Several organizations have migrated to the cloud for better quality in business engagements and security. Data quality is crucial in present-day activities. Information is generated and collected from data representin...Several organizations have migrated to the cloud for better quality in business engagements and security. Data quality is crucial in present-day activities. Information is generated and collected from data representing real-time facts and activities. Poor data quality affects the organizational decision-making policy and customer satisfaction, and influences the organization’s scheme of execution negatively. Data quality also has a massive influence on the accuracy, complexity and efficiency of the machine and deep learning tasks. There are several methods and tools to evaluate data quality to ensure smooth incorporation in model development. The bulk of data quality tools permit the assessment of sources of data only at a certain point in time, and the arrangement and automation are consequently an obligation of the user. In ensuring automatic data quality, several steps are involved in gathering data from different sources and monitoring data quality, and any problems with the data quality must be adequately addressed. There was a gap in the literature as no attempts have been made previously to collate all the advances in different dimensions of automatic data quality. This limited narrative review of existing literature sought to address this gap by correlating different steps and advancements related to the automatic data quality systems. The six crucial data quality dimensions in organizations were discussed, and big data were compared and classified. This review highlights existing data quality models and strategies that can contribute to the development of automatic data quality systems.展开更多
A simple, sensitive gradient rapid resolution liquid chromatographic assay method has been developed for the quantitative determination of Candesartan Cilexetil in bulk active pharmaceutical ingredient, used for the t...A simple, sensitive gradient rapid resolution liquid chromatographic assay method has been developed for the quantitative determination of Candesartan Cilexetil in bulk active pharmaceutical ingredient, used for the treatment of hypertension. The developed method is also applicable for the process related impurities determination. Efficient chromatographic separation was achieved on a C18 stationary phase with simple mobile phase combination delivered in a gradient mode and quantification was by ultraviolet detection at 210 nm at a flow rate of 0.4 mL × min﹣1. In the developed UPLC method the resolution between Candesartan Cilexetil and its two potential impurities was found to be greater than 2.0. Regression analysis showed an r value (correlation coefficient) greater than 0.99 for Candesartan Cilexetil and its two impurities. This method was capable to detect two impurities of Candesartan Cilexetil at a level of 0.003% with respect to test concentration of 1.0 mg × mL﹣1 for a 2 μL injection volume. The bulk active pharmaceutical ingredient was subjected to stress conditions of hydrolysis, oxidation, photolysis and thermal degradation. Considerable degradation was found to occur in oxidative stress conditions. The stress samples were assayed against a qualified reference standard and the mass balance was found close to 99.5%. The developed RP-LC method was validated with respect to linearity, accuracy, precision and robustness.展开更多
文摘Several organizations have migrated to the cloud for better quality in business engagements and security. Data quality is crucial in present-day activities. Information is generated and collected from data representing real-time facts and activities. Poor data quality affects the organizational decision-making policy and customer satisfaction, and influences the organization’s scheme of execution negatively. Data quality also has a massive influence on the accuracy, complexity and efficiency of the machine and deep learning tasks. There are several methods and tools to evaluate data quality to ensure smooth incorporation in model development. The bulk of data quality tools permit the assessment of sources of data only at a certain point in time, and the arrangement and automation are consequently an obligation of the user. In ensuring automatic data quality, several steps are involved in gathering data from different sources and monitoring data quality, and any problems with the data quality must be adequately addressed. There was a gap in the literature as no attempts have been made previously to collate all the advances in different dimensions of automatic data quality. This limited narrative review of existing literature sought to address this gap by correlating different steps and advancements related to the automatic data quality systems. The six crucial data quality dimensions in organizations were discussed, and big data were compared and classified. This review highlights existing data quality models and strategies that can contribute to the development of automatic data quality systems.
文摘A simple, sensitive gradient rapid resolution liquid chromatographic assay method has been developed for the quantitative determination of Candesartan Cilexetil in bulk active pharmaceutical ingredient, used for the treatment of hypertension. The developed method is also applicable for the process related impurities determination. Efficient chromatographic separation was achieved on a C18 stationary phase with simple mobile phase combination delivered in a gradient mode and quantification was by ultraviolet detection at 210 nm at a flow rate of 0.4 mL × min﹣1. In the developed UPLC method the resolution between Candesartan Cilexetil and its two potential impurities was found to be greater than 2.0. Regression analysis showed an r value (correlation coefficient) greater than 0.99 for Candesartan Cilexetil and its two impurities. This method was capable to detect two impurities of Candesartan Cilexetil at a level of 0.003% with respect to test concentration of 1.0 mg × mL﹣1 for a 2 μL injection volume. The bulk active pharmaceutical ingredient was subjected to stress conditions of hydrolysis, oxidation, photolysis and thermal degradation. Considerable degradation was found to occur in oxidative stress conditions. The stress samples were assayed against a qualified reference standard and the mass balance was found close to 99.5%. The developed RP-LC method was validated with respect to linearity, accuracy, precision and robustness.
