Introduction and Methodology

Introduction

The study research intends to learn about operations, significance and development of IBM's big SQL database. The study shall focus on defining the SQL query engine that should be applied for operating Hadoop database. The research study objective is to understand how to integrate big SQL databases that applies Map Reduce to run within existing organization’s databases. The research intends to facilitate effective management and controlling of the Hadoop Distributed File System, big data analysis, and concepts of cloud computing through use of read only queries and the Hadoop database engine (HBase) (Han, Yonggang, Tat-Seng, & Xuelong, 2014). The research study aims at effective and efficient understanding of transactional queries that are applied to perform reads and writes of data on SQL databases.

The reason for conducting this research study is to facilitate needs and requirement by many industries, companies, and organizations on handling data and information. The research intends to respond to the demand for more corporate friendly database analytics by providing SQL based database systems (Jason, & Sean, 2013). The study shall focus at providing a full SQL database query engine capabilities and significant performance improvements on the existing Hive database systems. The study shall design systems are that allows full SQL queries to analyze data and information across data warehouses, data sets, and other database systems through performing data mining. The proposed Hadoop databases shall facilitate effective operstions using database systems for entire acquisition of hybrid approaches. The study intends to incorporate use of new SQL queries at a scale that makes big data analytics accessible by several people in the enterprise. The system shall ensure all operations can clearly fit in the existing workflows (Han, Yonggang, Tat-Seng, & Xuelong, 2014).

The organization problem that shall be solved by current systems includes providence of systems that can manage entire system for coordination of activities within an organization. One of the major operstions improved within organizations include improving the existing methods of modifying database tables and index structures. The old types of databases such as the use of NoSQL databases ion most of industries and commercial agencies excludes applications of Structured Query Language (Holanda, & Souza, 2016). The structure of such databases has made coordination and handling of increasing data and information in organizations to be difficult. To improve the existing issues in handling, monitoring, and surveillance of organizations sensitive data, the research shall provide ways of incorporating Hadoop database systems. The big data concept shall be supported through designing structures for adding, updating, and deleting rows of data and information within an organization (Han, Yonggang, Tat-Seng, & Xuelong, 2014). The improvement that shall be incorporated shall enhance better performance in retrieving subsets of data and information from within a database for effective and efficient transaction processing. The Online Analysis Processing (OLAP) tool shall be installed in the researched systems to enhance embedding of analytics applications within the SQL database (Jason, & Sean, 2013). The event viewers and systems log analysis shall be integrated within SQL database for enhancing systems security. SQL queries and other SQL operations shall be coded in the system to facilitate effective utilization of commands that shall be written in statements. The most common SQL statements that shall be applied shall include the application of select statement, add statement, insert statement, update statement, delete statement, create statement, alter as well as truncate statements.

History of Action Research

Action research methodology was developed by social scientists. It was applied by Kurt Lewin in the early 1940s in improving different social, cultural, and political situations within the society (Styhre, & Sundgren, 2005). He also applied it in other areas of jurisdiction such as education, philosophy, science, and psychology. The Kurt Lewin’s action research methodology is a scientifically based characterized by a continuous spiral process. It involves in identifying social problems through collaborating with experts from social environments. Lewin research involved a collaborative analysis that was composed of collective team, audiences, as well as members of society. Kurt Lewin’s action research methodology is composed of four iterative steps comprising of cycles that has planning stage, action stage, observation stage, and reflection stage (Styhre, & Sundgren, 2005). In most of current activities, action research is widely applied in creating a strong research analysis by students, developing new plans in design and development stages, and facilitating step by step coordination and development of normal operations in daily life. Act ion research methodology is also applicable in developing and discovering necessary changes for improving existing status in industries, companies, organizations and welfare institutions. The study research has been applied as one of the major category for developing and building other scientific methodologies such as Agile (Styhre, & Sundgren, 2005).

Action research is a collaborative research methodology applied for facilitating collection of data and information used to define social problems within a social setting and organization. Action research is therefore a process of learning while researchers are taking action (Styhre, & Sundgren, 2005). It is a study method that facilitates participants to define social challenges within a social organization or industries to ensure that a change can be implemented using the best and appropriate solution. Basically it is a step by step procedure that utilizes a particular variable that determines if changes can be applied on the current system or shall more research is required.

Step by Step Action Research Methodology

The initial step in action research involves identifying a problem defining a plan that develops and implements a particular change based on the specific idea. During the planning stage the most appropriate ideas are suggested then most economical and supportive idea is determined through conducting a feasibility study (Styhre, & Sundgren, 2005). All costs are applied which are meant to accomplish particular solution at lowest cost and more effectively. The second session involves taking action which is incorporated in the study in real life to bring changes. The third operation involves carrying out the verification and validation processes that are meant to check if the implemented solution provides and accomplishes intended action. The fourth and final iteration cycle involves the process of developers reflecting on system improved by checking for any desirable change that may be applied or done to achieve a perfect system. The system has to be integrated with the rest of changes for improved performance (Styhre, & Sundgren, 2005)

Justification of Action Research

Action research methodology will be applied in this research study as one of most appropriate for improving commerce operstions using SQL databases. It shall supports step by step learning process through considering each variable of change at a given time. It supports the procedural, development of projects allowing each step to be implemented separately. The repetitive nature of methodology shall enable easy making of reviews especially technological based ideas and suggestions. It will facilitate easy analysis of both traditional and modern technologies that shall facilitate and support all forms and methods of collecting data. It is an open methodology that clearly works best with scientific techniques such as modular programming, Systems Development Life Cycle (SDLC) among other development techniques (Peffers, Tuunanen, Rothenberger, & Chatterjee, 2007). Through the methodology researchers can easily apply compatibility system, scientific standards as well as methods for transferring data and information across multiple databases. The methodology can easily incorporate any new project idea through the agreed procedures of collaboration, inquiries, and consulting. Action research methodology involves all users, stakeholders, managers, directors, and other support teams.

Significance of Action Research

Action research methodology is most suitable in understanding SQL database systems requirements. It is the best methodology for enhancing understanding the SQL queries, the appropriate technical practices and best troubleshooting, repairing and maintaining operations. Action research helps in facilitating effective training among participants to enable easy discovering of the best ways of acquiring skills, experience, and knowledge. The methodology allows best professional methods of fixing and collecting weaknesses on existing systems by easily embedding and integrating new models, structural designs as well as new technology inventions (Peffers, Tuunanen, Rothenberger, & Chatterjee, 2007). The researchers shall have best platforms for enhancing new innovations in SQL technology. New ideas such as the big data support databases such as Hadoop and internet of things can best be understood through action research.

References

Jason L., & Sean G. (2013). The hot new technology in Big Data is decades old: SQL. The decades-old database technology is staging a comeback. Retrieved from: https://arstechnica.com/information-technology/2013/07/the-hot-new-technology-in-big-data-is-decades-old-sql/

Holanda, M., & Souza, J. A. (2016). Query Languages in NoSQL Databases.

Han, H., Yonggang, W., Tat-Seng, C., & Xuelong, L. (2014). Toward Scalable Systems for Big Data Analytics: A Technology Tutorial. Ieee Access, 2, 652-687.

Styhre, A., & Sundgren, M. (2005). Action Research as Experimentation. Systemic Practice and Action Research, 18, 1, 53-65.

Peffers, K., Tuunanen, T., Rothenberger, M. A., & Chatterjee, S. ( 2007). A Design Science Research Methodology for Information Systems Research. Journal of Management Information Systems, 24, 3, 45-77.

Sherry Roberts is the author of this paper. A senior editor at Melda Research in