Andreas Bartsch, Head of Service Delivery at PBT Group

As technology has changed and data become more critical to the success of businesses in a digital environment, so too have the roles and responsibilities of Data Specialists shifted. One of the keys to business success now lies in how businesses manage these changes and deliver on stakeholder expectations to become more data-driven.

In the past, a data platform’s source data mainly resided within systems with relational structures like enterprise resource planning (ERP) and customer relationship management (CRM). But then the Internet and social media gave rise to an explosion of unstructured data, Big Data. This now requires data sources to be ingested into the likes of data lakes, extracted and transformed to operational data stores or data warehouses, and analysed for competitive advantage by data scientists, analysts or business users.

Specialist roles

Each business has put its own flavour on job titles and responsibilities when it comes to their data functions in this dynamic new environment.

A Business Analyst (BA) that used to typically be a subject matter or industry expert within a specific business area, is now being complemented by a BI Business Analyst or Data Analyst. Both these roles require a good understanding of data platform architectures, concepts and principles, with the BI Business Analyst being more client facing and the Data Analyst having a somewhat more technical focus.

Another example is the Data Architect that takes charge of the technical design of the data platform. This person is positioned across all data components and lives and dies by the total architectural design of the platform. And then there are the likes of Data Modellers, Data Analysts, Data Engineers, Data Visualisation Engineers, Data Scientists, the list goes on.

More than technology

A central theme is that roles change and evolve as new technologies and the cloud drive business strategy. Things like the Internet of Things (IoT) and Edge Computing, concepts like DataOps, and others contribute to a continuously changing data landscape.

But it is critical that the Data Specialists must remain technology agnostic. Take cloud service providers as an example. Each of them has their own products and services that deliver ETL (extract, transform, load) functions using their proprietary tools. This creates complexity in the tool stack especially when businesses still rely on their own solutions to deal with legacy systems.

For Data Specialists, in whatever role they are fulfilling, the underlying data management principles re more important than the supporting technology. Even though the latter remains important, it is about how to design and integrate all data environments for the success of the business and align to its strategy.

Going unstructured

Unstructured data has resulted in a significant change in the landscape to date. It has introduced new layers (such as data lakes) with new data modelling concepts and techniques also considering the sheer volumes. And while different technologies have emerged to explore this, the science of data will play a crucial role.

Any Data Specialist must now gain an understanding of the concepts behind unstructured data and the different mechanisms used to unlock its value. It comes down to having access to such Data Specialists that are familiar with the evolving landscape and what it means from both data and business perspectives regardless the technology.