Build Data Tools for aiOla:

• Develop infrastructure and tools to execute data-based processes

• Buid M.V.P: Move, Validate, Process: a tool to execute customer-oriented data pipeline

• Support (and development) of data pipelines oriented by customer needs (a.ka. Content Pack)

• Build DaLs (Data Access Layers) to support the aiOla model – both real-time and analytics.

Build Data Pipelines and Process:

• Developing data pipelines oriented by-product needs (e.g. ai_monitoring)

• Building a data lake compound of product and customer data (single tenant-oriented)

• Building one centralized data lake (multi-tenant oriented)

Own oiOla data model:

• Owning and maintaining the aiOla data model

• Defining the physical aiOla data model and storage architecture

• Data-related developments (e.g. data migration)

Maintain and govern Data quality:

• Developing data testing abilities

• Integrating data quality in all data pipelines

Be Data Evangelists:

• Leading the examination of new data tools

• Domain experts

• Supporting aiOla needs by providing suitable data tools