February 20, 2020

Redefining the Role of the Data Architect

Keith Kohl

Topic:   Data

The age of the data-driven business is upon us. Data, more than ever, has become a strategic asset, both driving and supporting digital transformation across every industry. Investment in data management, data science, and related technologies is healthy, too. The global market intelligence firm International Data Corporation (IDC) projects that spending on data and analytics will reach $260 billion by 2022.1

Data architects walk the line between technology and business – and this is a crucial partnership for data-driven success.

Organizations that are focused on becoming data-driven typically understand, or learn quickly, that trust in data is a prerequisite to being able to use it effectively. Trust in data means you can confidently base your decisions on it, and take action where it matters most. Trust means being able to pull together complex and siloed data into an integrated, accurate, and consistent view of your customer (or patient, or citizen, or supplier) to reveal insights that become the keys to innovation – building new transformative experiences to retain and delight. Organizations that are leading this new era understand that their data can lead to better products, better outreach, and better customer support.

In this current environment where “data is king,” data professionals are in a sweet spot. One role in particular has become more strategic with this paradigm shift: the data architect. Why? Because data architects walk the line between technology and business – and this is a crucial partnership for data-driven success.

Creating a Data and Technology Strategy

The business has to guide the implementation and use of data to ensure alignment with overall business goals and objectives. Data leaders have to build and operate the data management platform architecture, and draw on their experience to guide the selection of technologies and partners. In doing so, there are certain fundamentals that any platform needs to deliver. These include integrating and cleansing disparate source data, and deploying mastered domains. Data architects play a key role in delivering these capabilities.

It is important that the data architect tie this technical architecture to the desired business outcomes and goals. For example, a police officer should be able to quickly sift through consolidated records to find a person’s name, address, or other mastered data entity. A bank officer or marketing department should be able to see a 360-degree view of customers to effectively cross-sell and up-sell products and services. In healthcare, the data architect will bring in external big data sources such as population health, and combine them with clinical and financial information to measure performance with great precision.

When a data architect shifts his or her focus to the business driver, rather than the technology capability, it’s easier for companies to align on data strategy. Data-first thinking must always be informed by the mission.

When a data architect shifts his or her focus to the business driver, rather than the technology capability, it’s easier for companies to align on data strategy. Data-first thinking must always be informed by the mission.

Data Governance

Data governance requires a multi-pronged approach involving business process, technology, and industry best practices. One challenge with data governance is that business executives typically can’t translate the operational use of data into the systems that house that data. What an opportunity for data architects to educate the organization, and design and implement a data reference architecture to ensure data relevancy and quality throughout its life cycle. 

A strong value proposition that outlines the need and the anticipated returns will help recruit executive sponsorship at the outset of a project. Demonstrating measurable, relevant value over time will maintain the sponsor’s interest, so they will continue to use their clout and political standing to make data governance a continued priority across the organization.

Support and involvement from business and IT leadership is necessary to implement and enforce these processes and foster the needed organizational changes. To avoid disruptions and enable continuous improvement, data leaders and architects should ensure initiatives are designed to adapt to evolving needs. Engage non-IT and non-strategic personnel in data remediation and governance to promote cultural and process change and ensure alignment of strategic and tactical objectives.

Master Data Management

Master data management (MDM) is all about creating a “single version of the truth” for key business data. The technical fundamentals are simple enough for mastering: What are the data sources? What is the structure of these sources? What are the business definitions? Certainly, data architects are immersed in fulfilling these tasks.

But in our new, data-driven company it becomes critical to put the data into a business context. How is the data linked across the entire organization? If the data is changed, what processes are impacted? The key for the data architect is to make sure the mastered data reflects the people, processes, and data of the organization.

Recently I had the opportunity to speak with a data architect from a major hospital network who highlighted her approach to mastering data. “We reverse-engineered our implementation approach based on analytical needs. Instead of starting with mastered domains, we started with our strategic business priorities, developed analytics requirements to support those priorities, and let those analytics requirements drive the implementation plan.”

The Rise of the Business-Driven Data Architect

Becoming a data-driven company optimizes business, but this transformation needs to tie into the technology fabric of a company. This larger digital transformation requires a data transformation, too – and this begins with the data architect. The data architect understands technology and can communicate it effectively. If the data architect can embrace the needs of the business and ingest business requirements into the platform, data strategy, governance strategy, mastering strategy, and finally the analytics strategy, it is only then that a company can truly be prepared to adapt, survive and thrive in the future.


1 IDC, “IDC Forecasts Revenues for Big Data and Business Analytics Solutions Will Reach $189.1 Billion This Year with Double-Digit Annual Growth Through 2022,” idc.com, April 2019.