Iteration 1: Understanding of SQL Database Concepts
After receiving a letter of invitation, I took an initiative of meeting human resource officer at Pesters IT Company. I received letter and schedule plan containing various concepts about learning SQL database concepts. Iteration required taking about two weeks. According to the schedule issued by human resource officer, the first week involved an introduction to database schemas. Iteration was to be facilitated through seminars, training, and practical workshop activities. Subtask in session involved understanding physical and logical schemas. The facilitator of the session was Mr. Max, the database manager. During first half of week researcher shall be required to implement various sections involving physical schema (W. S. Max, Personal Communication, February 01, 2016). The second half of week session shall have participants understanding about the logical schema of the database.
The second week involved a training session by Mrs. Liza, the Oracle, database developer. Through the session, she was to train us on SQL concepts and commands. According to schedule concepts covered during research, the session shall involve learning three broad categories of SQL commands. Structured Query Language (SQL) involves three categories namely (P. G. Liza, Personal Communication, February 03, 2016)
- Data definition language (DDL)
- Data manipulation language (DML)
- Transaction control commands (TCC)
Through three categories interns shall understand various commands that are used to control major functions of the database which includes collecting, storing, retrieving, and processing data and information (Vainio, & Junkkari, 2014). The second half of week shall involve the understanding structure of databases such as relationships, tables, and constraints used to handle SQL databases. The session shall cover structure such as relational databases and database management systems (DBMS).
I initiated a meeting with a human resource officer. Through the meeting, I acquired a schedule plan concerning introduction to the SQL oriented databases schemas. Mr. Max introduced physical database schema and logical database schema. The physical database schema is referred as the actual storage of data and information in Oracle databases (W. S. Max, Personal Communication, February 05, 2016). It forms main storage for files, indices, and applications programs. It defines the format and structure in which data and information are stored on secondary storage devices (Papadakis, Plexousakis, & Christodolou, 2012). Mr. Max demonstrated the second schema in SQL database. In a workshop session, we learned and applied logical database schema whereby we analyzed table’s structures such as rows and columns. We managed to manipulate data and information using techniques and methods that change SQL schemas based on various constraints defined in logical schemas.
I took part in training session facile ted by Mrs. Liza. She guided us on how to use and apply various commands under data definition language. Through the session I was capable of creating, altering, and dropping tables using SQL table commands. Mrs. Liza demonstrated table syntax. Through training, she demonstrated various SQL commands used for manipulating data. Commands applied included Insert, Select, Delete, and Update. Mrs. Liza guided me on how to implement their trough syntax workshop practical sessions. Through practical operations in the workshop, Liza revealed commands involved in demonstrating commands used in controlling transactions. SQL database control statement includes commit, save point, and Rollback. Interns were able to apply syntax used in controlling and managing transactions (W. S. Max, Personal Communication, February 08, 2016).
Through study research facilitated by Mrs. Liza and Mr. Max, I have observed that operations in the database are controlled through implementation of SQL commands. Through session of introduction to the physical schema, I understood how data and information are stored and maintained within SQL database. I have realized that various database can be applied in implementing SQL language such as Oracle database, Microsoft Excel database as well as other forms of databases. Through a training session, I have understood different data control and handling techniques implemented through constraints handling. I observed that various constraints were implemented in the logical schema to control table structure of the database in a relational database. Constraints are defined at the column level, and at the table level (P. G. Liza, Personal Communication, February 09, 2016). During the training session, some of the constraints used included keywords such as NOT NULL, primary key, and referential integrity.
A session involving the implementation of SQL commands provided a better understanding of direct dealing with SQL databases. I have observed that there are various commands and statements involved in dealing with databases. Through SQL based commands database control, management, operations are easy to learn and understand. Syntax and commands applied in controlling data and information are English based thus making it easy for programmers, learners, and end users to understand easily how they are applied (W. S. Max, Personal Communication, February 11, 2016). I realized that SQL commands and statements are vital in controlling big data concepts. Commands can be used to access a large amount of data and information directly from where they are stored. Systems analysts do not require copying data and information from various sources or applications (Stonebraker, 2010).
The session implemented and facilitated by Mr. Max and Mrs. Liza was well accomplished. Through an introduction to database concepts, I have gained potential and ability to work with SQL command in managing SQL databases. A session involving control and conducting full measure of database concepts has provided high-level measures of understanding various ways in which Oracle database can be managed. The training session with Mr. Max was well covered. Concepts introduced included organizing database in different schemas. The session covered designing of tables and their columns which must be uniquely identified (W. S. Max, Personal Communication, February 13, 2016). Schemas implemented contained object schema, table spaces and data files with structures.
Upon implementing target SQL systems the various organizations operations involving analyzing, transferring, extracting, translating, and loading data and information shall be easy to audit and replicate (Mesmoudi, Hacid, & Toumani, 2016). The session also contained some areas that did not go well. Some section that never went well included designing of database concepts such as relational databases. However, research shall provide measures and parameters for covering remaining sessions. Other area that did not go well included interaction with database management systems (DBMS). The platform that links end users, clients and other applications with databases required more time of training so as to include DBMStraining (P. G. Liza, Personal Communication, February 14, 2016).Future studies and iterations shall deal with detailed concepts on models and structure of DBMS.
Mesmoudi, A., Hacid, M.-S., & Toumani, F. (2016). Benchmarking SQL on MapReduce systems using large astronomy databases. Distributed and Parallel Databases : an International Journal, 34, 3, 347-378.
Mesmoudi, A., Hacid, M.-S., & Toumani, F. (September 01, 2016). Benchmarking SQL on MapReduce systems using large astronomy databases. Distributed and Parallel Databases, 34, 3, 347-378.
Papadakis, N., Plexousakis, D., & Christodolou, Y. (2012). The ramification problem in temporal databases: a solution implemented in SQL. Applied Intelligence : the International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies, 36, 4, 749-767.
Stonebraker, M. (2010). SQL databases v. NoSQL databases. Communications of the Acm, 53, 4, 10-11.
Vainio, J., & Junkkari, M. (January 01, 2014). SQL-based semantics for path expressions over hierarchical data in relational databases. Journal of Information Science, 40, 3, 293-312.