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Big Data vs. Data Warehouse

Instructor: David Gloag
You will almost certainly have heard of big data, a popular topic these days, and you might be aware of data warehouses as well. What's the difference though? That's what we're exploring in this lesson. We'll look at each and the differences between them.

The Ever-Growing Thirst for Knowledge

There is an old adage that goes, 'knowledge is power'. And that couldn't be truer today. The need to know dominates everything. For example, have you ever wanted to know the 24-hour weather forecast, before you left the house that day? Or wanted to know the outcome of some sporting event before it starts, so you could place a wager? It is this thirst that drives us to collect more and more data, and use it to derive something meaningful. It follows then that someone would develop the means to do just that.

What is Big Data?

Big data is the area of science and technology that deals with data sets that are too large to be handled by traditional methods. For the most part, this means either by hand, or with software packages like Microsoft Excel, Access, SQL Server, and their equivalents from other vendors. The resource requirements are significant, even with powerful machines underneath. Today, normal sized data sets are pushing the boundaries of what these traditional packages can do. And that is constantly changing. Every year sees a hunger for more data, and an increase in the resources needed to handle it.

What is a Data Warehouse?

A data warehouse, on the other hand, is a centralize information repository that gathers data from many places. Businesses generally use them to report on, analyze, and make decisions on, various aspects of their operations. They are built upon traditional software packages like those mentioned before. And their resource requirements, although significant, are nowhere near that of big data. But like big data, the hunger for more information pushes resource requirements higher each year.

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