Question 1
(a) Define the following:
- Data is raw information such as symbols or alphabets.
- Information is accurate and timely data that is organized for a particular purpose and is presented in a manner that has a meaning and enhance understanding.
- A database is a collection of information organized for fast search and retrieval by computer.
- A database management system (DBMS) is a software application designed to interact with database, users, and other applications to obtain and analyze data (Kedar, 2009).
- A database system environment is a system of components including users, data, software, database handling techniques, and hardware which regulate group of data and data use and management.
(b)
Storing and retrieving data and information involves a database which is accessed via a database management system. With the DBMS, data can be inserted into the database and organized in a presentable way. The DBMS also is used to retrieve information stored. The process of data storage and retrieval relies on the database system environment whose components facilitate data entry and access.
(c) Applications supported by database technologies.
Some applications supported by database technologies include:
Social media sites - Sites such as Facebook and LinkedIn relies on database technologies to store user details.
E-commerce sites – Sites such as Amazon and Walmart use database technologies to store product catalog and user details.
Online Library – An online library is powered by database technologies which allow storage and retrieval of digital copies of books.
Question 2
Describe DBMS (MySQL):
1. Technical details
MySQL runs on all operating systems including LINUX and Windows. It can be used in many applications and is popularly used by web-based applications. It’s a light-weight application that is included as a component of LAMP, WAMP, and XAMPP – enterprise stack used for web development.
2. Features
MySQL has a cross-platform support and supports a wide subset of ANSI SQL 99. It supports stored procedures, triggers, online data definition language, updatable views, information schema, and cursors (MySQL, 2007). The DBMS has a performance schema for monitoring proposes and a several SQL model options that control runtime behavior. MySQL supports distributed transaction support and ACID compliance when InnoDB is used. Other features supported by the DBMS include full-text indexing and searching, Sub-SELECTs, query caching, SSL support, Built-in replication support, partitioned tables, commit grouping, and native storage engines.
3. Running environment.
MySQL can run in different operating systems including MAC, Windows, Linux, and UNIX. It supports multiple users as various users can access the database while maintaining ACID compliance. MySQL is a key component of open server web development stacks such as LAMP and XAMPP.
(b) MySQL commands for in storing, retrieving, updating, and deleting data.
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Store
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Retrieve
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Update
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Delete
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Data
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INSERT INTO table1 (name, age) VALUES (‘Myname’, 12)
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SELECT * FROM table1
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UPDATE table1 SET name=’James’ WHERE ID=1
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DELETE FROM table1 WHERE ID=1
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Question 3
(a) Define the following:
- Data modeling is the process of representing a system design as a diagram that includes texts and symbols indicating how data flows.
- A data model is a fundamental entity that includes attributes, entity types, relationships, integrity rules, and define how data is processed.
(b) Importance of concepts from 3(a) to database design
For a database design to be developed, data modelling has to be involved as it represents data flow in a system which assists in mapping key entities, attributes, and relationships between the entities that are incorporated in a data model.
(c) Define the following:
- Entity-Relationship (E-R) model is a way of representing relationships of objects (Thalheim, 2013).
- Relational database model is a data management approach that involves a structure and language representing data in terms of tuples grouped into relations (Paredaens, 2012).
(d) Relationship between these two models from 3(c)
E-R model is a graphical representation of the relational database model while the latter is an implementation of the former. Converting E-R model to relational database model involves creating tables and columns as graphically depicted. To convert relational database model to E-R model, tables, columns, and relationships have to be graphically be represented as entities, attributes, and relationships respectively.
Question 4
Gathering business rules is the first step of database design that involves defining rules based on data is perceived and used which is dependent on the functions of an organization (Maciol, 2008).
E-R modeling involve graphically representing the entities and attributes identified after developing the business rules.
Relational modeling involves implementing E-R model developed in the previous step.
Normalization is the last step which involves organizing the tables and columns created to reduce data redundancy.
Question 5
(a) Big data is a large data set that firms mine and analyze to gain insight into patterns that can lead to business gains.
(b) Challenges the database technology is facing regarding Big Data
The volume of Big data creates challenges related to storing and processing it. Trends such as social media, ecommerce sites, and Internet of things generate a lot of information that may be used by any organization. Due to the size of the data generated, organizations may face data storage problems especially if they lack the hardware equipment and software required to obtain and process the data (Tole, 2013).
Various data sources associated with big data creates data integration problems. Since big data comes from different sources such as social media streams, documents, etc., combing this data can be extremely difficult. Additionally, since organizations get similar data from various systems and the data may differ, the data obtained have to be validated. However, the process of validating each record obtained is difficult as organizations need robust systems that ensure the accuracy of the process (Nasser, 2015).
(c) Current technologies that deal with Big Data.
Some of the technologies available that deal Big Data include:
- Search and knowledge discovery tools support extraction of insights from data residing in different platforms and systems (Freitas, 2013).
- Predictive analytics allow firms to discover and use predictive models by analyzing data sources to mitigate risk.
- Stream analytics applications filter, analyze, and organize data from various live data sources in different formats.
- Data virtualization delivers information from different sources in real-time.
References
Freitas, A. A. (2013). Data mining and knowledge discovery with evolutionary algorithms. Springer Science & Business Media.
Kedar, S., 2009. Database management system. Technical Publications.
Macio?, A. (2008). An application of rule-based tool in attributive logic for business rules modeling. Expert Systems with Applications, 34(3), 1825-1836.
MySQL, A. B., & MySQL, A. B. (2007). The world’s most popular open source database. MySQL AB.
Nasser, T., & Tariq, R. S. (2015). Big data challenges. J Comput Eng Inf Technol 4: 3. doi: https://dx. doi. org/10.4172/2324, 9307(2).
Paredaens, J., De Bra, P., Gyssens, M., & Van Gucht, D. (2012). The structure of the relational database model (Vol. 17). Springer Science & Business Media.
Thalheim, B. (2013). Entity-relationship modeling: foundations of database technology. Springer Science & Business Media.
Tole, A. A. (2013). Big data challenges. Database Systems Journal, 4(3), 31-40.
