IT Glossary

Predictive Modeling

Predictive modeling is a commonly used statistical technique to predict future behavior. Predictive modeling solutions are a form of data-mining technology that works by analyzing historical and current data and generating a model to help predict future outcomes. In predictive modeling, data is collected, a statistical model is formulated, predictions are made, and the model is validated (or revised) as additional data becomes available. For exa…

Predictive Modeling Solutions

Predictive modeling is the process of analyzing data to create a statistical model of future behavior. Predictive modeling solutions are a form of data-mining technologies that work by analyzing historical and current data, and generating a model to help predict future outcomes. These technologies can be used to generate a score (for example, a credit score), to assess behavior (for example, fraud detection or customer acquisition), or to analyz…

Predictive Analytics (2)

Predictive Analytics is a form of advanced analytics which examines data or content to answer the question “What is going to happen?” or more precisely, “What is likely to happen?”, and is characterized by techniques such as regression analysis, forecasting, multivariate statistics, pattern matching, predictive modeling, and forecasting. Also see: Gartner’s Data & Analytics Summit Gartner’s free research and webinars on Data & Anal…

claims analytics

Gartner defines “claims analytics” as the use of business intelligence (BI), reporting solutions, dashboards, data mining and predictive modeling technologies to manage and analyze claims data, which can result in improved performance. Overall, three processes are supported in claims analytics tools: claims analysis, reporting and predictive modeling….

Advanced Fraud Detection and Analysis Technologies

Advanced fraud detection and analysis technologies employ sophisticated analytics and predictive modeling to identify potential fraud in real time during data entry, rather than during a later batch run after a transaction is complete. It can be applied to both claims and underwriting fraud….

Load Forecasting

…itted or delivered by the utility. Techniques include price elasticity, weather and demand response/load analysis, and renewable generation predictive modeling. Forecasts must use regional customer load data, with time series customer load profiles. Accurate forecasts require adjustments for seasonality. Distribution load forecasting must be reconciled with distribution network configuration as part of the distribution circuit load measurements….

Telecom Analytics

…eporting and dashboarding to include capabilities ranging from ad hoc querying and multidimensional analyses to predictive and descriptive modeling, data mining, text analytics, forecasting and optimization. The adoption of analytics in telecommunications is intended to improve visibility into core operations, internal processes and market conditions, discern trends and establish forecasts. Future analytics will also include data from systems bey…

Sales Analytics

Sales analytics is used in identifying, modeling, understanding and predicting sales trends and outcomes while aiding sales management in understanding where salespeople can improve. Specifically, sales analytic systems provide functionality that supports discovery, diagnostic and predictive exercises that enable the manipulation of parameters, measures, dimensions or figures as part of an analytic or planning exercise….

Data Mining

The process of discovering meaningful correlations, patterns and trends by sifting through large amounts of data stored in repositories. Data mining employs pattern recognition technologies, as well as statistical and mathematical techniques. Also see: Gartner’s Data & Analytics Summit Gartner’s free research and webinars on Data & Analytics.  …

Social Analytics

…and relationships of people, topics, ideas and content. Interactions occur in workplace and external-facing communities. Social analytics include sentiment analysis, natural-language processing and social networking analysis (influencer identification, profiling and scoring), and advanced techniques such as text analysis, predictive modeling and recommendations, and automated identification and classification of subject/topic, people or content….

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