Small business with big data? The data will yield!

When the concept of data was first known, it seemed that people thought the industry was just for corporate users. Large data-related technologies are changing, but the complexity and implementation costs are also staggering. Many small business users appear to have encountered large data problems on the surface, but eventually found that the implementation costs are already beyond their reach, and even the salaries of data analysts can not afford them. However, large data is actually the same as many other technologies, and is not a "patent" for large enterprises at all.

Small is not equal to no data

Larger companies tend to have larger dataset objects, which makes it easy for them to become "candidates" for large data industries. But most of these big-business data are scattered across a number of different systems or platforms, requiring more budgets and stronger infrastructure to support, and of course, data quality. Small enterprises do not represent no data, small-scale companies usually relatively concentrated data, easy to unified management, some growth enterprises even independently developed some information systems, data capture, mining processing.

To get valuable information out of the data, the first step is to have the data available, or even to say that it is half done. As a result, growth companies may not be spending large amounts of data upfront. When large and medium-sized companies are busy concentrating on their fragmented and massive data, small business executives can easily find business value in their existing data.

In addition, as with ERP, CRM and other enterprise-class software platforms, large data is rapidly moving towards commercialization. This is the same reason anyone with credit cards can successfully order an enterprise-class cloud computing platform or fortune IT service in just a few minutes, and large data analysis will not stay in the Enterprise Server room forever.

Large data can not only look at the capacity

Large data, the most intuitive embodiment of the large storage arrays and memory-type database technology, in these technical investments are often assumed to be unavoidable in large data management of the necessary expenditures. However, large data is also associated with build speed and real-time analysis. Speed is related not only to the technical function, but also to the speed at which the data is being promoted and the speed with which the business managers make decisions based on data analysis.

In small businesses, it is generally easier to develop and implement unified management processes and systems to make decisions faster using effective data, compared to large and medium-sized enterprises that have little advantage in these areas. For many growth types, the use of flexibility and speed advantages to compete with large enterprises is indeed a viable strategic solution. While industry giants are still struggling with the $ millions of worth of big data hardware, growth companies have been able to use open source or cloud computing software tools for more basic analytical work, and to take action on data analysis results before their projects are approved.

Mentality and consciousness are more important than hardware and software technology

Like all new technologies, the successful implementation of large data depends more on the acceptance and determination of transformation and change than on the purchase of appropriate hardware and software products. From a large data point of view, if a company lacks the awareness of collecting business-related data, can not find ways to expand business through data analysis, not enough enterprise to make the right decision according to the analysis result, then the scale of the business is even bigger, All its capital investment and human resource advantages will become meaningless.

(Responsible editor: The good of the Legacy)