Created by JACKSON BOEVE
almost 2 years ago
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Question | Answer |
Big Data | Datasets that are too large and complex for businesses’ existing systems to handle utilizing their traditional capabilities to capture, store, manage, and analyze these datasets. |
structured data | Highly organized data that fits nicely in a table or a database. A balance sheet or income statement is a good example. |
unstructured data | Data without internal organization (or structure). Blogs, social media, and pictures posted on Instagram are examples of unstructured data. |
semi-structured data | Data that has elements of both structured (highly organized) and unstructured (not highly organized) data. |
Data Analytics | The science of examining raw data (now often Big Data), removing excess noise from the dataset, and organizing the data to conclude decision-making. |
extract, transform, and load (ETL) | The process of cleaning and scrubbing the data before data analysis can take place. |
data integrity | Maintaining and assuring the accuracy and consistency of data during transmission and storage. |
numerical data | Data is associated with a number that has a logical order. |
categorical data | Data with no logical order can’t be translated into a numerical value. |
Audit Data Standards (ADS) | A standard format for data files and fields typically needed to support an external audit in a given financial business process area was developed by the AICPA. |
descriptive analytics | Analysis performed that characterizes, summarizes, and organizes features and properties of the data to facilitate understanding. |
diagnostic analytics | An analysis is performed to investigate the underlying cause that cannot be answered by simply looking at the descriptive data. |
predictive analytics | An analysis is performed to provide foresight by identifying patterns in historical data by judging likelihood or probability. |
prescriptive analytics | Analysis performed that identifies the best possible options given constraints or changing conditions. |
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