Sentence examples for volatility of data from inspiring English sources
However, the volatility of data traffic can make it difficult to provision enough cloud resources to handle this traffic, affecting ISPs cost of handling data.
The critical issues arising from the volatility of data due to the small sample size (especially at the highest ages) may be made worse by missing records; this is the case, for example, of a small country previously part of a larger country, or a specific geographic area of a country, given that in some periods mortality data could have been collected just at an aggregate level.
According to Equation 10, Table 7 shows the volatility of data sets used in the study.
The revealed contradictory combination of relatively high volatility of data and their consistent serial correlation generates a legitimate question: Is this contradiction a sign of a possible presence of an attractor in statistical series? 1.
After applying Equation 10 to the data in Table 6, volatility of data achieved are 2,643.33% and 4.25% for the first and second data sets, respectively, that are completely sensible.
The implemented module runs as a service and, as the volatility of the data is very low (at most a few records are updated each day), the data updating process runs once a day during the night.
"We get caught up in the monthly volatility of the data, and we need to step back," she said.
Sharply fluctuating monthly figures highlight the volatility of snapshot data and Halifax suggested a better indicator was its comparative figure for the three months to October, which showed a rise of 1.2% in house prices.
Factors that are likely to apply to any Asserted Versioning implementation include the number of users, the complexity of the application and the SQL, the volatility of the data, and the DBMS and server platform.
The quality, consistency, accuracy and volatility of web data should be examined (Carnevale et al. 2014).
Clemente De Lucia, an economist at BNP Paribas, noted that a methodological change had increased the volatility of consumer price data, meaning that the data should be taken with a grain of salt.
