General Business News for July 2016

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Making Sense of Structured and Unstructured Data

For individuals and business owners alike, the way data has been dealt with, especially with the advent of computers, is through two forms – structured and unstructured data. Structured data can take the form of databases and spreadsheets delineating names and figures in columns with headers. Unstructured data, as the name implies, holds data in undefined structures including emails, social media posts, PowerPoint presentations and text messages.

With artificial intelligence’s capabilities increasing and the amount of data created every day growing, how can businesses analyze both types of data and use it to their advantage?

Considerations for Structured and Unstructured Data

While structured data is readily available to be manipulated by humans, increasing amounts of unstructured data is not. Projected to keep growing, it’s unrealistic for humans to comb through the 2.5 quintillion bytes of computer data generated every day on the Internet, according to IBM. A quintillion, for comparison against a million or billion, is 1 followed by 18 zeros.

Whether it’s weather data, videos, photos or text generated on social media, websites or forums, digital invoices or mobile data points, the amount of information on the Internet needs a way to be collected and organized for organizations and individuals to process, analyze and act upon it for their business decisions. 

How Unstructured Data is Analyzed

With artificial intelligence, unstructured data can be analyzed with algorithms. An email is a good example of how structured and unstructured data is created. It can start off with the top of the message and include the text inside the email. The structured data takes the form of the “To,” “From” and “Subject” lines. The unstructured data takes the form of the unique message written in the body of the email.

With the help of algorithms, language can be analyzed to determine what adjectives are contained and what they mean. If words such as “poor” and “service” are found, it may be able to determine how many customers are not satisfied with their service experience.

Potential Uses of Big Data for Business Purposes

Artificial intelligence has the ability to look at photos, sense location through GPS and compile social media data, which could include existing or potential customers. This offers the potential to compile demographics on where marketing efforts should be increased or decreased depending on the data results. Businesses could also use big data to analyze delivery efficiency whether they are shipping manufactured goods or a delivery service. By gauging weather, traffic, accidents, price and on-time performance data from multiple data sources, companies can analyze the most efficient shipping options.

Considerations to Make Before Aggregating and Using Big Data

While the risk of a data breach already exists, the increase of data creation and aggregation only increases the risk of data violations and misuse. Moreover, data should be anonymized by removing identifying markers such as age, gender or race, so that employees do not intentionally or even unintentionally make unethical or illegal decisions when it comes to hiring or lending. It’s also important to evaluate data integrity and the accuracy of the algorithms performing the analysis.

As more and more data is created, the ability for businesses to analyze and act upon it for future decisions increases. However, only the future will tell how extensively businesses can make sense of their structured and unstructured data.

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