Looking at the numbers, 2018 was the year that saw a shortage of more than 151, 000 data scientists in the U.S, a significant increase from previous years. This could mean two things. First, as long as businesses will continue to rely on data for insights, the demand for scientists will continue to grow. Secondly, a shortage means that while data science and data analytics are two lucrative careers, data science and data analytics certification training are just not for everyone.
You could be apt to crunching numbers and smart in coding but passion goes beyond learning and practice. There is a wealth of resources out there that can help you grow your love for data science and analytics. In this article, we have compiled 11 must-read data analytics books that will equip you with the relevant information you need to build passion and grow your career.
- Are you just starting on data analytics? Read…
Data Analytics Made Accessible
By A. Maheshwari
If you are a newbie just venturing into data analytics, whether in college or out, this is the place to start. Data Analytics Made Accessible breaks down data analytics in a way that you will digest the concepts easily and clearly gain both theoretical and practical knowledge. Packed with real-world illustrations and case studies that you can explore to get the hang of business intelligence and data mining, this book takes you through analytics step by step into the world of analytics.
- Want to discover the intrigues of predictive analysis? Read…
Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
Eric Siegel
In the most interesting way, Eric Siegel reaches out to everyone interested in predictive analytics through very intriguing real-world illustrations like the Obama campaign, case studies, quotes, and current techniques, there is never a dull moment reading this resourceful book. It is written in such a lively language yet covers predictive analytics concepts to the hilt. Covering what predictive analytics is, how it works, deployment, core and uplift modeling, ensemble models, and matters ethics, this is certainly a book for all.
- To have a peek in the past and trend into the future, read…
Business unintelligence: Insight and Innovation Beyond Analytics and Big Data
Barry Devlin
Business intelligence in the digital transformation era is not what it was in the past. Businesses today are bombarded with complex models thanks to the ever-advancing technology, dynamic competitive environment, changing customer perspective of value, and more. This book brings us the new reality of business intelligence. Analytics and big data have propelled business intelligence to where it is today. However, business intelligence must go beyond analytics to unearth business value from data. This book takes us down the business intelligence road, from its history, present, and right into the future. It explicitly talks about issues that have bedeviled this field, outdated data practices, while still highlighting those that have worked.
- To get some insight into transformative customer experience, read…
Predictive Marketing: Easy Ways Every Marketer Can Use Customer Analytics and Big Data
Dominique Levin and Omer Artun
Away from all the technicalities that come with implementing predictive analytics, this book presents a marketer’s manual to warming the hearts of customers through building lasting customer relationships. It is loaded with several use-cases, effective strategies, and practical tips on implementable approaches to data-driven and personalized marketing, customer acquisition, and customer growth. These approaches are applicable to all companies, large and small.
- To build professional skills around analytics. Read…
https://www.youtube.com/embed/vMFh6z1ET7o
Developing Analytic Talent: Becoming a data scientist
Vincent Granville
Refined data scientists will tell you that theoretical knowledge is valueless without application. This book is not just about improving your skill through practice. Many have gone down that route. You want practical tips that if implemented, will distinguish you from others in a technically demanding space. This book saves some groping around to gain expertise by giving you valuable information about in-demand skills, job interview questions, recent salary surveys, and sample job postings. This way, you will not just be building detailed analytics skills but also positioning yourself for the job market.
- Onto deeper mining? Read…
Data Mining and Predictive Analytics (Wiley Series on Methods and Applications in Data Mining)
Daniel T. Larose and Chantal D.Larose
The 7th in the Wiley Series on Methods and Applications in Data Mining, this is an updated second edition that lays a solid foundation on data mining techniques and models. It covers association rules, clustering, neural networks, logistic regression, and multivariate analysis with R programming language. It thus doesn’t just leave you at the theory level but also helps you to apply your knowledge using the practical examples working with real-world data sets and assessment exercises. As a student or someone who is learning the ropes of data mining and predictive analytics, this is a great instructional resource.
- To unearth the business value of analytics, read…
A practitioner’s Guide to Business Analytics: Using Data Analysis Tools to Improve your Organization’s Decision Making and Strategy
R. Bartlett
Data analytics does have business value and every futuristic business thrives on data-driven decisions and strategies. A good read for those in the position of making business decisions, this book is a blueprint for assessing the capabilities of, strategic planning with and developing good criteria for evaluating the value of business analytics.
- Curious about what there is beyond algorithms? Read…
Feature Engineering and Selection: A Practical Approach for Predictive Models
K. Johnson and M. Kuhn
Modeling algorithms is just one part of creating predictive modeling. This book covers other aspects of the predictive modeling process to give you holistic insight. Think about finding representations for predictors, finding the best subset in a dataset that will yield the expected performance, along with practical illustrations on sample datasets using R programming language.
- Analytics for the start-ups? Read…
Lean Analytics: Use Data to Build a Better Startup Faster
A. Croll and B. Yokovitz
The very life of any business is in meeting the needs of its customers by developing products that align with their expectations and values. Thus, this book offers valuable insight on leveraging customer feedback through data analytics and fast. It may have been written for start-ups that hope to conquer their markets but it certainly carries much value for companies, large and small. All in all, it comes down to developing a product that people want without too much trial and error. This book answers your ‘how-to’ questions and helps you apply the lean approach to product development.
- To learn about the indispensability of big data, read…
Too Big To Ignore: The Business Case for Big Data
P. Simon
Big data is without a doubt a big deal in the 21st century. Markets have shifted away from the masses to personalized customer experience. Competition is rife and the competitive environment is as dynamic as can be. Customers have far too many choices. There is no taking chances, their needs must be met or they align with the competition.
This book is an eye-opener. Way beyond the types, characteristics, and sources of big data, gives you valuable insight into technologies backing big data for businesses to explore its full value. It is packed with case studies, quotes, illustrations, and analyses, this book is a fun but informative read for anyone who wants some insight into harnessing the power of big data.
- To get down to proven analytics best practices, read…
Analytics Best Practices: A Business-driven Playbook for Creating Value through Data Analytics
Dr. P. Southekal
This book delves into the not so often trodden path of best practices. Analytics success is not only about technology, big data, and the market but also determined by best practices. The topic of best practices is in reality the mainstay of analytics. Dr. P. Southekal, comprehensively and practically lays out analytics best practices in ten proven guidelines that will help business leaders, decision-makers, and others to address challenges, explore opportunities, and design practical solutions around data analytics to realize its business value.
In summary
These are just 11 books we have covered that we thought might interest you. A passionate data scientist or analyst is always thirsty for information. he/she will go the extra mile to check out other books in their field.