Data-as-a-Service - Making Reliable Data Consumable

Data-as-a-Service (DaaS) brings together the technologies necessary to retrieve data from heterogeneous sources such as transactional databases, data warehouses, enterprise resource planning (ERP) systems, and customer relationship management (CRM) solutions.

Part of the DaaS methodology is to deliver relevant data in a timely and secure manner through either public or private cloud platforms based on open standards. Being able to act upon timely, accurate information is critical to win business in this highly competitive marketplace. IT must walk a fine line between ensuring governance and securitizing data without handcuffing the Business users with unnecessary bureaucracy that slows them down. If DaaS can work, it’s the perfect answer.

DaaS means agile, fast, low cost access to valuable, reliable data. This sounds relatively simple, so why is it so complicated? Well, for DaaS to deliver on its promise, many challenges need to be overcome, such as:

  • Standardizing ingestion to support multiple sources of data from structured to unstructured, real-time and batch.
  • Integrating data from multiple systems of record in various file formats, which is essential to capture "the single source of truth".
  • Defining a plan for metadata management and lineage to ensure data is discoverable, reliable and searchable.
  • Defining common data definitions and hierarchies in a common data catalogue so that data can be captured, collected and revealed.
  • Establishing an enterprise domain model that will provide access to data that is secure and governed; protecting not only the data assets but the reputation of the organization that is maintaining this data.

Translating the vision of DaaS into a reality requires the collaboration of processes, applications and technologies that collect, clean and prepare enterprise data from multiple sources. This will ultimately help achieve the goal of low-cost analysis and critical, timely decisions based on meaningful, trust-worthy data.

In addition to data ingestion, another key component of DaaS is data transformation, which is the process of converting data from one format to another. This is essential to allow Business users to explore and access multiple sources of data (from various file formats) in terms that they understand.  Without extensive knowledge of the underlying data model and data definitions, Business users can query using language that they understand, thus making reliable data consumable.

If your company is interested in making data more reliable, and consumable, Next Pathway can help. Please feel free to contact us for more information.