By: Haytham Abdel-Qader

Topics in Data Management include: I. Data analysis II. Database management system III. Data modeling IV. Database administration V. Data warehousing VI. Data mining VII. Data quality assurance VIII. Data security IX. Data architecture

Data analysis is the process of looking at and summarizing data with the intent to extract useful information and develop conclusions. Data Analysis as a process plays a significant role on an important level and is used in: ________________________________________________________________  Nuclear and particle physics, In nuclear and particle physics the data usually originate from the experimental apparatus via a Data acquisition system.  Social Sciences,Qualitative data analysis (QDA) or qualitative research is the analysis of non- numerical data, for example words, photographs, observations, etc.  Business intelligence ( BI),dates to It refers to technologies, applications, and practices for the collection, integration, analysis, and presentation of business information.

(DBMS) is computer software designed for the purpose of managing databases. Typical examples of DBMSs include Oracle, DB2, Microsoft Access, Microsoft SQL Server. A (DBMS), Is used by over 90% of all people using a computer, a Familiar example is Microsoft Access, as mentioned above. _________________________________________________________________  “Attribute Management System" where attributes are small chunks of information that describe something. For example, "color" is an attribute of a car.  Query ability.  Relational DBMS.  SQL DBMS.

 Taking Microsoft Access as an Example ; Query Ability Relational DBMS.

Taking Microsoft Access as an example for SQL use Structured Query Language (SQL)

Data Modeling, is the process of creating a data model by applying a data model theory. A data model theory is a formal data model description. When data modeling, we are structuring and organizing data. These data structures are then typically implemented in a database management system. ____________________________________________________________________________________ There are 3 Parts ;  The structural part: a collection of data structures which are used to create databases representing the entities or objects modeled by the database.  The integrity part: a collection of rules governing the constraints placed on these data structures to ensure structural integrity.  The manipulation part: a collection of operators which can be applied to the data structures, to update and query the data contained in the database.

A (DBA) is a person who is responsible for the environmental aspects of a database. _________________________________________________________________ In general these aspects, include;  Recoverability - Creating and testing Backups  Integrity - Verifying or helping to verify data integrity  Security - Defining and/or implementing access controls to the data  Availability - Ensuring maximum uptime  Performance - Ensuring maximum performance given budgetary constraints  Development and testing support - Helping programmers and engineers to efficiently utilize the database.

(DW) is the main repository of an organization's historical data, its corporate memory. It contains the raw material for management's decision support system. The critical factor leading to the use of a data warehouse is that a data analyst can perform complex queries and analysis, such as data mining, on the information without slowing down the operational systems. _________________________________________________________________________ Extract, Transform, and Load ( ETL) is a process in data warehousing that involves  Extracting data from outside sources, transforming it to fit business needs (which can include quality levels), and ultimately  Loading it into the end target, i.e. the data warehouse.  ETL is important, as it is the way data actually gets loaded into the warehouse.

Data warehouses enhance end-user access to a wide variety of data. Decision support system users can obtain specified trend reports, i.e. the item with the most sales in a particular area within the last two years. Data warehouses can be a significant enabler of commercial business applications, particularly customer relationship management (CRM) systems. There are many advantages to using a data warehouse, some of them are:

The principle of sorting through large amounts of data and picking out relevant information. It is usually used by business intelligence organizations, and financial analysts, but it is increasingly used in the sciences to extract information from the enormous data sets generated by modern experimental and observational methods. "the science of extracting useful information from large data sets or databases“

1- Acquiring Different forms of Data from large variety of sources. i.e. Sensors, observations, diagrams, statistical info. Etc. 2- Processing the Acquired data for, required and relevant needs, then this data will be sorted in groups according to the relevancy of the issue at hand. 3- The relevantly grouped & processed data, will be further analyzed by, a (DBA) for a specific use or to store in a (DW), Data analysts and in regards to scientific experimentation, by scientists.

Notable uses of data mining  - Data mining has been cited as the method by which the U.S. Army unit Able Danger supposedly had identified the September 11, 2001 attacks leader, Mohamed Atta, and three other 9/11 hijackers as possible members of an al Qaeda cell operating in the U.S. more than a year before the attack  - It has been suggested that both the Central Intelligence Agency and their Canadian counterparts, Canadian Security Intelligence Service, have put this method of interpreting data to work for them as well

(DQA) is the process of profiling the data to discover inconsistencies, and other anomalies in the data and performing Data cleansing activities to improve the data quality. These activities can be undertaken as part of Data warehousing or as part of the Database administration of an existing piece of applications software.

 Data Security is the means of ensuring that data is kept safe from corruption and that access to it is suitably controlled. Thus data security helps to ensure privacy. It also helps in protecting personal data. This is done by following the Data protection Act (DPA).

Data Architecture : is the design of data for use in defining the target state and the subsequent planning needed to hit the target state. Data Architecture is one of the pillars of Enterprise Architecture and handshakes with its peer pillars of Business Architecture, Application Architecture and Integration Architecture.  Enterprise  Technology drivers  Economics  Business policies  Data processing needs