Sains Data- Middle Test

A branch of science that combines mathematics, statics with computer science with the aim of analyzing data both small scale (sample) and large (population) by applying certain algorithms, is the definition of:

• Data warehouse

• Data science

• Data obtain

• Data complexity

One of the capabilities needed in data science is, unless:

• Business knowledge

• Computer science

• Public speaking

• Statistics and mathematics

Some of the processes involved in data science are, except:

• Bigdata

• database

• data mining

• Business intelligence

One of the stages in data science that is used as regression and prediction to estimate future values and classify and group groups of values from data is:

• type

• scrub

• explore

• interpret

The following picture is...

• abilities needed by data science

• ability required by a BI.

• the main factors supporting data science

• important scientific fields learned

The process of organizing, tidying up data, and discarding anything that is not needed, and replacing lost data and standardizing the entire format, is a stage in data science:

• explore

• scrub

• obtain

• analisis

What is Big Data?

• Optimization of company costs, Increasing business effectiveness and efficiency, Product development, Gaining insights about customers and markets.

• Optimization of marketing costs, Increasing productivity, Gaining insights about customers and markets

• a collection of processes consisting of volumes of data with a small capacity and holding only structured and unstructured data

• A collection of processes consisting of large volumes of data and can hold structured and unstructured data.

Which is the complexity data below, except:

• volume

• validitas

• velocity

• variety

Below is the application of big data in a number of sectors:

• government

• Banking

• Manufacturing

• all true

Big data works with the following 3 processes/ ways, namely:

• Analysis, Data integration and data management

• Data integration, data verification and analysis

• Data integrase, data management and data validation

• Data analysis, data management and data validation