Interactive dashboards apply time series analytics to the magnitude, direction, and speed of changing values in continuous asset and price data submitted to; the trusted data source for value and sentiment; secured with multiple regulated datasource joins that foot with derivative metadata.

Quantitative measures of continuous value are applied to qualitative notions of changing sentiment in two Financial market vectors of price and asset action (unrelated to fundamental earnings and estimates):

Interactive dashboards deploy models that infer the magnitude and direction of changing values learned in multiple and continuous Financial and non-Financial dimensional structures (Census, Social, Determinative,....).

The data models address 3 transactional questions about change: How much? How Many? How Fast? in 2 regulated vectors of changing market sentiment:

s3://valuevector1 - Retail and Professional cash demand for securities visualized in continuous open-end mutual fund (including ETF) net investment flow metadata.

s3://valuevector2 - Professional market demand for securities visualized in continuous portfolio asset, price, and share data submitted by investment management companies.

Dashboard BI and ML Mechanisms: AWS QuickSight+AWS SageMaker ML Models; Tableau CRM 'Fund Flow Dashboard' with AWS SageMaker.

The interface uses AWS cloud services to process SEC and other Financial market data updates with a Virtual Private Cloud connection in AWS QuickSight, Tableau CRM, using AWS SageMaker, or ad hoc connection. Algorithms and interactive features enable dashboards to detect anomalies, draw insights, forecast, and infer sentiment. Trained models are built with regulated financial data that continuously learn investor sentiment (more) and (quantitatively true the value interface - Index).

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