Our holistic data approach
Learn why a holistic approach to achieving value through data is crucial for businesses and how Cardinal Solutions can help you with data architecture, business intelligence, and analytics.
1 min read
Based on a study by Forbes (2023), data-driven organizations are 23 times more likely to top their competitors in customer acquisition, about 19 times more likely to stay profitable and nearly seven times more likely to retain customers. Nevertheless, numerous organizations hold the belief that the data insights are propelled by state-of-the-art business intelligence (BI) and analytics tools. While analytics and BI tools enable the creation of aesthetically pleasing dashboards and visualizations, BI tools solely present and visualize the data that an organization possesses. When an organization stores multiple versions of data throughout its infrastructure, a significant portion of its time will be devoted to reconciling the data, rather than utilizing the data to obtain a competitive advantage. In the realm of business intelligence and analytics, the phrase "garbage in, garbage out" is frequently utilized to express this.
Organizational executives frequently need to recognize that establishing a data-driven enterprise does not require the 'BI' silver bullet. Cardinal Solutions adopts a methodology wherein customer engagements commence with assessments of data maturity, resource expertise, and technology stack. The results of the evaluation are subsequently incorporated into a personalized project strategy that outlines a progressive methodology for attaining the goals for the organization. We collaborate with our clients on data roadmaps, data strategy, data and analytics solutions, governance models, and skill gap assessment and training as part of our multifaceted approach. We are committed to delivering value to our clients through our knowledge and dedication. Moreover, we have years of experience assisting our partners in their transition to becoming data-driven enterprises and spearheading data-driven transformations.
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