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A telecommunications company has a substantial amount of data. This data is being created by network elements within their environment. The company wants to change the way the network elements Call Detail Records (CDR) are stored and analyzed. The existing infrastructure consolidates all of the CDRs into a table structure, and then ingests them into a large database. Once ingested, a query engine accesses the database and performs analysis on these files. The system is functional; however, since the amount of CDRs generated will increase exponentially over the next year, the company is open to alternatives for storing and analyzing these records. In evaluating alternatives, the key requirements are to reduce cost, the amount of storage, and the amount of time to analyze the data. The customer would like to use Hadoop to analyze the CDRs. After you have conducted an assessment of the workflow, you have recommended an Isilon Cluster to work within the Hadoop environment. Which protocols would be the best fit when using Isilon for this customer's Hadoop workflow?
Central Tendency
A statistical measure that identifies a single value as representative of the middle of a dataset, commonly the mean, median, or mode.
Outliers
Data points that lie an abnormal distance from other values in a random sample from a population, often indicating a measurement or transcription error, or a novel phenomenon.
Variance
Measures the variability or spread of a set of data points around their mean; it's calculated as the average of the squared differences from the Mean.
Descriptive Statistics
Statistical methods that summarize and organize the information in a data set to describe its various features, such as mean or standard deviation, without drawing inferences about the population.
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