Data Warehousing Mining

Data warehousing mining is the process of accessing a centralized database for the purpose of business analysis and discovery.  In data warehousing mining business data is taken from multiple sources and is stored in a central repository where the data warehousing mining takes place.  Data warehousing mining has traditionally been the domain of large organizations, but smaller businesses are finding that the tools and resources are now available to make data warehousing mining accessible even to the most modest business.          

Does Your Business Need Data Warehousing Mining?

Just a few years ago the answer to this question was directly related to company size.  Smaller businesses did not have the financial ability to implement data warehousing mining, making it an exclusive enterprise solution.  With the introduction of open-source databases, low cost data integration tools like EMANIO Unite! and affordable data mining software like EMANIO Insight!, however, data warehousing mining is now a question of need vs. cost.  The easiest way to answer the question of need is to consider the amount of data your business owns.  Data warehousing mining is an ideal way to take vast volumes of data from places like CRM, ERP, Accounting and other systems, in order to create a clearer picture critical business trends.  The better decision on your need for data warehousing mining then is related to vision.  Specifically, do you need to have greater insight into what drives your business? If the answer to that question is yes, you may need data warehousing mining.

Getting Ready for Data Warehousing Mining

Before you begin to consider what you will need for data warehousing mining, however, you need to ensure that your business and your systems are ready for data warehousing mining.  In the world of data warehousing mining the old saying of "garbage in, garbage out" is certainly true.  Most businesses pay little attention to how "clean" or "complete" their data is until after they have embarked on data warehousing mining.  A better way to prepare is to consider these issues before a data warehousing mining project is started.  Specifically, how much dirty data do you have? dirty data consists of incomplete fields, fields with improper entries and other typographical mistakes that can pollute a data warehousing mining project.  In addition you should consider the "completeness" of your records - for example, how much demographic data do you have on your customers?  The more data your records have, the more effective your data warehousing mining will be.

Data Warehousing Mining and the Small Business

Once you have identified that you have the right data for data warehousing mining, the next step will be to consider the tools you will need to implement data warehousing mining.  At the core of a data warehousing mining project will be the database used for the data warehouse.  With open source tools like My-SQL as well as low-cost database systems, the options for a core database are plentiful.  Additionally you will need access to extract, transform and load (ETL) tools like EMANIO's affordable Unite! product, to help you populate your data warehousing mining project with data from your multiple sources.  Once you have your data set up it's time to use reporting and analysis tools.  Products like Crystal Reports and EMANIO's Insight! data mining tool will give you affordable means of creating a successful, low-cost data warehousing mining project.

Using Data Warehousing Mining for Success

Now that you have created your data warehousing mining project the next focus will be on best use.  To get the most from data warehousing mining, the key will be to ensure that the "right" data is in your data warehousing mining repository.  To ensure this your best bet is to consider what key metrics are important to your company?  The data related to those metrics will need to be part of your data warehousing mining.  For example, if average days outstanding (DSO) is a key measurement, having data related to sales and the days each sale requires to be paid will be a critical part of your data warehousing mining.