第8章データ管理

The set of clear roles, policies, and responsibilities that enables a business to manage and safeguard data quality using internally set rules and policies is called data governance. The related concept that ensures that data practices align with external legal requirements and industry standards is called data compliance. For example, the UK-GDPR (General Data Protection Regulation) is the United Kingdom’s data security regulation, modeled after the EU-GDPR that governs and regulates how UK organizations and businesses collect, store, use, and process personal data.

Using data governance, data are managed as an asset rather than a liability. Data governance has three dimensions: technology, people, and process. It should include standard roles for quality, security, and ownership.

In planning for data governance, we should answer four questions: what, how, why, and who. What policies should we include? How do we integrate the policies with the enterprise business process? Why do we need this policy? Who will be part of this policy?

Different frameworks have been introduced for data quality management and data quality improvement: Total Data Quality Management (TDQM), Total Quality Management (TQM), Capability Maturity Model Integration (CMMI), ISO 9000, Control Objectives for Information and Related Technology (COBIT), Data Management Body of Knowledge (DMBOK), Information Technology Infrastructure Library (ITIL), and Six Sigma. These frameworks provide guidelines for organizations that define how a product or process should be based on high-quality standards. The main issue in these frameworks is that they may cause failure when the system is not considering all of the processes in a correct flow.

It is possible to annotate the data with data quality metadata as a short-term solution. Unfortunately, many data governance efforts (if any) are mostly reactive and ad hoc.

Chegg is an educational technology company based in California. It offers various online services such as textbook rentals, tutoring, homework assistance, and more to students around the country. In April 2018, an unauthorized party gained access to Chegg’s database. This database hosted user information for both Chegg and its affiliated companies (e.g., EasyBib). The hacked information included names, emails, passwords, and addresses, but did not include any financial information or social security numbers. After discovering the breach, Chegg implemented plans to notify the 40 million affected users. The motivation for the attack is still unclear, but it is likely that a third party sought information to profit from identity theft.

What are some things that Chegg users can do to protect themselves from this hack and future breaches of personal information?

Within any organization, there are various data management roles including information architect, database designer, data owner, data steward, database administrator, computer scientist, and data scientist. Their roles are outlined in the following sections.

An information architect, also known as a data architect or information analyst, is responsible for designing the conceptual data model (blueprints) to bridge the gap between the business processes and the IT environment.

The information architect collaborates with the database designer who may assist in choosing the type of conceptual data model (e.g., EER or UML) and the database modeling tool. Figure 8.5 shows an example of different database systems that various personnel working in data management may encounter.

A database designer is responsible for creating, implementing, and maintaining the database management system. Other responsibilities include translating the conceptual data model into a logical and internal data model, assisting the application developers in defining the views of the external data model, and defining company-wide uniform naming conventions when creating the various data models.

The data owner has the authority to ultimately decide on the access to, and usage of, the data. The data owner could be the original producer of the data, or the data could originate from a third party. A person who assumes the role of a data owner should be able to insert, edit, delete, or update data as well as check or populate the value of a field. The data owner is the one responsible for checking the quality of one or more datasets.