Organizations recognize data as a critical asset. Available and reliable information is the most important resource of any business in any industry. A productive Systems and Network Administrator must know how databases and data warehouses are built and queried, and what types of information can be extracted. The professional Systems and Network Administrators sometimes must communicate with database designers and must be able to tell how data elements relate to each other, how they would like the data to be accessed, and what report they need.
There are many topics within data management; some of the more popular topics include data recovery, data modeling, data mining and data warehousing:
- Data Recovery Data Recovery is exactly what it sounds like – a way to recover important information that was lost from a computer crash, hard disk malfunction, or virus attack. No matter the scale, big corporation database recovery or single user retrieval of files from spontaneous “deleting”, data recovery is an important and necessary part of any operating system. Data Recovery software can be developed, installed and removed from existing systems to retrieve lost data or partial data and minimize damage caused to the system.
- Data Modeling Data modeling is the process of structuring and organizing data. These data structures are then typically implemented in a database management system. In addition to defining and organizing the data, data modeling may also impose constraints or limitations on the data placed within the structure. Managing large quantities of structured and unstructured data is a primary function of information systems. Data models describe structured data for storage in data management systems such as relational databases. They typically do not describe unstructured data, such as word processing documents, email messages, pictures, digital audio, and video. Early phases of many software development projects emphasize the design of a conceptual data model. Such a design can be detailed into a logical data model. In later stages, this model may be translated into physical data model.
- Data Mining Data mining involves the use of sophisticated data analysis tools to discover previously unknown, valid patterns and relationships in large data sets. These tools can include statistical models, mathematical algorithms, and machine learning methods. Consequently, data mining consists of more than collecting and managing data, it also includes analysis and prediction.
- Data Warehousing A data warehouse consists of a computer database responsible for the collection and storage of information for a specific organization. This collection of information is then used to manage information efficiently and analyze the collected data. Although data warehouses vary in overall design, majority of them are subject oriented, meaning that the stored information is connected to objects or events that occur in reality. The data provided by the data warehouse for analysis provides information on a specific subject, rather than the functions of the company and is collected from varying sources into one unit having time-variant.