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Chart Snapshot: Fan Charts

The Data Visualisation Catalogue

A Fan Chart is a visualisation tool used in time series analysis to display forecasts and associated uncertainties. Also, as the forecast extends further into the future, uncertainty grows, causing the shaded areas to widen and give this chart its distinctive ‘fan’ appearance.

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Perform time series forecasting using Amazon Redshift ML and Amazon Forecast

AWS Big Data

Many businesses use different software tools to analyze historical data and past patterns to forecast future demand and trends to make more accurate financial, marketing, and operational decisions. Forecasting acts as a planning tool to help enterprises prepare for the uncertainty that can occur in the future.

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TBM helps CIOs translate tech spending to business outcomes

CIO Business Intelligence

Cost transparency and accurate budget forecasting are two major parts of the TBM framework, Guarini says. The US Office of Management and Budget has also pushed agencies to use TBM practices since 2017.

ROI 100
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Infor’s Velocity Summit Highlights Multiple Advances and Enhancements

David Menninger's Analyst Perspectives

Infor introduced its original AI and machine learning capabilities in 2017 in the form of Coleman, which uses its Infor AI/ML platform built on Amazon’s SageMaker to create predictive and prescriptive analytics. It also offered a chatbot that utilized Amazon Lex.

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Our quest for robust time series forecasting at scale

The Unofficial Google Data Science Blog

by ERIC TASSONE, FARZAN ROHANI We were part of a team of data scientists in Search Infrastructure at Google that took on the task of developing robust and automatic large-scale time series forecasting for our organization. So it should come as no surprise that Google has compiled and forecast time series for a long time.

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Can Predictive Analytics Help Traders Navigate Bitcoin’s Volatility?

Smart Data Collective

The evidence demonstrating the effectiveness of predictive analytics for forecasting prices of these securities has been relatively mixed. Many experts are using predictive analytics technology to forecast the future value of bitcoin. This algorithm proved to be surprisingly effective at forecasting bitcoin prices.

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The trinity of errors in financial models: An introductory analysis using TensorFlow Probability

O'Reilly on Data

Errors in analysis and forecasting may arise from any of the following modeling issues: using an inappropriate functional form, inputting inaccurate parameters, or failing to adapt to structural changes in the market. For such distributions, parameter values based on historical data are bound to introduce errors into forecasts.

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