Data management is an enterprise function, comprising large teams with many roles and responsibilities. However, there are a few key roles within the enterprise data management team that should be carefully chosen to build a strong foundation team.
Data strategist is a very senior role and generally holds executive position within the organization. They are responsible for formulating the vision and strategy for leveraging data for the benefit of the organization. They are closely involved with the teams that are working on business strategies and have good understanding of the industry, markets, competition and trends. They align the data strategy to meet business objectives like improving the products and services, cutting operational costs, improving performance and profitability, reducing risks and monitoring business models.
They generally operate on an enterprise level, and consolidate various data related requirements from various business units to build common approaches and solutions across the enterprise. The are also involved in setting priorities for servicing various businesses and defining the roadmap of technical implementations. They also formulate the execution strategy for implementing the enterprise data strategy, and engage with the businesses to get continuous feedback from them. They manage various stakeholders within the organization, and resolve conflicts of interest across business units within the organization.
Data Governance Specialists
Data Governance specialists are typically from business background and are responsible for ensuring data quality and data integrity within the organization. They are responsible to build governance structures and define data policies and processes. They define owners and stewards of data, and define how data quality and integrity is ensured on an enterprise level.
Data Governance specialists are senior roles and have typically spent several years in the organization, and have good understanding of various business stakeholders and organizational governance structures. They have a good understanding of the industry, business, compliances, regulations etc.
Data Architects are typically from technical backgrounds, but have a good understanding of the organization, business, industry, markets and trends. They are responsible to build technical solutions that adhere to the enterprise data strategies and data policies. They ensure that the solutions are built in accordance to the design standards and are consistent across the organization. They ensure that the technical solutions meet the user requirements, and are aligned to the overall business goals. They also ensure that the technical solutions are easy to use and get adopted across the enterprise.
Data architects are specialised to build enterprise frameworks that enable quick and easy onboarding of various technical implementations, thereby improving the ability of the organization to constantly meet the changing business requirements. Data architects typically design solutions blueprints across the enterprise. They understand the latest technology trends, and liaise with various technology and systems integration vendors to design technical solutions. They ensure that the right technologies and designs are implemented to solve business problems.
Data Analysts are representatives from the business who use are entrusted to help the technical teams with the business knowledge and are involved in detailing the business requirements. They also help the technical teams in identifying data sources, data transformation rules etc. They also constantly communicate with the application users and ensure that the solution meets their requirements.
Data analysts are responsible to engage with the users of the applications within their own business area, and constantly get feedback from them to ensure that the technical solutions deliver what the users want. They serve as the eyes and ears of the implementation team, and ensure that the solution gets adopted by the business. They are the evangelists of the solutions within the business, they do user acceptance tests, perform user trainings, manage user escalations, coordinate across businesses for data access etc. and get involved in the data governance process to manage data within the organization.
These are skilled technical people responsible for designing and building technical solutions. They are responsible to ensure that the solutions can scale up to high data volumes. There are various technical specialties like ETL experts, reporting experts, data visualization experts, data analytics experts, data modelers, database experts etc.
Technical experts design and build solutions in line with the business requirements and according to the prescribed solution architecture. Technical experts continuously catch up with the changing technology landscape, learn new technologies, understand the capabilities and the limitations of various technologies within the field of their expertise. They create design guidelines for ensuring consistency of design across the organization, and are responsible to build technical competencies within the organization. They recruit, lead and manage technical teams. They build eminence within their technology domains and contribute towards the progress of technology. They typically join technical communities, speak in technical conferences, mentor junior technologists, publish research papers and are the evangelists of their technology within the organization.
Data scientists are the engine of innovation within an organization. They constantly experiment with data to validate various business hypothesis, improve various products and services, create new products and services, and constantly optimize operating costs and reduce risks.
It is a common misconception that data scientists are from technical backgrounds, but they do have very strong technical skills for handling data. Apart from technical skills, they also have vast experience in a specific business domain. They are very professional and data driven in their approach, and have great convincing and storytelling skills. They typically have good knowledge of statistics, and have expertise in building predictive models.
Data scientists operate in data labs, an area dedicated for experimentation. They work closely with data strategy teams and provide them with insights to build new applications that can use data to its full potential for business benefits.
Data Product Managers
Data Product Managers use data from data warehouses to build business applications. They have good understanding of the business and how data can influence the business. They are also skilled in designing and building products for customers. They understand the psychology of their customers and are aware of the current trends in the market. They can build new business models or improve existing business models.
Data Product managers are senior roles, and they can come from either technology or business backgrounds. They are typically good at identifying the value that the product brings for its users, conceptualising the design of the product, engaging with the users to get continuous feedback on the product and defining the implementation strategy to build the product. Product managers are also expected to be good at stakeholder management, team management and delivery management.