第8章データ管理

A data steward is a DQ expert who ensures that the enterprise's actual business data and the metadata are accurate, accessible, secure, and safe. The data steward performs extensive and regular data quality checks, initiates corrective measures or deeper investigation into root causes of data quality issues, and helps design preventive measures (e.g., modifications to operational information systems, integrity rules).

The database administrator (DBA) is responsible for the implementation and monitoring of the database as well as ensuring databases run efficiently by collaboration with network and system managers.

A computer scientist is a person who has theoretical and practical knowledge of computer science. The computer scientist will solve problems using technology by applying computer science practices. Computer scientists typically focus on building end-to-end solutions for companies. For example, computer scientists can create software applications that implement complex algorithms and store and retrieve related data into and from database systems. Computer scientists may also be involved in designing and fine tuning complex machine learning algorithms.

Data scientists typically focus on creating classification and prediction models by training existing machine learning algorithms. The resulting trained models act as programs to help classify new data or predict an outcome based on input data. In general, a data scientist is a person who has theoretical and practical knowledge of managing data. A data scientist’s background combines computer science, mathematics, and statistics. A person in this role is responsible for gathering a large amount of structured, semistructured, and unstructured data to preprocess and prepare data for advanced data analysis to develop a product or to make a business decision.

The data management road map has multiple steps, starting from collecting and storing data to having a final product or decision. Available databases vary in type and vendor (e.g., SQL, Hadoop, Spark, and MongoDB). Storing the data in databases is not hard, but the entire data management process most often takes place on the cloud, which adds a new set of necessary skills for the computer scientist and the data scientist. Massive data growth transformed the way data are stored and analyzed, and many applications and databases are hosted on servers in data centers elsewhere. While preparing data, data scientists and computer scientists should clean and format the data/information to be used for the correct marketing use. We will discuss database types in more detail together with their data structure implementations (refer to 8.2 Data Management Systems).

End-to-end data management covers the data life cycle within the system. A data life cycle is a process that helps the organization to manage the flow of data, and it includes creating the data, storing the data, and sharing the data.

A global positioning system (GPS) is an embedded system that mainly uses data to provide routes and destinations. Most of us use a GPS to check on road construction, traffic, or to find the shortest route.

How does knowledge of end-to-end data management help people in their everyday life? Look at these data collections from all aspects of data management including collecting, storing, and analyzing these data. Provide a few illustrative scenarios to explain your opinion.