Thousands of businesses rely on data mining techniques to manage the information they receive every second. From retail operations tracking their customers' purchases to financial services firms looking for the next big stock trend, data mining has become an invaluable tool. Many firms have filled this need by starting their own data mining operations. However, with increasing concerns about personal privacy and online security, data mining operators must exercise caution when beginning their new ventures.
Finding Business Niches
A major part of starting a successful data mining business lies in finding businesses and industries that lack the internal resources to do their own data tracking. Many small businesses fail to implement data mining techniques, which can leave them vulnerable to changes in customer taste, market economics or technological innovation. Data mining businesses are especially well-equipped to find and exploit under-served business niches, as they have techniques to examine data and spot trends in industries where they can leverage their knowledge for increased growth and profitability.
Data Mining Techniques
A strong grasp on data analysis tools and techniques will also determine the path that the startup data mining business will follow. The tools a data mining startup uses to analyze trends in financial data can be vastly different than those used by retail store operators to track customer purchasing patterns, so selecting from different data mining techniques often will determine the types of customers the startup will pursue. For instance, the company can develop its own custom-made software for its clients, or use a third-party solution, such as SAS.
Data Privacy and Security
While the principles of data analysis focus on examining aggregate data, a data mining company also should take steps to protect users' personal data. The process of creating a startup data mining business should include the study of data protection and security methods. A major concern for data mining companies in recent years has been the laws surrounding data privacy. As the laws attempt to catch up to the technology, many users are worried about how their personal data will be used. Addressing those customer fears is key to winning business.
Data mining startups can use in-house "alpha" and external "beta" users to test the reliability of their programs and to measure the capabilities of their systems. The company can conduct the tests during its startup period to find issues with their systems in a controlled environment. These tests will ensure that the startup has built a solid data mining methodology before making its initial presentations to potential customers.
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