Companies with the goal of increasing their efficiency in making fact-based decisions understand the importance of business intelligence. It uncovers important patterns and trends within business data, delivering a deep view of organizational processes, consumer behavior, and internal productivity. That insight is vital to optimizing decision-making and performance.

The quality and location of data and skills required to use BI tools effectively are factors in helping customers address these key challenges:

• Data quality: Having quality data is critical to achieving good business analytics. Bad data results in bad business intelligence. Data quality is a challenge for two primary reasons. One, data is outdated, which occurs easily in a large, complex organization. Two, companies aren’t taking the time to practice good data hygiene. To maintain quality data, companies need to take steps to clean and normalize the data regularly.
• Critical data buried in different systems: When data is in different systems and inaccessible to other systems, because the software may not be compatible or the business unit tightly controls user permissions, it’s called siloed data. The problem with this is that when critical data is siloed, it’s locked away and you only get a partial picture of your overall data, so your business intelligence is incomplete. Working with a good ETL tool (extract, transform, load) can help you bring data from different systems together to make it available for analysis.
• Lack of expertise: Using business intelligence tools requires significant expertise. This means that only a few key people in your organization have the skills to use the business intelligence tools effectively, which in turn can create a bottleneck.