What is Data Analysis?

Data analysis refers to the use of appropriate statistical analysis methods to analyze the collected large amounts of data, summarize them, understand and digest them, in order to maximize the development of data functions and play the role of data. Data analysis is the process of detailed research and generalization of data in order to extract useful information and form conclusions. ^[1]

Data analysis

The purpose of data analysis is to concentrate and refine the information hidden in a large number of seemingly disorganized data, so as to find out the inherent laws of the research objects. In practice, data analysis can help people make judgments to take appropriate action. Data analysis is the process of collecting and analyzing data in an organized and purposeful manner, and making it into information. This process is a supporting process of the quality management system. Throughout the product's entire life cycle, including the market research to after-sales service and final disposal, the data analysis process needs to be properly applied to improve effectiveness. For example, before starting a new design, designers must analyze the data to determine the design direction through extensive design surveys. Therefore, data analysis plays an extremely important role in industrial design. ^[3]

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1.List method

Use the data according to a certain rule

Using the data analysis function that comes with Excel, you can complete data statistics and analysis only available in many professional software, including: histograms, correlation coefficients, covariances, various probability distributions, sampling and dynamic simulation, overall mean judgment, mean inference, Linear, non-linear regression, multiple regression analysis, moving average and more. In the field of business intelligence, Cognos,

Data analysis has a very wide range of applications. A typical data analysis may involve the following three steps: ^[6]

1. A classic case of Wal-Mart: beer and diapers

The story of "beer and diapers" originated in Wal-Mart supermarkets in the United States in the 1990s. When Wal-Mart's supermarket managers analyzed sales data, they found an incomprehensible phenomenon: In some specific cases, "beer" Two seemingly unrelated items of "diapers" often appear in the same shopping basket. This unique sales phenomenon has attracted the attention of managers. After subsequent investigation, it was found that this phenomenon appeared in the young father. ^[7]

In families with babies in the United States, the mother usually looks after the baby at home, and the young father goes to the supermarket to buy diapers. When the father buys diapers, he often buys beer for himself, so that two seemingly unrelated products, beer and diapers, often appear in the same shopping basket. If the young father can only buy one of two items at the store, he is likely to give up shopping and go to another store until he can buy beer and diapers at once. Wal-Mart discovered this unique phenomenon and began to try to place beer and diapers in the same area at the store, so that young fathers can find both items at the same time and finish shopping quickly; and Wal-Mart can also let these Customers buy two items at a time instead of one, and get a good sales revenue, which is the origin of the "beer and diapers" story. ^[7]

Of course, the story of "beer and diapers" must have technical support. In 1993, the American scholar Agrawal proposed an association algorithm that analyzed the collection of products in the shopping basket to find out the relationship between the products, and found the customer's purchasing behavior based on the relationship between the products. From the perspective of mathematics and computer algorithms, Agravo proposed the calculation method of commodity associations, the Prior algorithm. Wal-Mart's attempt to introduce the April algorithm to the analysis of POS data from the 1990s was a success, so it produced a "beer and diaper" story. ^[7]

2.Suncorp-Metway uses data analysis to achieve smart marketing

Suncorp-Metway is a diversified financial services group in Australia that provides general insurance, banking, life insurance and wealth management services.It has 5 business units, manages 14 categories of goods, and is supported by companies and shared services. New Zealand's operating business has partnerships with more than 9 million customers. ^[8]

The company's mergers and acquisitions in the past ten years have increased the customer base by 200%, which has greatly increased the complexity of data management of the customer base. If it is not solved properly, it will have a negative impact on the company's profits. To this end, IBM Corporation Provided a set of solutions for it, the components include: IBM Cognos 8 BI, IBM Initiate Master Data Service IBM Unica. ^[8]

With this solution, Suncorp-Metway has achieved significant results in at least three areas of business: ^[8]

1. Significantly increased market share, but did not increase marketing expenses; ^[8]

2. Annual savings of approximately $ 10 million in integration and related costs; ^[8]

3. Avoid repeat mailing of the same letter to the same family and eliminate redundant systems, thereby reducing direct mailing and operating costs. ^[8]

It can be seen that Suncorp-Metway uses this solution to integrate data from multiple previously isolated sources to achieve smart marketing, which plays a very active role in controlling costs and increasing profits. ^[8]