What you should know about Data Mining

February 5, 2013 in Data warehouse Info by K. Anton  |  No Comments

Data mining is becoming the real must-have tool for every business that has already faced Big Data challenge and going to leverage this technology factor. Over the past decade, Data Mining has taken its shape and techniques so now it is not just a hot trend but a valid IT field that works with ROI and marketing improvements. In fact all of us are dealing with Data Mining tens of times a day from Social Media messages to the fraud-detection algorithms that scrutinize our every credit card purchase.

The popularity of Data Mining tools is very simple – it does work as for big businesses so for mid-market enterprises. Especially today, the technologies are getting cheaper and easier, so even mid-market companies with limited IT department can afford it. But even with all these benefits and wows not all the executives have the idea how to get started with Data Mining and Business Intelligence project.

Data Mining and BI project must begin with a plan of business opportunities. Simply, make a diagram with three phases of the DM/BI. In the 1st phase find out the requirements of gathering process – make a list of opportunities that will lead to a great business impact. The most important steps in Data mining are not about technology but about understanding the business and its approaches. Have a meeting with business-oriented people and decide what will be your high-level opportunities of Data Mining project. The 2nd phase of diagram should point out what are the demands and tasks that will help to reach these goals, also mention the business analysts who will manage the data. In the 3d phase you will identify the business goals that will be met with the Big Data and BI.

Since you have done your diagram, make a draft with these questions:

– Business opportunity description;

– Expected data issues;

– Modeling process description;

– Implementation plan;

– Maintenance plan.

The good business plan and the right people will lead to the success in implementation of Data Mining Project.

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