Huffman Trucking Data Warehouse Report essay

Soon after Huffman acquired 5 eastern regional carries helping the company bread its business ventures further enabling more business to thrive. Huffman trucking has grown to 1,400 employees and has more than 800 trailers on the open road providing carrier services all over the county. Along with its growth Huffman has to think about securing it data and implementing a process in order to control this data. The implementation of a data warehousing project would greatly improve the integrity of their data.

The most important aspect of having data warehousing is the fact that it allows for data storage and presentation of this data enabling executives to make sound decisions. Another important use of data warehousing is it takes the separate areas the company is divided up in and takes it all and lumps it in to one single entity. One great benefit of data warehousing is that Huffman will be able to handle server task connected to all queries which is not commonly found in all systems. Another powerful benefit of data warehouses is that they allow companies to use data modeling for querying tasks that are quite difficult for transaction processing” (Exporters 2007). Huffman trucking is already successful but by implementing a success data warehousing system hey would be able to understand and analyze all data coming in and leaving the system better and at a more efficient rate. Attached to this report is a diagram or example of what the data ware house configuration might look like when the process is fully implemented.

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Huffman trucking has to understand the full potential Of its fleet, customers, and decision making for operations in order to keep the company moving in the right direction. The data structure provided for Huffman trucking shows the different operating systems or areas that are important to the operation of the company. These areas are parts catalog, vehicle, vehicle type, maintenance description, parts purchased, maintenance work order, tire maintenance, vendors and all external data.

Each system is comprised of many categories for example: Parts Catalog: this gives the part id, description of the part, what type of part it is, quantity, when it was ordered, and the vendor it was order from. Such systems should be implemented into to the data modeling because it brings all areas of fleet management into one file. Each file is broken down into separate categories enabling the company to open only those areas that are in question.

Once this information is gathered it is then moved through what it described as the TTL (Extract, Transform, and Load) process moving into a staging area in what is known as the integration layer. At this point the data is extracted, transformed, and loaded into the data vault or the data warehouse itself where it is stored safely until it is needed for further analysis. Once the end user of the executive of the company needs this info it again goes through the TTL Process. At this point it is distributed out to the separate areas of either the data marts Or sub systems with in the main file like parts talon.

There is another area called the strategic marts and this is a analyzing stage to see what they are going to do with the data they have extracted from the vault. At this point the data is going through an exploration or data mining stage. Data mining “is the analysis of data for relationships that have not previously been discovered” (Rouse, 2014). Conclusion Huffman trucking although very successful could be more successful ad could also find areas that they might be able to enhance if they take the time to learn about data warehousing and its benefits.

The ability to manage data n a more sufficient manner can only help the company to continue its growth and might be able to find other areas to pay more attention to. Data base management is vital to all parts of the company and with the implementation of data modeling or warehousing the company will make a difference when it comes to correcting any loose ends or back tracking to find any mistakes that might happen in everyday business matters. The process of extracting data, then transforming it, to loading it I something many companies are starting to see as an important tool in the success of the business.