Data services are useful when organizations use a heterogeneous storage infrastructure, for example, when using Data as a Service (DaaS). In these situations data can be stored in many places and consumers of the data need ways to find and analyze the information they need without concern for the specific location of that data.
When combined with data virtualization, data services provide an abstraction layer from the details of stored data. Data virtualization provides the storage platform while data services do the programmatic work of retrieving data from the platform. Data services automate the work of locating heterogeneously-stored data and provide developers and data analysts with simple programmatic tools to find and extract the data they need with little effort. In an application, data services act as a middleware, independently finding and delivering data the application requests. Data services are essentially web services for data.
Master Data Management (MDM) is the key strategy of Winning Corporations as it holds the data about your of customers, vendors, employees and products.Read More
In the field of data management, data classification as a part of Information Lifecycle Management (ILM) process can be defined as a tool for categorization of data to enable / help organization.Read More
The rapid growth of e-commerce has increased the integration of multiple databases for which data cleansing is the must to ensure that the data in each database is standard, consistent and accurate.Read More
Data enrichment is a value adding process, where external data from multiple sources is added to the existing data set to enhance the quality.Read More
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