Remove Data Analytics Remove Publishing Remove Uncertainty
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What you need to know about product management for AI

O'Reilly on Data

Machine learning adds uncertainty. Underneath this uncertainty lies further uncertainty in the development process itself. You might establish a baseline by replicating collaborative filtering models published by teams that built recommenders for MovieLens, Netflix, and Amazon.

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Publish and enrich real-time financial data feeds using Amazon MSK and Amazon Managed Service for Apache Flink

AWS Big Data

An enriched data feed can combine data from multiple sources, including financial news feeds, to add information such as stock splits, corporate mergers, volume alerts, and moving average crossovers to a basic feed. IV is forward-looking and derived from the current market price of an option.

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What’s so Special About 50:50?

Andrew White

After sifting through several year’s worth of formally written data, analytics, and data and analytics strategies, we found about 85% of them did not include a measurable business outcome. See Data and Analytics Strategies Need More-Concrete Metrics of Success. As such an ROI would have been impossible.

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5 Types of Costly Data Waste and How to Avoid Them

CIO Business Intelligence

Duplication of data also entails duplication of effort, which is an additional cost. And the problem is not just a matter of too many copies of data. Approximately duplicated data sets may introduce uncertainty about data quality.

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Predictive Analytics Improves Trading Decisions as Euro Rebounds

Smart Data Collective

Predictive analytics tools can be particularly valuable during periods of economic uncertainty. Predictive Analytics Helps Traders Deal with Market Uncertainty. We have talked about a lot of the benefits of using predictive analytics in finance. Analytics Vidhya, Neptune.AI

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Topics to watch at the Strata Data Conference in New York 2019

O'Reilly on Data

Terms that relate to data engineering, data management, and data analytics dominate the top tiers of proposal topics. This is noteworthy for several reasons: first, the top three terms in our data set relate in one way or another to ML. Another related term, “data pipeline” (at No. The term “ML” is No.

IoT 20
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What it Means to be a Data-driven Financial Institution

Sisense

Luckily, there are intelligent and scalable ways institutions can access and make sense of their data, allowing them to spot trends and extract insights that drive innovation and inspire creative solutions. This insight can inform future partnerships, and reduce uncertainty about which services will be most relevant and useful.