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Bringing an AI Product to Market

O'Reilly on Data

The first step in building an AI solution is identifying the problem you want to solve, which includes defining the metrics that will demonstrate whether you’ve succeeded. It sounds simplistic to state that AI product managers should develop and ship products that improve metrics the business cares about. Agreeing on metrics.

Marketing 362
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The Lean Analytics Cycle: Metrics > Hypothesis > Experiment > Act

Occam's Razor

To win in business you need to follow this process: Metrics > Hypothesis > Experiment > Act. We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. That metric is tied to a KPI.

Metrics 156
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Financial Statements: Types, Examples, and Analysis

FineReport

What are Financial Statements Financial statements are written documents prepared regularly based on daily accounting data. Within the dashboard, essential financial metrics critical to management, such as income and expenditure details and daily financial data, take center stage.

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What is Six Sigma? Streamlining quality management

CIO Business Intelligence

The name references the Greek letter sigma, which is a statistical symbol that represents a standard deviation. The process aims to bring data and statistics into the mesh to help objectively identify errors and defects that will impact quality. Six Sigma was trademarked by Motorola in 1993.

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A Guide To The Methods, Benefits & Problems of The Interpretation of Data

datapine

Secondary Research: much like how patterns of behavior can be observed, different types of documentation resources can be coded and divided based on the type of material they contain. Interviews: one of the best collection methods for narrative data. Inquiry responses can be grouped by theme, topic, or category. Dependable.

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Practical advice for analysis of large, complex data sets

The Unofficial Google Data Science Blog

We were often asked to make sense of confusing results, measure new phenomena from logged behavior, validate analyses done by others, and interpret metrics of user behavior. Some people seemed to be naturally good at doing this kind of high quality data analysis. Why has this document resonated with so many people over time?

Metrics 107
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Fundamentals of Data Mining

Data Science 101

Data Collection. After defining the goals in the previous step, it is essential to collect data. This could involve using data that already exists in a company’s database, getting data from external resources or steps to collect new data through survey forms filled by customers. Regression.