Learn why conducting a data migration impact assessment (DMIA) is crucial for data architecture and how it can help ensure a successful data migration outcome.

1 Take the Assessment. Data management is critical for the success of expanding BI and analytics programs. That’s why TDWI created the Data Management Maturity Model and Assessment—to help ...

ML and DL (deep learning) algorithms are important in helping organisations learn from sourced data, in structured and ...

Data architecture management is crucial for aligning information systems with business objectives. However, existing frameworks often lack comprehensive assessment tools. This study proposes an ...

Data architecture describes the structure of an organization’s logical and physical data assets, and data management resources, according to The Open Group Architecture Framework (TOGAF).

The data architect is responsible for visualizing and designing an organization’s enterprise data management framework, which describes the processes used to plan, specify, ...

A headless data architecture means no longer having to coordinate multiple copies of data and being free to use whatever processing or query engine is most suitable for the job. Here’s how it works.

Data architecture, however, spans the organization and takes a high-level, holistic view, whereas data modeling focuses on specific systems or business cases.