Data Analysis and Management of Steel Organization...

Data Analysis and Management of Steel Organization A steel organization is very complex in nature. In such an organization, there are a large number of units working in conjunction with each other and there are a large variety of processes taking place simultaneously at all the times, generating huge amount of data. This large quantity of data need to be coordinated, collected, integrated, and analyzed for decision making in order to ensure the smooth running of the processes and units, as well as for the proper functioning of the steel organization. Hence data plays a very important role in efficient management of the steel organization. The speed and quality of the data analysis provide ultimately the steel organization the efficiency as well as a competitive advantage. Further while the majority of the data is generated internally in the organization, some of the data comes to the organization from the sources which are external to the organization. The generated data in the steel organization are worthless in a vacuum unless its potential value is unlocked and leveraged to drive the decision making in the organization. To enable such evidence based decision making, the steel organization needs efficient processes to turn high volumes of fast-moving and diverse data into meaningful insights. The overall process of extracting insights from the large data can be broken down into five stages (Fig 1).  These five stages are (i) acquisition and recording, (ii) extraction cleaning and annotation, (iii) integration, aggregation and representation, (iv) modeling and analysis, and (v) interpretation. These five stages form the two main sub-processes namely (i) data management, and (ii) analysis. Data management involves processes and supporting technologies to acquire and store data and to prepare and retrieve it for analysis. Analysis, on the other hand, refers...