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Automating the Automators: Shift Change in the Robot Factory

O'Reilly on Data

Given that, what would you say is the job of a data scientist (or ML engineer, or any other such title)? Building Models. A common task for a data scientist is to build a predictive model. You know the drill: pull some data, carve it up into features, feed it into one of scikit-learn’s various algorithms.

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What is business analytics? Using data to improve business outcomes

CIO Business Intelligence

Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more. Forecasting: Forecasting analyzes historical data from a specific period to make informed estimates predictive of future events or behaviors.

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12 data science certifications that will pay off

CIO Business Intelligence

Cost: $180 per exam Location: Online Duration: Self-paced Expiration: Credentials do not expire SAS Certified Advanced Analytics Professional The SAS Certified Advanced Analytics Professional credential validates your ability to analyze big data with a variety of statistical analysis and predictive modeling techniques.

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Understand PMML (It’s Not That Hard)!

Smarten

Incorporate PMML Integration Within Augmented Analytics to Easily Manage Predictive Models! PMML is Predictive Model Markup Language. It is an interchange format that provides a method by which analytical applications and software can describe and exchange predictive models. So, what is PMML Integration?

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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. What are the four types of data analytics? Data analytics vs. business analytics.

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The Benefits of Low-Code, No-Code in Augmented Analytics!

Smarten

The organization can leverage and change data workflows, reports, dashboards and predictive models without extensive coding or time investment. The incorporation of new technologies and capabilities will drive current and future user adoption and the successful implementation of analytics within the business user community.’

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A Planning Center of Excellence Delivers Performance Improvement

David Menninger's Analyst Perspectives

This does away with the need for analysts to repeatedly perform data extraction, enrichment or transformation motions from the required source systems, all but eliminating the substantial amount of time analysts and business users spend routinely on data preparation.