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Big Data

Compléter

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Non-relational databases

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À propos de Compléter
technology
k12
big data
 Âge recommandé: 12 ans
74 fois fait

Créé par

Monica Nash
Monica Nash
United States

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Big Data

Non-relational databases

Monica Nash
1

social media transactions sensors medical vast amounts

Every day , of data are collected from Internet searches , posts , customer , military surveillance , tests , and weather .

2

unconventional sense Data volume processes Big data stored

The term refers to two things : first , the actual of collected and all over the world , and second , the tools and used to make of this data .

3

activities surveillance constant data Internet staggering sensors raw Weather technology transactions

The amount of generated by our use of is . Billions of users are involved in and other on the . instruments , cameras , and traffic produce streams of data .

4

target Data customers collecting customer experience business analyzing driven data decisions quickly Big

From a perspective , we can use to effectively potential in an upcoming advertising campaign . By and data on business operations , we can make intelligent , - that increase efficiency and optimize product development . We can respond to needs and enhance their in using our products .

5

weapons roads governments Big patient traffic media gene social purchases information

With Data , can sift through profiles , , and other online activities to identify potential terrorists . Medical researchers can use and mappings to predict who might need specific treatments . Cities can take advantage of sensor technology to better design and keep traffic moving smoothly .

6

complex engineers can't unstructured extract organize analysts

How do big data and do their work ?

The first step is to the data and it in some way . This is a challenge because big data is typically and distributed over several different locations . And because it's so , combining various types of information , big data be processed quickly into a relational database .

7

extracted mining trends patterns algorithms analysis

The next step is called data , which is a broad and open - ended of data . Data mining experts use automated tools and to discover or in the data .

8

big questions analysts interpret analytics

This brings us to the last step , which is data . This is where ask specific to help them the data .

9

big user knowledge potential consent

With all of the exciting benefits of data , we need to be aware of problems . First , data is often obtained without the or of

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