Transform Your Organization
With Reporting You Can Trust
Enterprise Scale Your Analytics
No organization in this world can afford not to use data. It’s a fact, data-driven organizations are 19 times1 more likely to be profitable than other organizations. It explains why investments in Data and BI have been and remain the most important investment in IT for decades now.
For years organizations invested in Analytics and progressively invested in DataOps, especially since the rise of Self Service. This has helped improve overall data quality. But data is useless if your collaborators can not trust it when it comes to making decisions, ie when using reports and dashboards. Ensure the reliability of data through data analytics components, restore trust, and scale the use of analytics throughout your organization with Wiiisdom.
1 https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights
“4/5 CEOs do not trust data upon which they base their decisions”
(Trusted Analytics Matters to CEOs – KPMG – 2019)
If you want your organization to be data-driven, you need to prove the reliability of data and analytics. Testing your reports and dashboard outputs is a critical step forward that will help you establish a good methodology, continuously monitor your reports, and reassure the business users.
Barriers to adoption
of BI/analytics
Source: “Strategies for Driving Adotpion and Value with BI and Analytics”, BARC, Eckerson Group, 2022.
The adoption rate of BI and Analytics in organizations is worrying low: 25% according to this recent study. The lack of quality data that people trust is the #2 barrier to adoption.
Ensuring the quality of data is a sine qua non-step for restoring that trust, and contributing to the adoption of Analytics at scale.
Ease of use and performance are two other important factors that prevent your organization from truly being data-driven.
The performance of your BI and Analytics system can be impacted at any time, by many different factors. Without testing their performance and usability, you are opening the doors to a bad user experience.
The Last Mile Problem
Data Quality alone is not enough. You need Data Analytics Quality.
Most organizations still don’t realize the importance of testing the data once in the analytics layers.
Even if your data is certified in your data warehouse, it doesn’t automatically mean that once it lives in the analytics layer it will be without issues. The analytics data is often merged with other data sources, transformed, filtered, and more.
Certify the data in its last mile, the same way you do with raw data.
