Learn Predictive Analytics 2021 – Best Predictive Analytics Courses & Best Predictive Analytics Books & Best Predictive Analytics Tutorials

Best Predictive Analytics Courses 2021


Best Predictive Analytics Tutorials 2021

Introduction to Predictive Analytics on SAP HANA

This entry-to-intermediate SAP HANA Predictive Analytics course will help you master many techniques important to begin building sophisticated predictive analytics applications that use the power of SAP HANA and Business Intelligence. The course is designed so that you can master all the techniques gradually, starting with basic and relatively simple techniques before moving on to the more demanding techniques that Business Intelligence professionals use to build predictive analytics applications for their clients. The course will take you step-by-step through the process of creating the required HANA objects, such as tables, views, and predictive analytics SQL scripts. In particular, from this course you will learn:

Fundamentals of the predictive analysis library,
The structures involved, such as HANA tables, views, PAL SQL procedures and more,
A comparison of the raw PAL SQL code with the HANA analytical processes available in SAP BW by creating the comparable HANA AP in BW,
Integration of predictive analytics in SAP BW and SAP Lumira


This course does not assume any knowledge of the HANA predictive analytics library. BW and HANA experience would be helpful.

What this course is not:

This course does not cover all predictive analytics algorithms. It covers enough algorithms so that you can familiarize yourself with their use and apply the techniques to any other function. Covering all algorithms will result in a high level of repetition with no real value. What sets this course apart from anything available on other platforms is the fact that it covers the integration and application of the Predictive Analytics library with the various other visualization and viewing platforms.

SAP Big Data Predictive Analytics : An Overview

Big data analysis involves examining large sets of data to uncover hidden patterns, unknown correlations, market trends, customer preferences, and other useful business information. Analytical results can lead to more effective marketing, new revenue opportunities, better customer service, improved operational efficiency, competitive advantages over competing organizations, and other business advantages.

The main goal of big data analytics is to help businesses make more informed business decisions by enabling predictive data modeling specialists and other analytics professionals to analyze large volumes of data. transaction, as well as other forms of data that may be left untapped by conventional business intelligence programs. This could include web server logs and internet feed data, social media content and social media activity reports, text of customer emails and survey responses, detailed phone call records. mobile and machine data captured by sensors connected to the Internet of Things.

Big data can be analyzed with software tools commonly used in advanced analytical disciplines such as predictive analytics, data mining, text analysis, and statistical analysis. Potential pitfalls that can trip organizations into big data analytics initiatives include a lack of internal analytics skills and the high cost of hiring experienced analytics professionals. The amount of information typically involved and its variety can also cause data management headaches, including issues with data quality and consistency. Additionally, integrating Hadoop systems and data warehouses can be a challenge, although various vendors now offer software connectors between Hadoop and relational databases, as well as other data integration tools with Big Data capabilities. SAP has a comprehensive suite of solutions to support the entire analytical scope.

HR Analytics – Predictive Analytics

Best Predictive Analytics Books 2021

Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die

Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
  • In this rich, fascinating - surprisingly accessible - introduction, leading expert Eric Siegel reveals how predictive analytics (aka machine learning) works, and how it affects everyone every day. Rather than a "how to" for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques. Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement, hospitals, and universities ar
  • Siegel, Eric (Author)
  • English (Publication Language)
  • 368 Pages - 01/20/2016 (Publication Date) - Wiley (Publisher)

Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel. An introduction for everyone. In this rich, fascinating and surprisingly accessible manual, eminent expert Eric Siegel reveals how predictive analytics (also known as machine learning) works and how it affects everyone on a daily basis. Rather than a “how-to” for tech experts, the book serves both lay readers and experts by covering new case studies and the latest cutting edge techniques.

The prediction is booming. He is reinventing industries and running the world. Companies, governments, law enforcement agencies, hospitals and universities are taking power. These institutions predict whether you will click, buy, lie, or die. Why? For good reason: predicting human behavior combats risk, increases sales, strengthens healthcare, streamlines manufacturing, eliminates spam, optimizes social media, strengthens the fight against crime, and wins elections.

How? ‘Or what? The prediction is based on the world’s most powerful and flourishing man-made resource: data. Accumulated largely as a byproduct of routine tasks, data is the tasteless, unsalted residue that is deposited en masse as organizations disintegrate. To surprise! This pile of garbage is a gold mine. Big Data incorporates an extraordinary wealth of experience from which to learn.

Predictive analytics (also known as machine learning) unleashes the power of data. With this technology, the computer literally learns from the data how to predict the future behavior of people. No perfect prediction is possible, but putting the odds into the future more effectively leads to millions of decisions, determining who to call, mail, investigate, incarcerate, schedule an appointment, or seek treatment.

In this insightful and engaging introduction, now in a revised and updated edition, former Columbia University professor and founder of Predictive Analytics World, Eric Siegel, reveals the power and dangers of prediction:

What Kind of Mortgage Risk Chase Bank Predicted Before the Recession.
Predict which people will drop out of school, cancel a membership, or get divorced before they know it themselves.
Why early retirement predicts shorter life expectancy and vegetarians miss fewer flights.
Five Reasons Organizations Predict Death, Including a Health Insurance Company.
How the American Bank and Obama for America figured out how to more firmly persuade each individual.
Why the NSA Wants All Your Data: Machine Learning Supercomputers to Fight Terrorism.
How IBM’s Watson Computer Used Predictive Modeling to Answer Questions and Beat Human Champions on TV Jeopardy!
How Companies Uncover Untold Private Truths: How Target Finds Out She’s Pregnant and Hewlett-Packard Infers She’s About To Leave Her Job.
How Judges and Parole Boards Use Crime Prediction Computers to Decide How Long Convicts Can Be Held
182 examples from Airbnb, BBC, Citibank, ConEd, Facebook, Ford, Google, IRS, LinkedIn, Match.com, MTV, Netflix, PayPal, Pfizer, Spotify, Uber, UPS, Wikipedia, etc.

How does predictive analytics work? This stuffy book satisfies by debunking the intriguing science under the hood. For future active professionals pursuing a career in the field, it lays a solid foundation, provides the necessary knowledge, and whets an appetite for more. A truly ubiquitous science, predictive analytics permanently affects our daily lives. Whether you use it, or use it, harness the power of predictive analytics.


SaleBestseller No. 1
Predictive HR Analytics: Mastering the HR Metric
  • Edwards, Dr Martin (Author)
  • English (Publication Language)
  • 536 Pages - 03/28/2019 (Publication Date) - Kogan Page (Publisher)
Bestseller No. 2
Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
  • Amazon Kindle Edition
  • Siegel, Eric (Author)
  • English (Publication Language)
  • 356 Pages - 01/12/2016 (Publication Date) - Wiley (Publisher)
SaleBestseller No. 3
Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst
  • John Wiley Sons
  • Abbott, Dean (Author)
  • English (Publication Language)
  • 464 Pages - 04/04/2014 (Publication Date) - Wiley (Publisher)
SaleBestseller No. 4
Predictive Analytics For Dummies
  • Bari, Dr. Anasse (Author)
  • English (Publication Language)
  • 464 Pages - 10/31/2016 (Publication Date) - For Dummies (Publisher)
Bestseller No. 5
Predictive Analytics: Data Mining, Machine Learning and Data Science for Practitioners
  • Amazon Kindle Edition
  • Delen, Dursun (Author)
  • English (Publication Language)
  • 448 Pages - 12/15/2020 (Publication Date) - Pearson FT Press (Publisher)
Bestseller No. 6
IISS: Employee Experience & Engagement with Predictive Analytics
  • Amazon Kindle Edition
  • Ng, Mong Shen (Author)
  • English (Publication Language)
  • 355 Pages - 02/27/2020 (Publication Date)
Bestseller No. 7
Hands-On Predictive Analytics with Python: Master the complete predictive analytics process, from...
  • Amazon Kindle Edition
  • Fuentes, Alvaro (Author)
  • English (Publication Language)
  • 330 Pages - 12/28/2018 (Publication Date) - Packt Publishing (Publisher)
Bestseller No. 8
Predictive Analytics for Business Strategy
  • Amazon Kindle Edition
  • Prince, Jeff (Author)
  • English (Publication Language)
  • 368 Pages - 01/30/2018 (Publication Date) - McGraw-Hill Higher Education (Publisher)
SaleBestseller No. 9
Fundamentals of Machine Learning for Predictive Data Analytics, second edition: Algorithms, Worked...
  • Hardcover Book
  • Kelleher, John D. (Author)
  • English (Publication Language)
  • 856 Pages - 10/20/2020 (Publication Date) - The MIT Press (Publisher)
Bestseller No. 10
Mastering Predictive Analytics with R
  • Forte, Rui Miguel (Author)
  • English (Publication Language)
  • 414 Pages - 06/17/2015 (Publication Date) - Packt Publishing (Publisher)
As an Amazon Associate I earn from qualifying purchases.