What's Data Architecture?

Data Architecture is all about understanding and organising your data landscape: knowing what data is valuable to your business, what it means and where it lives.

Reduce duplication and fragmentation across your organisation

Standardise terminology and promote a common understanding

Make your data more simple and less costly to manage

Improve discoverability and insightful analysis of your data

Make it easier to comply with industry regulations

Why Ortecha?

Core to Ortecha’s work, we define meaningful, coherent Data Architectures that unlock value and make your data landscape easier to understand and cheaper to maintain.

We’ve seen it all! Conceptual, logical, semantic & physical models

We are skilled at both Application & Enterprise level Architecture

We endeavour to use existing standards rather than building new

We’re recognised as experts that deliver value to our clients

Our consultants have been involved in Architecture throughout their career, some for over 20 years

How we can help you

Data Architecture Strategy

If your data landscape is complex it’s helpful to define how you’ll tackle your Data Architecture. We can help you set your vision and adopt best practice standards so modelling activities work in harmony.

Data Modelling

It’s difficult to derive value from data that is misunderstood, misused, duplicated or ambiguous. We can help you pin down definitions, meanings and relationships, so you can make the most of your data.

Data Flow Modelling

Complex ETL (Extract-Transform-Load) processes can be tricky to follow and almost impossible to explain. We can help you design your data flows and data transformations so they’re clear and efficient.

Data Architecture Consulting

Wherever you are with Data Architecture we can support you. Whether you need high-level one-off advice or regular ongoing guidance, we can help you efficiently manage your data landscape.


Data Architecture at a Global Investment Bank

The Challenge

A Global Investment Bank was struggling with the challenges of regulatory demands such as BCBS239, because they lacked a common definition of the data across their different business units.

With thousands of applications, databases and feeds distributed across the organisation, they needed to better understand what data they had, how it flowed and where it was used.

What we did

Built Logical and Physical Data Models across each risk domain

Developed data standards to provide common definitions for all

Established data modelling standards so modelling activities could be federated

Created a fully attributed and well-defined Enterprise Data Model

Standardised data feeds flowing into a new data lake platform

The Benefits

All of the bank’s data described and visualised in data models

Enterprise-wide Data Dictionary using a common terminology for all areas

Common data sourcing led to thousands of legacy feeds being decommissioned

Ability to join disparate datasets together for analytics and reporting purposes

Improved discoverability, enabling the bank to comply with risk regulations

Ortecha has consistently provided experienced data modelling teams with Financial Services knowledge. This is rare and required expertise in the industry.