. Instead, we need to give them the tools in our web-based analytics solutions to manage their data and queries on it so that they get the instant results they expect.
End Users Want Simple Answers to Queries
End users not only don’t know the company’s underlying data model – they don’t want to know it, either. They usually don’t understand the constraints of queries and expect real-time results. So they’ll need a solution with filter controls and ranges, auto complete, contains, selector types and check boxes. That means a safe, preconfigured environment. We can include this in a BI and analytics application as a pre-built function or an expression. Or it could be built within the database, which is much more likely.
Users will get to iteratively explore the data, something that’s essential to discover the true story of the data. They may need one-off changes, as they don’t understand what they need from reporting until they see it. That’s where a self-service BI and analytics solution makes sense for the end user and keeps IT from becoming a report writing department instead of software development experts.
Users Need Analytics Personalized to Their Roles
Users will need to get used to working with smaller sets of data on a screen due to the limits of a web-based application’s ability – and because of the limits needed for this preconfigured environment. Web browsers cannot display massive amounts of data in a page, nor can they process beyond a certain number of rows. Remember that tools rendering in HTML have different limitations than Excel files or pdfs. In these cases, users may input a dataset into another process.
On a web platform, users need succinct, personalized results relevant to their role and the workflow in which they are engaged. That’s the “right amount of analytics at the right time.”
This “right amount of analytics” means that reports should have a specific purpose. It’s best to use charts and drill downs whenever possible.
A mobile world creates more limitations for web-based analytics – or really any type of application. Limitations of the laptop, tablet or smartphone restrict how much you can render in the browser. Too much can grind everything to a halt. You can see CPU usage spiking as Chrome renders visualizations. We load up all JSON data and then the browser has to handle all the transformations. So the less data to animate, the better for the end user.
A few tips to handle this include:
- Visualizations are best applied to aggregates, not 100,000s of rows.
- Screen resolution: In all cases for mobile, you need to design the application and its embedded analytics to be responsive. So page sizes also need to keep to a minimum for those tablets and smartphones.
- Don’t slice too many pieces of the pie (visualization): For mobile – and even dashboards on a desktop – end users have a small window in which the visualization has to make sense. (Besides, after a certain number of slices the pie chart just makes no sense.)
Izenda Reports Directly Against Leading Database Platforms
Izenda 7 SeriesTM BI and analytics platform inconspicuously integrates into your product, keeping your user experience consistent.
Our platform, purpose-built for embedding, securely reports against databases in real time. At its core is an automated query building engine that generates and executes queries against reporting data sources, without requiring users to understand underlying data models or write SQL.
The platform automatically recognizes existing constraints (primary and foreign key relationships), tables, views, stored procedures, functions, columns and data types for all supported database systems.
Powerful aliasing and categorization options allow you to present your users with an easy to understand, business-relevant set of names and groupings. You’ll be able to optimize the user experience by providing a simple, elegant, intuitive interface for your data model through our UI or API.