Books by Lillian Pierson
Data Science For Dummies®, 2017
Available for sale here: http://amzn.to/2osljza
Topics include:
• Math, statistics, and machine learning
• Internet of Things analytics, data science, and AI
• Data engineering technologies and big data
• Python, R, D3.js, SQL, Excel, and QGIS for data science
• Data visualization, data-driven storytelling, and data journalism
• Business-centric data science
• Data science for ecommerce growth
• Data science for environmental good stewardship
• Data science for crime prevention
• Free tools, applications, and resources for use in data science
Book preview:
Big Data / Hadoop For Dummies®, 2015
DELL CANADA SPECIAL EDITION
Learn to:
Understand big data technologies – learn how big data technologies work and the factors you must consider when planning your transition
Implement big data – learn the steps you should take to optimize the implementation of your big data project
Generate business value with big data – increase revenues, decrease expenditures, optimize IT, and optimize standard business operations with insights generated from enterprise big data
Author: Lillian Pierson, P.E.
Managing Big Data Workflows for Dummies®, 2016
BMC SOFTWARE SPECIAL EDITION
Available as a free download here: http://bit.ly/BigData-Workflows
Learn to:
Select the best big data technologies for the task at hand
Solve business problems using big data technologies
Navigate in the world of big data workflows
Hire the best big data candidates
Authors: Joe Goldberg, Lillian Pierson, P.E.
A Badass’s Guide to Breaking Into Data
Available as a free download here: http://data-mania.com/blog/guide-to-breaking-into-data/
This guide covers:
Course recommendations for becoming a self-taught data scientist or engineer
Tips on getting real-world programming experience in data
Tips on showing off your data-savvy (and increasing your sphere of influence)
Who you should be following if you want to be a top data professional
How to build an awesome data blog (and make a name for yourself while you’re at it)
Must-do tips for building out your data coding portfolio
Author: Lillian Pierson, P.E.
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