Data as a Service

Data as a Service

Data as a Service (DaaS) is our term for serving Data as a utility in the organization: reliable, quality Data with built-in governance, available on demand, and easy to use. 

 

This utility-based model provides Enterprise Data Access for applications, AI/Data science needs, business users, and external parties via seamless microservices API-based access to analytics and Data extracts with proper access management and monitoring. 

 

The Data warehousing operations are managed by a dedicated team whilst shielding users from the complexity of its implementation.

Getting Data foundation right for positive business impact

DaaS

[noun]

The provisioning, distributing and analyzing of Data in organization whereby Data management, governance and security is inherent to each Data element at Group or Business Area Layers.

Business Outcomes

Built-in Data Governance

Improves Data Quality

Data Science at Scale

Reduces Cost

Real Time Processing

.

.

Built-in Data Governance

.

.

Improves Data Quality

.

.

Data Science at Scale

.

.

Reduces Cost

.

.

Real Time Processing

Data as a Service Pillars

Open
Architecture

Future ready Architecture API driven approach for ingestion and publishing of analytics and Data extracts.

Self
Service

Data and analytics on-demand logical, federated view of Data business autonomy.

Governance
is the key

Data standardized across a single platform defined policies on use of Data throughout its lifestyle.

Driving
Data Culture

Data culture and Data success are intertwined and interdependent.

Open Architecture

Future ready Architecture API driven approach for ingestion and publishing of analytics and data extracts

Self Service

Data and analytics on-demand logical, federated view of data business autonomy

Governance is the key

Data standardized across a single platform defined policies on use of data throughout its lifestyle

Driving Data Culture

Data culture and Data success are intertwined and interdependent

Open Insights’ approach to build DaaS

Rapid assessment of current and target state

Stand-up partial DaaS supporting first high-value use case

Deliver measurable business value after each sprint to keep the business engaged
Build out DaaS in stages iteratively to reference architecture by addressing next highest-demand high-value use cases

Open Insights’ DaaS Principles

  • 1

    Open Architecture & Data APIs

    • Utilizes open source technologies and open storage formats to leverage ongoing innovation and to reduce TCO

    • Allows for integration with open source Data sharing and proprietary tools

Rapid Build and Implementation Process
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