Data Warehousing and Data Mining

Order from us for quality, customized work in due time of your choice.

Introduction

Information technology is growing every day, with new things that we can do with it to make life easier. Growth of IT has caused us to change the way we handle data from our businesses. Today managers have to make a decision on what to do with the data they have in their firms. To make these decisions, a manager has to be well informed on the advantages of having huge data banks and how he can use it to transform his firm. Thus the importance of data to a firm cannot be overlooked, especially data that is generated by the firm itself. Data warehousing is a profitable venture only when a firm knows the worth of its data. This paper will present new insights on business data and how a firm can use it for its benefits.

Data warehousing

Most people are familiar with a database, maybe the concept of a database and how it works or have heard the word database in conversations. To understand the concept of data warehousing, you must be familiar with databases. So, a database is like a store, where all data is kept in a particular order. All data that is entered in a database is stored in groups, using a particular relation.

Data warehousing uses the same concept of as a database, however more security measure are taken in a data warehouse. A unique database is created for major business purposes like analyzing data to get a trend and understand sessions.

Current trends and benefits of data warehousing

The main purpose of a data warehouse is to store data which is used for business analysis and in making the right managerial decisions. Data warehouses are an integral part in data analysis for the business, today a business stands a chance to save its operating costs using a data warehouse. Instead of conducting the same survey every year, a team can conduct one survey and have it stored in digital format. This survey will be analyzed at different angles and important managerial decisions can be made from it.

Managers now have a chance to access business data flexibly, and this data is not manipulated. The data is extracted from data sources by an independent system, this shows that the data is credible and can be used to make important decisions.

The main advantage of data warehousing is that data access is easier and flexible but at the same time it is secure. Look at it this way, a manager who does not have a firm understanding on how databases work can access information from them and make a decision without involving a number of workers to assist him.

Businesses have a chance to improve their strategies after they implement data warehousing. Business strategy is formulated by analyzing data from the past, this will now be possible. Different levels and departments of a firm can easily access each others data in a data ware house.

Data warehousing will bring a new perspective to your firm; data will be easily accessible but at the same time not manipulated thus credible. The main worry about data that is easily accessible by a firm is its credibility. Managers dont have to worry about that when implementing data warehousing.

Data Mining

This is comparing trends or patterns in large data banks to understand the relation. In business it is the comparison of large customer data sets to understand how customers respond to different things in order to come up with marketing strategies.

Data mining is important for data comparison. The concept works by obtaining data from a large data set and making it understandable, getting the particular details that you requires or that are useful to you from a data bank. A data bank is a place where a lot of data is stored; data mining helps you get the relevant information from a pool of so much data.

Why should a business conduct data mining?

The main business advantage in data mining is creating a base for comparison. It is not a specific system that is created to conduct data mining. A business goes back to the data that it has collected over a period of time.

Lets say sales records for the last six months, a company goes back to these records and learns who buys what from them. The business team is also able to learn what items are bought at certain times and at what prices do customers buy the items in large numbers. Such information is very important for a business to strategize on its marketing methods and supply method. They are able to learn what items to make available or to stock at what time seasons.

A business goes back to its records to obtain data and interpreted it. The advantage is that the firm has obtained all this data for free and they use it to increase sales and come up with new strategies. This is data that would have been deleted but now the business recycles it.

Often when a firm collects data from customers, they use it for a very short time, maybe only to perform a particular task. If the data was collected from a survey, the firm only uses it for analysis and dumps it or puts it in the archive. Now a firm has to maintain all its records because every piece of data is important.

Data mining for a firm is now as important as recycling, old data is as good as new data. A firm can implement data mining by installing software that goes through all their data gathering information for them. The software will help in making work easier; it works faster and requires less people to operate. I am not an advocate of downsizing or laying-off workers but with data mining, fewer workers will be required to conduct data searches. These workers can be assigned tasks where they will be more useful.

Examples of companies that use data warehousing

American Airlines

They use data ware housing to increase their sales by reducing the number of forged and fake airline tickets. Data of the genuine airline tickets that are generated by the company is made accessible to all departments in the company. This data cannot be altered by any person; it is used only for reference by workers to know the genuine tickets. This system enables the company to know which tickets they have sold once and cannot be used again and also which tickets they never sold.

With data warehousing the company is able to use the data they have to their advantage profitably.

Sears

The company aimed at increasing its storage space, to have all data that it collects in one central storage point. Creating a central storage point enabled them to create a data warehouse where they stored all data. This was easily accessed by managers and other workers who were interested in it. It was also not manipulated, thus it was credible to use in making business decisions.

This gave the store a chance to compare data from different geographical locations but was stored in one point. They were better placed to understand what their clients wanted and they were able to provide it at the right time.

Architecture used in data warehouses

Enterprise warehouses

This is a data store for all the information relating to the firm. It collects information which is generally linked to the firm, no specifics.

Virtual Data Warehouse

Many databases are put together to form one large data resource center. It becomes a data ware house because it combines different sources of data for information analysis.

In these architectures there are different models which are used to implement them;

A data model is a system for data flow; how data comes in and out of the ware house is presented by a data model. Models are presented in levels from the conceptualization to the actual implementation.

The conceptual level of a data model is where the idea and relationships between data is established. No implementation is made, however this level provides the details for design.

The logical level is where the data is analyzed and described to create a relationship which is used in the data warehouse. All data that will be in the data warehouse must be identified and a logical relationship established. How is one data item related to the other, this is what this stage seeks to establish.

The physical data model is the final stage. It is similar to implementation, as the data warehouse is now put into motion. This is the last stage, these stages are procedural, and you cannot do one before the other.

Optimization techniques for data warehousing and data mining

The company has already taken the first step by implementing the use of a data base. To optimize this, now data must be protected. The database provides for that. The company should store all its data in the databases that it runs; this will be the central point of storage i.e. the data ware house. Managers can access the data and use it to learn business trends and improve practice.

For data mining, the company will have to purchase the software which will assist them in the process. All data that is collected by the company should be stored and never disposed because it is valuable. The software will assist in data analysis and comparison. It also helps in making data searches easier for the firm.

In conclusion

It is time to use the available data resources to improve our management skill and decision making. The firm has a huge resource of data from its clients and should use it to its own advantage. Recycle your data and save the cost of searching and conducting surveys in your business.

References

Han, J., & Kamber, M. (2006). Data mining concepts and techniques (2nd ed.). Amsterdam: Elsevier ;.

Hobbs, L. (2005). Oracle Database 10g data warehousing. Amsterdam: Elsevier.

Munnelly, B., & Holden, P. (2002). Databases. London: Prentice Hall.

Order from us for quality, customized work in due time of your choice.