Data Services

Enterprise data is stored in multiple systems and requires multiple interfaces or mechanisms to interact with them. There are varying channels (branch, Online, call center) and mechanisms (event driven, on demand, batch process) that need to be served as well adding additional challenges to data services. Without an abstract layer for data consumers that insulates them from this complexity the enterprise will end up with a spaghetti of point-to-point integrations between data sources and data consumers.

Such Services Might Include

Data-as-a-service (DaaS) initiatives, which present business users with data that is curated, cleaned, and organized to meet their business needs.

Data services marketplaces, which deliver any type of data, even transactional data, to business and technical users over a unified interface.

Few key challenges to deploy Data Services

Data Needs to be processed in real

While IT is getting burdened with a wide variety of data at high volumes, including data from social media, streaming sources, and the cloud, business users often need data the instant it changes.

The Complexity Of Data Silos

As many different forms of data sources come to life and proliferate, they tend to create their own data silos. The greater the number of silos, the harder it is to gather holistic intelligence for the enterprise.

Costly Physical Data Aggregation

Massive volumes of data from external sources such as social media platforms, the Web, and sensors, need to be stored in expensive infrastructures in order to be integrated with legacy technologies. Data also gets replicated multiple times and often becomes out-of-date.

Data Security, Privacy, and Governance

As organizations make data available to a wider range of users, it becomes of paramount importance to provide effective encryption and proper access controls for personally identifiable information (PII), as well as to ensure that they always deliver the most trustworthy, accurate data.