Connect the laptop via cable or wireless to the printer. Sometimes printers will need for you to install software (comes in a CD) before you can use it.
Hope this helps.
<span>A certain database has numerous tables, but they do not share any fields in common. this database will not be as powerful as others because it is not relational. In </span><span>a relational database the data elements are dividing the data elements into related tables. Once ready to start working with the data, one can rely on relationships between the tables to pull the data together in meaningful ways.</span>
I would go with B
Charts,worksheets,images
Answer:
3rd;mobile;velocity;NoSQL;out;shards;dynamic;schema-less;value;column;Hadoop;MapReduce.
Explanation:
Big data refers to huge collections of data that are difficult to process, analyze, and manage using conventional data tools. It is a core component of the 3rd platform, which also includes cloud computing, mobile devices, and social networking. The five Vs of big data are high volume, high velocity, diversified variety, unknown veracity, and low-density value. Although SQL and relational databases can be used for big datasets, a collection of alternative tools referred to as NoSQL has become popular. These tools work well when databases scale out (horizontally) and when databases are broken into subsets called shards. Modern database tools also handle dynamic scaling as devices are added when additional capacity is required. NoSQL tools are sometimes said to create schema-less databases, but they usually have some type of structure, though it may be more flexible than the relational model. A key-value data model provides each data element with a key. A column-oriented data model makes it easy to access data stored in similar fields, rather than in individual records. Two very popular NoSQL tools include Hadoop, which is a big data file system, and MapReduce which sends processing logic to the data, rather than bringing the data to the computer that performs the processing.
Answer: (C) Sensitivity analysis
Explanation:
The sensitivity analysis is also known as simulation analysis or "What-if" analysis as, it is basically used for the outcome prediction of the decision making in various range of the given variable.
It is used by making a given arrangement of factors, an investigator can decide that how changing in a single variable influence the final result.
The sensitivity analysis is the process for investigation of how the vulnerability in the yield of a scientific model or framework can be isolated in the system.
Theretofore, Option (C) is correct as all the other options does not involve in the study of variable and also others are not the extension of what-if analysis.