Big data, the latest buzzword of the new data era, has been gaining traction in the United States for years.

But what exactly is it and what does it mean?

Here are five facts you need to know.

(Sarah Parnass/The Washington Post) –Big data is a new term for big data that involves big data processing, data analytics, big data tools, and big data products.

It’s all about big data.

What is big data?

Big data is an increasingly sophisticated collection and analysis of large amounts of data.

Big data means that it has become so complex that its value is often underestimated.

That’s why big data has been the focus of much media coverage since its inception in 2010.

It involves the use of data to analyze big data in ways that might not be readily apparent.

But there’s more than one definition of big data and the key point is that it encompasses a range of different ways in which large amounts or vast amounts of information can be analyzed.

So, for example, you can use big data to identify trends and patterns in the behavior of people or groups, but you can also use it to analyze the patterns of economic activity.

So what does big data actually do?

For a start, big technology companies have been developing big data systems and products for decades.

For example, Amazon’s Alexa has become a popular voice-activated digital assistant that can predict what you’re going to want to do next.

Apple’s Siri is another smart assistant, and Google’s Google Now can find the best places to buy food and gas, among other things.

These products are built to solve a specific set of problems.

For instance, they can provide more precise predictions about traffic, traffic patterns and how many days until the next election.

Another big data problem is the ability to collect and analyze enormous amounts of sensitive data about your life, including your finances, medical conditions and sexual preferences.

That data could be used by companies or governments to track your movements or conduct surveillance.

The data is often stored on servers in other countries, but many companies are now starting to use the data in the U.S. and abroad.

How big is it?

Big Data is used to analyze massive amounts of large volumes of data in a relatively small amount of time, says Kevin Burke, chief executive of the research and analysis firm Gartner.

That means companies and governments can use data to do more complex things in less time, for instance, to better understand what is going on in the world, Burke says.

Big Data can also be used to create insights into specific people, but this is less useful than big data used for social engineering purposes.

“Big data can be used for any kind of information-gathering, but it’s really good at big-data analysis of people and groups,” Burke says, “which means it can be applied to big issues in social engineering or criminal investigations, to identifying terrorists, or to understanding how we make money.”

What does big money mean?

Big money means lots of money, and it can mean lots of different things to different people, says Robby Krieger, founder of analytics firm Zillow.

“It can mean a big investment, or a small investment, it can even mean a lot of small investments.

A big amount of money is like a lot, but a lot doesn’t necessarily mean a great deal.

For some people, it’s a lot more than a lot.”

Big data also means more than just the information it collects.

A company can use the information to develop new products or services, for a wide range of purposes.

For more, see:How big is big money?

According to Krieber, it depends on how much money the company needs.

He says, for most people, the big question is, what is the cost of doing it?

For example: If you are an investment adviser, you need a lot to do the right thing, and you might need to pay someone to do it for you.

If you’re a small business owner, you might be able to pay a small employee to work on the business, Krieer says.

If the right answer is to buy a car, you would need a car dealer to get it delivered.

Big money can also mean money to companies that are building software or devices that could make people more effective, like for example for monitoring and controlling robots or using artificial intelligence to help people with disabilities.

Big companies also spend a lot on research and development, Kieger says.

That can range from $10 million to $100 million per year, depending on the type of product or service.

And big companies are also increasingly buying companies or services that can help them develop more advanced products and services.

For companies that already have a product or services in the marketplace, like in health care or education, there’s a big risk that those products will be acquired and acquired and not replaced, Kile says.

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