Database Architect versus Data Architect

Is there a difference between a Database Architect and Data Architect ? I was talking with a colleague , who is creating a job description for a Data Architect. As we discussed the skillset and characteristics of the two roles – it became obvious there is some overlap – but the two functions are different

The Database Architect Role and  Data Architect are involved in the same workflow – but become involved at different times . Depending on the organisation – there can be different configurations of these roles.

The Data Architect – also called a Modeler,  looks at the wider use of data , they should be involved at the outset of the project ensuring : metadata , defining enterprise use ,logic data models  are established. The process is  independent of the RDBMS.

When the logical models are created ,the Database Architect decides which RDBMS and how the infrastructure is implemented. They tend be experts in one or more RDBMS systems. The database architect is concerned with  performance, optimisation,  capacity planning,  data storage techniques and DBA challenges

As an added note : the DBA role will work with the Database Architect to develop the relevant knowledge in being to support the database systems.

The larger organisations may have 2-3 “physical” DBAs and 2-3 “logical” modelers. Quite often a Senior DBA will also act as the Database Architect

Data Architect skillset

Data Analysis

Data Migration Tools

Data Modeling – Enterprise Data Modeling with an emphasis on transactional enterprise data models meeting normalization rules

Data Integration -  disparate source systems and disparate data formats.

Database Design – Structured methods for design

Data Architecture – Conceptual Model methods

Metadata management

Database Architect

Security Architecture expert

Database Engine in-depth

ETL tools – Designing and implementing ETL processes

Database Design Patterns – OLTP ,DSS

Database Usage Methods – OLTP , DSS

Data Storage Techniques. Defining database server IO profiles  and mapping to storage methods such as DAS, SAN, SSD, RAID levels ,PCIe attached .

Database Optimization Techniques such as Partitioned Tables, Queues,sql programming, Exceution Plans, Data File management to support different usage ,full range of Backup and Restore  strategies, Indexes, XML optimization

Performance Tuning – Strategies for improved performance across the whole Performance Stack

Disaster Recovery and High Availability -  Techniques such as Linux Clustering,Tivoli Storage Automation,HADR, SAN Replication

Extending functionality, sometimes integrating with legacy systems

Integration with External Applications  -

Capacity Planning

Let me know how these terms are applied in your organisation.

Read More

Database Tuning overview –Storage Tuning

Database Tuning overview – Hardware Tuning

SQL Server – RAID levels overview