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Data Governance for the Digital Age — Part 2: Organizational Structure



organizational structure


Let us briefly examine some of the data functions that your organization must coordinate to be successful in the digital age.

  • Chief Data Officer (CDO) – The CDO is a relatively new C-level title. This individual must orchestrate data systems and technologies while leading and managing the people involved in data governance.

  • Chief Information Officer (CIO) and Chief Technology Officer (CTO) – Traditionally the CIO managed the IT team, which was a service provider for internal tech users. The CIO will need to transition from being a service provider to becoming the driving force for processes and technology that enable the business to thrive in the digital space. The CTO typically managed external facing technology to fit the organization’s business model. This role will also have to move beyond the current expectations of aligning technology to business models to developing a better business model using the best technologies. Both titles will become primary examples for leadership and innovation going forward.

  • Data Protection Officer (DPO) – The DPO must ensure and demonstrate the organization’s compliance (to GDPR and other local data regulations). Laws and regulations are trending towards stronger data privacy and security, giving the DPO a more critical role now than ever.

  • Data Architect – The data architect defines the data vision based on business requirements, translates it to technology requirements, and defines data standards and principles. The data architect must consider the balance of control and democratization when it comes to the organization’s data architecture.

  • Data Engineer and Developer – Engineers and developers design, deploy and maintain the architecture to process the data flows for the organization. They need to ensure that the “new” data architecture remains robust while being decentralized.

  • Data Scientist and Data Analyst – Data scientists and analysts are responsible for discovering insights from massive amounts of data to help shape or meet specific business needs and goals. Note that data analysts usually work with only structured data while data scientists work with both structured and unstructured data. With the volume of unstructured data, the importance of the data scientist has become critical, while some of the basic functions of a data analyst will become automated.

  • Business Analyst (BA) – BAs take the curated and validated data and use business intelligence (BI) tools to generate trusted insights from the data. They usually present this information in an easily digestible format such as an intuitive dashboard. These BAs will have to improve their data literacy and be involved in the data governance process.

  • Data Steward, Data Custodian, and Data Owner – These were traditionally IT roles, but will now be assigned to the actual data users such as BAs. These individuals need to have both domain knowledge and the technical background to manage data and administer data tools.

This article was part of the “Data Governance for the Digital Age” series:

Part 1: A Paradigm Shift 

Part 3: A Collaborate Data-Driven Culture

Part 4: Technology for Democratized and Collaborative Data Governance 

About BaseCap Analytics: BaseCap’s Data Quality Manager is a data quality control platform that supports a collaborative data governance. Its intuitive user interface allows non-technical individuals to be data stewards. With no user limit and customizable permission levels, an organization can leverage the Platform to address all data issues across all its teams.

Contact us to see how the Data Quality Manager will become a critical component your organization’s data governance program.