Last Updated 10/2021
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 7 lectures (3h 49m) | Size: 3.14 GB
Creating business value by linking historical data to the future
What you’ll learn
Understand the art and science of predictive analytics to define clear actions that result in improved business results
Describe the core principles of predictive customer analytics
Embrace machine learning basics in predictive analytics
Understand the process that links data to business value
Requirements
No prerequisites.
Description
Why should a company invest in data analytics and deploy big data analytics, for example, today?
The reason is that analytics and decisions based on data analytics and data insights drive business value and enhance firms’ marketing and financial performance. Firms that have developed capabilities related to data analytics perform better in the marketplace. They outperform their competitors.
And this should be a major reason why today’s companies should invest in data analytics.
What’s the focus of this course? It is our job – or your job as a data analyst – to extract insights from data. This course introduces learners to predictive analytics applied to management and business administration so that managers can deliver more relevant and meaningful customer experiences, at all customer touchpoints, throughout the customer life cycle, boosting customer loyalty and revenues. In particular, predictive analytics is a set of tools and algorithms used to make predictive marketing and customer analytics possible. In this course, we will cover the core principles of predictive data analytics. We will cover the core principles of predictive data analytics through the discussion of the different steps in the Cross-Industry Standard Process Model for Data Mining (CRISP-DM) that links business understanding, data, and methods to business value.
During the course, you will develop and acquire abilities to
Understand the art and science of predictive analytics to define clear actions that result in improved business results;
Describe the core principles of predictive customer analytics;
Embracing the Cross-Industry Standard Process Model for Data Mining (CRISP-DM) steps to building predictive models.
Who this course is for
Domain experts who want to develop an overall understanding of predictive data analytics.
Managers who need to understand how they can link data to business value through data analytics.
Anyone who wants to understand the fundamentals of predictive data analytics.
Students who want to add data capabilities to their curricula.
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