Big data 319-18 group Kurbonov Bekzod What is Big data ?

Big data
319-18 group Kurbonov Bekzod
What is Big data ?
Big data refers to the large, diverse sets of information that grow at ever-increasing rates. It encompasses the volume of information, the velocity or speed at which it is created and collected, and the variety or scope of the data points being covered (known as the "three v's" of big data). Big data often comes from data mining and arrives in multiple formats.

• Big data is a great quantity of diverse information that arrives in increasing volumes and with ever-higher velocity.
• Big data can be structured (often numeric, easily formatted and stored) or unstructured (more free-form, less quantifiable).
• Nearly every department in a company can utilize findings from big data analysis, but handling its clutter and noise can pose problems.
• Big data can be collected from publicly shared comments on social networks and websites, voluntarily gathered from personal electronics and apps, through questionnaires, product purchases, and electronic check-ins.
• Big data is most often stored in computer databases and is analyzed using software specifically designed to handle large, complex data sets.

The three Vs of big data
Volume
Velocity
Variety
The amount of data matters. With big data, you’ll have to process high volumes of low-density, unstructured data. This can be data of unknown value, such as Twitter data feeds, clickstreams on a web page or a mobile app, or sensor-enabled equipment. For some organizations, this might be tens of terabytes of data. For others, it may be hundreds of petabytes.
Velocity is the fast rate at which data is received and (perhaps) acted on. Normally, the highest velocity of data streams directly into memory versus being written to disk. Some internet-enabled smart products operate in real time or near real time and will require real-time evaluation and action.
Variety refers to the many types of data that are available. Traditional data types were structured and fit neatly in a relational database. With the rise of big data, data comes in new unstructured data types. Unstructured and semistructured data types, such as text, audio, and video, require additional preprocessing to derive meaning and support metadata.