No matter what self-service BI solution you choose, preparing your database to optimize reporting speed is a key to success.
In IT, the last thing developers think about when launching an application is its reporting. But when it comes to delivering modern embedded business intelligence through visualizations and self-service capabilities, often the last thing IT thinks about is whether their database can handle reporting. Regardless of the analytics solution, ensuring your data can be rapidly retrieved is a key to success.
Self-service analytics in real time is a common goal of modern BI. If the analytics solution cannot support end-user expectations for performance, or if the reporting infrastructure requires too much IT support, then its economics might not make sense. Before implementing self-service reporting, you should determine whether your current database system can handle the increased load. If not, you’ll need to invest in other hardware or software.
Learn how to Prepare Your Database for Self-Service Analytics.
Organizations planning to deliver improved self-service analytics to users should consider these database and data-related issues. These general guidelines can help you frame your requirements for a business intelligence project. More than 1,500 successful implementations of the Izenda platform have proven their value for our clients.
But every database is unique. Get context from the database administrator to help determine the best path to prepare your data for reporting.
The issues we recommend you consider when making a decision on a database include:
What do your end users need?
Do they need ad hoc reports? Dashboards containing KPIs? Visualizations? Robust, visualization-heavy dashboards, for example, will generate heavier demand on an RDBMS than basic ad hoc reports.
Do you have all the data you need for reporting?
Audit your data. What data sources do users need? Do you need to report against more than one database? Do you need to address data quality issues before users try to do self-service reporting?
Performance expectations
How quickly do customers need their queries returned? How live does the data need to be? Most reporting and BI solutions allow for lag time. But end users may expect instant, real-time results when they do a query.
What is the scale of your project?
How many clients, how many users, how many roles? Given the scale and scope of the project, infrastructure changes may move from “nice to have” to “necessary.”
Are there legacy reporting considerations?
If you are migrating from a legacy reporting platform like Crystal or SSRS, what existing reports do you need to deliver? How much reporting will you need to run in parallel? For how long post-launch will you need to generate legacy reports for end users?
Read more about the issues surrounding Preparing Your Database for Self-Service Analytics in our latest white paper.
Follow Izenda on social media for the latest on technology and business intelligence:
