Underutilization and the complexity of managing growing data sprawl have spawned several trends during the last several years. Data-as-a-Service (DaaS) is one such trend which represents an opportunity to improve 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.
Within the corner offices of business heads, data scientists and analysts several questions are being asked:
In the early years most of DaaS initiatives were limited to financial services, telecom, and government sectors. However, in the past 24 months, we have seen a significant increase in adoption in the healthcare, insurance, retail, manufacturing, eCommerce, and media/entertainment sectors. This is because of massive amalgamation of extracting continuous insights from structured and unstructured data, liberation of data restricted and protected within silos to the enterprise level and the express desire to conduct real-time analytics.
Businesses are looking to solve tough data and process integration challenges as they once again begin to invest in new business capabilities. Data as a Service (DaaS) is based on the concept that the fragmented transaction, product, customer data can be provided on demand to the user regardless of geographic or organizational separation of provider and consumer. Additionally, the emergence of PaaS and service-oriented architecture (SOA) has rendered the actual platform on which the data resides also irrelevant.
Data as a Service (DaaS) has many use cases:
Data as a Service (DaaS) brings the notion that data related services can happen in a centralized place – aggregation, quality, cleansing, enriching and offering it to different systems, applications or mobile users, irrespective of where they were. DaaS is a major enabler of the Master Data Management (MDM) concept.
Master Data Management is the Holy Grail in data management. The focus for most businesses is on the single version of the truth or Golden Source “Product”, “Customer”, “Transaction” and “Supplier” data. This is because:
MDM provides the plumbing that enables DaaS solutions. This plumbing allows for:
We find that there is a common process that is appearing within the mid-market and customer customers focused on enabling and MDM strategy. It is the data logistics chain consisting of data acquisition, data stewardship, data aggregation and data servicing.
There is a sudden and dramatic shift in how data is handled in businesses as they are shifting away from a hierarchical, one-dimensional enterprise data warehouse initiative with fixed data sources to a fragmented network. This phenomenon has caused ripple effects throughout the old data logistics network. Data-as-a-Service (DaaS) at its core is addressing this problem of fragmentation soundly enabled by MDM.
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