A matrix is a standard assortment of numbers within brackets. This array represents the real world data and solves real world problems. An adjacency matrix is a rubric cube of data with n vertices creating n*n matrix. In order to stay in the competitive world, many businesses use the workplace as a powerful knowledge-sharing tool for attracting and retaining its staff. With constant change in business operations, an organisation adapts effectively, which is a crucial tool for success. In business, matrices analyze data and gain knowledge about patterns of behaviour. It also enables one determine the interactions that exist between different data, indications about the data and the relationships amongst data.

One explores all the possible dimensions of doing business in the market using an adjacent matrix. This falls in line with the core business purpose as it prepares a map of possible growth opportunities (Zook & Allen, 2001). A matrix has endpoints. Each of the endpoints is a brainstorming moment that generates adjacent opportunities and ideas for the business. These endpoints also trigger creativity. According to Zook & Allen (2004), this takes place through protecting the business by seeking growth in the areas the adjacencies show. The adjacencies imply that a business is moving to a new era while taking advantage of the existing competencies.

Adjacent matrices explore various business applications. For example, an individual may want to determine the relation between the rate of occupancy in relation to the location of a room or its type. In this case, we use adjacent matrices to analyse and carry out business research. It is also used in data mining. This takes place when analysing large volumes of data. The matrix will assist in identifying the source of data, and defines the constraints for data selection. We extract data from the available pool whilst developing a cube. The next step is to search through the data seeking trends in pricing, market characteristics and availability.

In networking, adjacency matrix in the clustering of network attacks graphs. Multiplication of the clustered adjacency matrices shows the area the attacker reached across a given network in a given number of attacks.  This provides the impact of network configuration changes on the attack. This is advantageous to an organisation as the organisation tracks the attacks present in the network as it determines the origin of the attacks. It enables the organisation be able to know the impacts on the network configurations.

In summary, it is essential to know that a legitimate business is the worthwhile reward of good business procedures and organisation. Adjacency matrices provide a variety of options for strategic growth of a business. Therefore, it is vital to apply this concept.

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