Analytics Applies Statistical Algorithms
NOW FOR AN ORIGINAL PAPER ASSIGNMENT:Analytics Applies Statistical Algorithms
Question 1 Which analytics applies statistical algorithms and/or machine learning to historical data from multiple sources to ascertain the likelihood of outcomes and events? Explanatory Predictive Descriptive Historical Question 2 What is the most widely used schema to develop data warehouses and dimensional data marts? Constellation Sun Star Galaxy Question 3 What provides advanced data analysis and visualization tools, including multidimensional data analysis to support decision support? Big data processing tool (BDP) Data extraction, transformation, and loading tools (ETL) Master data management (MDM) Online analytical processing (OLAP) Question 4 Which process results in the extraction of patterns and knowledge from large amounts of data? Data dredging Data mining Data warehousing Data cleansing Question 5 What fundamental data structure was first developed to unite data from multiple, disparate systems on different technical platforms in different physical locations? Data warehouse Data aggregate Data dashboard Data processor
Predictive analytics encompasses a variety of statistical techniques from data mining, predictive modelling, and machine learning, that analyze current and historical facts to make predictions about future or otherwise unknown events.[1][2]
In business, predictive models exploit patterns found in historical and transactional data to identify risks and opportunities. Models capture relationships among many factors to allow assessment of risk or potential associated with a particular set of conditions, guiding decision-making for candidate transactions.[3]
The defining functional effect of these technical approaches is that predictive analytics provides a predictive score (probability) for each individual (customer, employee, healthcare patient, product SKU, vehicle, component, machine, or other organizational unit) in order to determine, inform, or influence organizational processes that pertain across large numbers of individuals, such as in marketing, credit risk assessment, fraud detection, manufacturing, healthcare, and government operations including law enforcement.
Predictive analytics is used in actuarial science,[4] marketing,[5] financial services,[6] insurance, telecommunications,[7] retail,[8] travel,[9] mobility,[10] healthcare,[11] child protection,[12][13] pharmaceuticals,[14] capacity planning,[15] social networking[16] and other fields.
One of the best-known applications is credit scoring,[1] which is used throughout financial services. Scoring models process a customer’s credit history, loan application, customer data, etc., in order to rank-order individuals by their likelihood of making future credit payments on time.
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