Information quality management: Roles & duties


A hand reaching out to adjust a point on a data graph visualization. Image: WrightStudio/Adobe Stock Data quality management is a crucial aspect of any business’s growth and functional techniques. But attaining high information quality needs that particular functions, responsibilities and tools be in place.

SEE: Task description: Chief data officer (TechRepublic Premium)

Data management takes a team with both technical and organization proficiency. They need to work together to understand what data is needed by various stakeholders, how it must be gathered or created, how administrators should store it, and whether they need to update it occasionally. In addition, business need front-end (collection) and back-end (analysis) teams who evaluate incoming information streams to identify problems before propagating throughout your enterprise.

Assembling a group with these skillsets and duties can be tough, particularly for companies that are simply getting going with a data-driven mindset. To accomplish greater levels of information quality through reliable information quality management, consider investing in professionals who can deal with these data functions and responsibilities.

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What is information quality management?

Data quality management is the procedure of guaranteeing that information meets a set of fixed requirements. It is an information strategy that takes a look at the whole information lifecycle, from collecting and putting together raw information to evaluating and presenting it in significant ways. Information experts play an essential role in every action, managing how details is gathered, processed, kept and distributed.

Data quality management roles and responsibilities

The information quality management procedure is a diverse one that involves different professionals with differing obligations. These are some of the most essential functions to include on a data quality management job force:

Data quality managers

Information quality supervisors are responsible for managing projects related to data quality along with evaluating what requires to be enhanced. The duties of information quality managers consist of the following:

  • Working with customers to recognize and specify requirements for information quality management tasks.
  • Analyzing information that requires to be handled to figure out how well it aligns with these requirements.
  • Developing metrics to determine development towards specific task objectives.
  • Executing new policies or procedures that will result in improved information quality.
  • Monitoring development versus metrics gradually.

Chief data officers (CDOs)

A primary information officer, or CDO, is a C-level executive who is accountable for a company’s information possessions. As their core duty, CDOs guarantee that their company’s information properties meet tactical objectives. The function of the CDO has been developing over the last few years from tactical information management to business procedure management as more organizations become reliant on data-driven decision-making.

The responsibilities of a CDO differ by organization but usually consist of the following:

  • Establishing organizational goals associated with data quality management.
  • Establishing policies for the usage and control of organizational information possessions.
  • Overseeing the application of those policies and developing systems for determining compliance.
  • Prioritizing information quality tasks.
  • Integrating information quality across organizational departments.
  • Training personnel on best practices.
  • Promoting internally and externally for enhancements in organizational data practices.
  • Overseeing the information quality management process to make sure data that is collected and utilized by the company fulfill service requirements.
  • Developing strategies for how to use information to accomplish business goals.

SEE: Techniques for adopting information stewardship without a CDO (TechRepublic)

Information stewards

A data steward is a professional accountable for implementing policies around data use and security as set by the organization’s data governance method. In addition, information stewards may be responsible for assigning resources to preserve and update databases, ensuring that policies are being followed, and tracking and reporting on information quality.

The responsibilities of an information steward can change from task to job depending on the scope of their role and their function in the company.

As the data gatekeeper, the information steward takes an active management function in preparing tasks, evaluating reports, taking part in development sessions, designing new processes, and advocating for changes when essential.

Data Stewards deal with groups across different practical groups to develop commonalities on how best to use and handle data-related details throughout the enterprise; this effort often needs negotiating cross-functional differences among stakeholders with different requirements or priorities.

SEE: How do I end up being a data steward? (TechRepublic)

Information experts

A data expert is a data specialist who gathers, evaluates and analyzes raw information to reveal patterns. Data analysts can be discovered in many markets, consisting of retail, finance, government and health care.

Their duties vary by market but generally include:

  • Gathering data from numerous sources.
  • Evaluating collected data.
  • Designing and keeping data systems and databases.
  • Making predictions based on their findings.
  • Communicating plainly with coworkers across departments.
  • Working with developers, engineers and organizational executives to boost processes, modify systems and develop data governance policies.

Information experts should have excellent organizational skills to keep track of big amounts of information. They must also communicate effectively with individuals throughout departments, such as IT personnel or company advancement professionals who are not involved straight with the analytical process.

Information experts work closely with the data scientists who are accountable for developing predictive designs based upon historic patterns and forecasting what will occur in the future. These two positions need similar ability, though one may specialize more in analytical analysis while another specializes more in predictive modeling.

Information custodians

Must-read big information protection

An information custodian is a data specialist who is accountable for the storage and security facilities of all or part of the enterprise. Data custodians supervise the storage, aggregation and usage of datasets. In addition to keeping, handling and securing data on behalf of other users or departments within a company, information custodians are frequently accountable for guaranteeing that organizational requirements for privacy guidelines are met in accordance with the organization’s data governance method.

Their duties may include managing dangers connected with details access, adjustment and deletion, and figuring out how admins should retain long information. The individual might likewise need to carry out tasks connected to systems user management, configuration management, systems advancement lifecycle management, capability preparation, disaster recovery preparation, backup treatments and media management.

Information modelers

Information modelers are systems experts who deal with data architects and database administrators to create a data model that specifies the various elements of the information architecture. They construct an organizational structure for a company’s information by deciding what data will be stored in databases and how to structure it.

SEE: Task description: Big information modeler (TechRepublic Premium)

Data modelers’ obligations consist of:

  • Developing models that specify different elements of the information architecture.
  • Building an organizational structure for company information by choosing what information will be saved in databases and how to structure them.
  • Choosing how data is moved between systems so that it can be examined or accessed by people or programs.
  • Making sure a suitable level of information quality across all applications and systems.
  • Developing guidelines for handling change and modeling brand-new requirements.

Big data engineers

A big data engineer is an IT expert who uses big data innovations to examine big datasets. Big data engineers design, build, evaluate, test, preserve, monitor and handle intricate company data facilities systems.

SEE: Hiring package: Data engineer (TechRepublic Premium)

A huge data engineer’s task consists of handling relational databases, columnar databases, distributed file systems, caching algorithms, info retrieval approaches and other associated techniques.

Data designers and designers

A data designer or information designer is responsible for designing a business’s information architecture. This consists of event requirements from service stakeholders, analyzing the existing information structure to determine what needs to be done and constructing an architecture for the future.

SEE: Hiring package: Data designer (TechRepublic Premium)

Data designers are strategic thinkers who comprehend how any modifications in the innovation landscape will affect a business’s data environment. They look after all the technical elements of developing information architectures and guarantee they align with other organizational initiatives. They also manage relationships with IT partners and vendors and should have exceptional communication skills.

Having the right people in place is an important primary step towards greater information quality, however it’s equally crucial to give them the tools and resources they require for success.

There are a variety of tools readily available for this purpose that vary from easy to complex. Choosing a data quality management tool will depend upon the size and scope of your company in addition to how much staff time and resource you can devote to this task.

Some of the top information quality tools to think about include Cloudingo, Data Ladder, IBM InfoSphere QualityStage, Informatica Master Data Management, OpenRefine, SAS Data Management, Precisely Trillium and Talend Data Quality. These tools vary in price, complexity and feature sets, so ensure to think about all of these aspects when selecting which tool best matches your business’s particular requirements.


Starting with the right data quality management group and responsibilities is a substantial initial step that numerous companies never ever take. It involves preparation, comprehensive understanding of your organization’s data method and a dedication to employing and training the right people for the task. To attain the highest levels of success right out of the gate, hire an information leader like a chief data officer who can shape and improve your data quality management hiring strategies as your business’s goals evolve.


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