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What is Big Data?

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All news publications talk about big data. However, to fully capitalize on this Information Age revolution, it is important to understand the basics. What is big data for hotels? Here it is expressed in laymen:

Big data refers to datasets that are so large, complex and unstructured that they are difficult to process with traditional data management tools.

The term may also refer to the tools and methods used to analyze unstructured data and multi-structured data.

What is so revolutionary about Big Data? Data is now available as never before Volume, variety and speed So,

1 volume: Data is bigger than ever. It is estimated that 2.2 million exabytes of new data are created daily. That's enough to fill over 5 million DVDs.

2 diversity: It comes from several points of contact, ie data comes from many different sources and interaction points.

Third speed: Data changes quickly as new data is constantly being created and used.

Big data sources include social media posts, online reviews, and transaction information. Useful big data for hotels can be a great amount of information about every guest being made usable.

Suppose a guest named Chuck was in your hotel. When he arrived, Chuck tweeted about your hotel, ordered a favorite beer from the bar, and demanded hypoallergenic pillows upon check-in. Imagine you could collect all this information in one place. Imagine, the next time Chuck stays at your hotel, his room will be fitted with the right pillows before he even asks.

Imagine hoteliers collecting information about each guest who checks in AND analyzes the data in real time. Hoteliers could spot trends and possibly develop the ability to predict guests' wishes before they even know they want it.

What is the problem?

The challenge with big data is that there are so many different places that it is very difficult to capture and analyze.

In our example, your hotel might find out something about Chuck because of its online behavior and interactions with employees. However, the data comes from Twitter, a cash transaction and personal interaction with the front desk. And the next time Chuck stays with you, he decides he needs extra towels. So, your data on Chuck comes from multiple touch points (diversity), they change quickly (speed), and if you want that data for every guest in your hotel, that's a huge amount of data (volume).

To complicate matters, internal hotel data is often stored on separate software platforms. Guest feedback, reservation and marketing data are not yet integrated. Traditionally, IT's job is to store and access data, and data analysts need to find actionable insights. However, with today's unstructured data, using data without the right tools can be difficult.

Big data is also a challenge for brands that deal with consumers in terms of consumer expectations. Consumers, especially millennials, increasingly expect an ultra-personalized experience. Traditional methods of data analysis and implementation are falling quickly.

The good news?

The right tools, such as sentiment analysis, will become available quickly. And it's not just the availability of the right tools. These tools are also easier to use for the average person. As a result, more and more data becomes available over time without the help of IT or data analysis experts.

Big Data also offers exciting ways to revolutionize the customer experience. For example, Kimpton and Marriott are already Updating their loyalty programs to meet consumer expectations. The Kimpton program records and records personal interactions with employees. Over time, the guest profile develops Custom Stay Preferences. Eventually, Kimpton will learn to anticipate the needs and tastes of its loyal guests, creating the potential for targeted surprise and enjoyment, like a favorite snack that is automatically brought to the room at check-in.

The programs at Kimpton and Marriott are a good start. Ideally, however, all guest data will one day be integrated on a simple platform, allowing hoteliers to make the most of big data.

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The post What is Big Data? first appeared on Revinate,



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