Data 101: The Data Dream Team – Exploring the various roles in data-driven organisations
By Syazwani Tajudin (Wani), Data Analyst at Derilinx
In today’s data-driven era, organisations are increasingly aware of the importance of data and its ability to offer a competitive advantage. However, behind the scenes, a diverse group of professionals collaborate to extract insights, guide data-driven decisions, and contribute to the overall success of the organisation relevant to public and private sectors.
In this blog post, we will explore the different roles found in data-driven organisations as defined by DAMA-DBOK2 and highlight the specific responsibilities and essential skills needed for each role.
The Executive Team
1. Chief Data Officer
A key executive in charge of spearheading the organisation’s data-focused initiatives. They are appointed to bridge the divide between technology and business, advocating for a comprehensive data management strategy at a senior level. For example, the Chief Data Officer collaborates with business functions (e.g., HR, finance, product) to align data initiatives with business goals and ensure data quality, privacy, and compliance.
The Business Team
1. Data Protection Officer
In-charge of how the/making sure that the organisation processes personal data such as staff data, customer data, and any other individuals’ data in compliance with the applicable data protection rules. For example, in a healthcare organisation, the Data Protection Officer plays a critical role in ensuring the security of patient data and adhering to privacy regulations like the General Data Protection Regulation (GDPR).
2. Data Owner
A business data steward who has approval authority for decisions about data within their domain. For example, a marketing manager may be the Data Owner for customer data, determining how it is collected, stored, and used for marketing campaigns.
3. Data Custodian
IT personnels/ professionals who understand where and how the data is stored. They also translate the definitions of data quality into queries or code that identify specific records that do not comply. For example, the Data Custodian in a financial institution is responsible for securely managing and protecting financial data. They collaborate with IT and other departments to enforce data security measures and ensure compliance with regulations and internal policies.
4. Business Data Steward
Often recognised as subject matter experts accountable for a subset of data. They work with stakeholders to define and control data. For example, a Sales Data Steward oversees sales data, ensuring its accuracy, generating reliable reports, and addressing any data-related concerns that may arise.
5. Technical Data Steward
IT data professionals operating within one of the knowledge areas such as Database Administrators or Business Intelligence Specialists. For example, a Technical Data Steward collaborates with IT teams to develop and enhance data pipelines, ensuring smooth data integration and high data quality across the organisation.
6. Project Manager
Responsible for delivering the project, leading, and managing the project team, with authority and responsibility from the project board. For example, a Project Manager leads a data migration project, coordinating team efforts to ensure a seamless transition from old systems to a new data platform.
The IT Team
1. Data Analyst
Responsible for collecting, organising, and analysing data to uncover insights and patterns. They often work with large datasets, using statistical techniques and data visualisation tools to make sense of the information. For example, a Data Analyst may examine sales data to identify trends in customer purchasing behaviour, helping the marketing team optimise their campaigns and target specific customer segments for an effective campaign performance.
2. Data Architect
Responsible for data architecture and data integration. Data architects may work at the enterprise level or a functional level. For example, a Data Architect works with the IT team to establish data infrastructure like databases, data warehouses, and data lakes. They ensure data is stored in an organised manner, facilitating easy access for analysis and reporting.
3. Data Engineer
An expert who focuses on developing and managing the technical components of a data ecosystem. For example, a Data Engineer develops a real-time data pipeline that captures customer interactions on the company’s website, such as product views, clicks, and purchases.
4. Database Administrator
Responsible for the design, implementation, and support of structured data assets and the performance of the technology that makes data accessible. For example, Database Administrator handles routine tasks such as database backups, recovery, and user access management.
5. Business Intelligence Analyst
Responsible for supporting effective use of Business Intelligence data by business professionals. For example, the Business Intelligence Analyst may focus on analysing sales data to identify patterns and trends to find new revenue growth opportunities.
6. Data Quality Analyst/Manager
Responsible for assessing data suitability, monitoring data condition, and contributing to the analysis of data issues. For example, a data quality analyst assists a financial organisation to identify opportunities for business processes and technical enhancements that improve financial data quality.
The scenarios illustrated above simplify the different data roles and their responsibilities. In practice, the three teams often collaborate closely, leveraging their expertise to derive meaningful insights to solve complex problems. This is the main essence to create the data dream team for any data-driven organisation. Refer to this link for the full data terms of reference commonly used in a data-driven organisation.
It is important to highlight that Public Sector Bodies, SMEs (Small Medium Enterprise) and companies starting their data journey might not have the resources to fill up every role above. In practical terms, some individuals might have to take on more than one role, or they can decide to outsource part of them to be able to follow good data management practices.
There are data services companies that can help you overcome those limitations, complete, and enhance your data dream team and improve every stage of your data journey. To learn more about how Derilinx can help you achieve your goals, check out this blog post or contact us.
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