If the analytics team wrestles with getting access to data, how timely are the insights?
To address the question…Global CIO are shifting their strategy — “need to build data-as-a-service offering for my data” to enable the analytics users in the organization. The more advanced CIOs are asking – “how should I build data science capabilities as a shared foundation service?”
The CIO challenge is not trivial. Successful organizations today operate within application and data eco-systems which extend across front-to-back functions (sales & marketing all the way to fulfillment and service) and well beyond their own boundaries. They must connect digitally to their suppliers, partners, distributors, resellers, regulators and customers. Each of these have their “data fabrics” and applications which were never designed to connect, so with all the data-as-a-service and big data rhetoric, the application development community being asked to “work magic” in bringing them together.
Underutilization and the complexity of managing growing data sprawl is not new. But the urgency to address this is increasing dramatically during the last several years. Data-as-a-Service (DaaS) is seen as a big opportunity in improving IT efficiency and performance through centralization of resources. DaaS strategies have increased dramatically in the last few years with the maturation of technologies such as data virtualization, data integration, MDM, SOA, BPM and Platform-as-a-service.
The questions which are accelerating the Data-as-a-Service (DaaS) trend: How to deliver the right data to the right place at the right time? How to “virtualize” the data often trapped inside applications? How to support changing business requirements (analytics, reporting, and performance management) in spite of ever changing data volumes and complexity.