Technically elegant, highly usable applications that give users the answers they need, when they need them, are a must for making data intelligence pervasive and driving high-impact outcomes. However, these applications will only be as good as the data that powers them. It won’t matter how elegant or responsive an analytics system is—if the data isn’t clean or reliable—users won’t trust it, and they won’t use it. Therefore, it’s critical to eliminate data silos, secure and govern your data, and demand accountability for data governance (DG), throughout the enterprise. With a solid DG foundation to support your analytics efforts, you can embed intelligence in your organization to drive information yield; glean better insights; and enable faster, more accurate decision-making.
Fragmentation in systems and data hobbles efforts at enterprise-wide analysis and creates an environment where there is no single version of the truth about organizational data. The remedy for this is data consolidation to get rid of organizational silos. To be successful at using analytics, you must have a common (or federated) data store with clean, standardized data that provides the same answers to the same questions. That is, it creates borderless data.
More and more, companies are turning to the cloud (see Chapter 3 for ...