How Big Data Analysis is Essential to Business

Unstructured data

There’s an enormous amount of data being created every second in our world. Facebook alone has nearly two billion users producing new information throughout every hour of every day of the year. Being able to mine this data and analyze it is essential for businesses hoping to get an edge in the modern world. Opinion mining and sentiment analysis can help determine risk as well as increase customer engagement. Fuzzy name matching can provide context to data that is important in making strategic decisions. According to the International Data Corporation, however, less than 1% of the available data is ever analyzed. One way to reach that other 99% is with text mining.

The Importance of Fuzzy Name Matching

Name matching for big data is an important form of big data analysis, and is also one of the more difficult. This is because while humans prefer to use names, computers prefer to use numbers. Fuzzy name matching, however, is far easier to obtain data for than numbers, as many places have laws prohibiting ID numbers or phone numbers from being freely shared. The same is not true of names. Unfortunately, names are a difficult data point to analyze because of the existence of nicknames, multiple ways of spelling the same names, multiple people with similar names, the use of initials, titles and honorifics, translation errors, and simple misspellings.

Because fuzzy name matching is so difficult, there is no one way to do it perfectly. There are quite a few kinds of name matching tools and name matching software options, including the common key method, the word embedding method, and the list method, among others. Each method is suited to solving a different type of challenge, and a combination of methods is often the best way to ensure fuzzy name matching gets the needed data as quickly and accurately as possible.

Using Sentiment Analysis

Not only is it important to mine and match names; another key to business strategy in the digital world is being able to evaluate language for tone. This is known as sentiment analysis, and it can analyze social media, call center data, and business websites to see what people are saying and if they are talking positively, negatively, or neutrally about a particular issue or brand.

This kind of opinion mining is key to evaluating risk and interacting with customers. It allows a business to know quickly if public opinion has changed in any way, as well as identify places and products that could use improvement or promotion. Opinion mining can also be valuable in employee training, threat detection, and in keeping abreast of compliance requirements.

Currently, the text analytics market is worth about $3 billion. That number is expected to rise to $6 billion by 2020. The insights that big data analysis can provide are increasingly essential, providing valuable information to help a business grow, thrive, and stay competitive.

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