The Art of Data Analysis: Non-Technical Skills for Data Analysts

The Art of Data Analysis: Non-Technical Skills for Data Analysts
Author: Alberto Scappini
Publisher: Alberto Scappini
Total Pages: 235
Release: 2020-08-16
Genre: Business & Economics
ISBN: 1702688526

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Would you like to greatly improve your data analysis capabilities by learning the most critical non-technical skills? Do you want to be more astute and well-rounded when applying your skills as a data analyst and achieve better results? If you answered “yes” to any of these questions, keep reading ….. There is an immense focus being placed on data analysis by businesses these days. It is indispensable and helps boil down decision-making to a science. This in turn lets organizations streamline their processes, increase their efficiency, and reduce their operating costs. For this reason, data analysts are in high demand. While technical skills are needed for the job, a salient focus is placed on what soft skills do the incumbent data analysts possess. A lot of data analysts do not adequately acquire these soft skills and therefore fail to realize their full potential. The most impactful work that a highly successful data analyst does comprises non-technical skills. Some crucial skills among these include being able to construct the problem, understand the business context, ask the right questions, find creative solutions, creating visualizations, and presenting the findings. This indispensable book will guide you through these absolutely necessary soft skills that you need in order to excel at your work as a valuable data analyst. Here’s a preview of this fantastic book, and what else you’ll learn: ● The critical contribution of non-technical skills in data analysis ● Using creativity to enable solving more complex problems quickly ● Understanding the business to address the specific needs of enterprises ● Thinking strategically to enhance the effectiveness and efficiency of your work ● Knowing how the human mind works to discover the abilities and limitations of various analytical models ● Using alternative techniques compared to statistical analysis such as qualitative data analysis, analytics, heuristics, etc., to gain a deeper perspective ● Acquiring negotiating skills to better deal with external and internal stakeholders ● Learning to better communicate your data analysis insights ● Being a better writer to be able to better express yourself ….. And much more! As a key bonus, included in this book are chapters that extensively elaborate on designing your findings by means of visualizations and public speaking in order to convincingly present your finding to a group of influential people and executives. The author understands your peculiar concerns and has therefore written this book in a clear and concise manner. The work is also thorough, relevant, and up-to-date. You are not required to be an experienced analyst to read this book. However, you do need to have a zeal for the subject and the passion for improving the outcome of your work. So, if you want to dramatically improve as a data analyst and aspire to reach the zenith of your field, click the “Add to Cart” button, and let’s get started!

Data Science

Data Science
Author: Field Cady
Publisher: John Wiley & Sons
Total Pages: 208
Release: 2020-12-03
Genre: Business & Economics
ISBN: 1119544173

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Tap into the power of data science with this comprehensive resource for non-technical professionals Data Science: The Executive Summary – A Technical Book for Non-Technical Professionals is a comprehensive resource for people in non-engineer roles who want to fully understand data science and analytics concepts. Accomplished data scientist and author Field Cady describes both the “business side” of data science, including what problems it solves and how it fits into an organization, and the technical side, including analytical techniques and key technologies. Data Science: The Executive Summary covers topics like: Assessing whether your organization needs data scientists, and what to look for when hiring them When Big Data is the best approach to use for a project, and when it actually ties analysts’ hands Cutting edge Artificial Intelligence, as well as classical approaches that work better for many problems How many techniques rely on dubious mathematical idealizations, and when you can work around them Perfect for executives who make critical decisions based on data science and analytics, as well as mangers who hire and assess the work of data scientists, Data Science: The Executive Summary also belongs on the bookshelves of salespeople and marketers who need to explain what a data analytics product does. Finally, data scientists themselves will improve their technical work with insights into the goals and constraints of the business situation.

Qualitative Analysis

Qualitative Analysis
Author: Margaretha Järvinen
Publisher: SAGE
Total Pages: 411
Release: 2020-02-06
Genre: Social Science
ISBN: 1529713242

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Introducing eight analytical approaches that are key to successful social science research, this book helps you get to grips with theory and apply it to qualitative analysis. With two ‘matched chapters’ dedicated to each approach, it provides a balance between theory and analytical method. The first chapter grounds the approach in theory and the second uses real-world examples to show how to conduct your own analysis using the approach. Drawing on the contributing authors’ wealth of experience, the book: · Highlights how analysis relates to the entire research process and helps you position your analysis within the larger context of your research · Provides a strong, theoretical foundation for building good qualitative analysis · Guides you through translating theory into real-world practice in your own research Detailed, clear and accessible, this book is perfect for students who want to understand the theory behind qualitative analysis before conducting their own research, or develop their understanding of specific approaches.

Data Analysis for Business, Economics, and Policy

Data Analysis for Business, Economics, and Policy
Author: Gábor Békés
Publisher: Cambridge University Press
Total Pages: 741
Release: 2021-05-06
Genre: Business & Economics
ISBN: 1108483011

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A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.

Excel Data Analysis For Dummies

Excel Data Analysis For Dummies
Author: Paul McFedries
Publisher: John Wiley & Sons
Total Pages: 58
Release: 2018-11-13
Genre: Computers
ISBN: 1119518164

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Take Excel to the next level Excel is the world’s leading spreadsheet application. It’s a key module in Microsoft Office—the number-one productivity suite—and it is the number-one business intelligence tool. An Excel dashboard report is a visual presentation of critical data and uses gauges, maps, charts, sliders, and other graphical elements to present complex data in an easy-to-understand format. Excel Data Analysis For Dummies explains in depth how to use Excel as a tool for analyzing big data sets. In no time, you’ll discover how to mine and analyze critical data in order to make more informed business decisions. Work with external databases, PivotTables, and Pivot Charts Use Excel for statistical and financial functions and data sharing Get familiar with Solver Use the Small Business Finance Manager If you’re familiar with Excel but lack a background in the technical aspects of data analysis, this user-friendly book makes it easy to start putting it to use for you.

The Art of Data Science

The Art of Data Science
Author: Roger D. Peng
Publisher:
Total Pages: 170
Release: 2016-06-08
Genre: Business & Economics
ISBN: 9781365061462

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"This book describes the process of analyzing data. The authors have extensive experience both managing data analysts and conducting their own data analyses, and this book is a distillation of their experience in a format that is applicable to both practitioners and managers in data science."--Leanpub.com.

Data Smart

Data Smart
Author: John W. Foreman
Publisher: John Wiley & Sons
Total Pages: 432
Release: 2013-10-31
Genre: Business & Economics
ISBN: 1118839862

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Data Science gets thrown around in the press like it'smagic. Major retailers are predicting everything from when theircustomers are pregnant to when they want a new pair of ChuckTaylors. It's a brave new world where seemingly meaningless datacan be transformed into valuable insight to drive smart businessdecisions. But how does one exactly do data science? Do you have to hireone of these priests of the dark arts, the "data scientist," toextract this gold from your data? Nope. Data science is little more than using straight-forward steps toprocess raw data into actionable insight. And in DataSmart, author and data scientist John Foreman will show you howthat's done within the familiar environment of aspreadsheet. Why a spreadsheet? It's comfortable! You get to look at the dataevery step of the way, building confidence as you learn the tricksof the trade. Plus, spreadsheets are a vendor-neutral place tolearn data science without the hype. But don't let the Excel sheets fool you. This is a book forthose serious about learning the analytic techniques, the math andthe magic, behind big data. Each chapter will cover a different technique in aspreadsheet so you can follow along: Mathematical optimization, including non-linear programming andgenetic algorithms Clustering via k-means, spherical k-means, and graphmodularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, andbag-of-words models Forecasting, seasonal adjustments, and prediction intervalsthrough monte carlo simulation Moving from spreadsheets into the R programming language You get your hands dirty as you work alongside John through eachtechnique. But never fear, the topics are readily applicable andthe author laces humor throughout. You'll even learnwhat a dead squirrel has to do with optimization modeling, whichyou no doubt are dying to know.

Building Data Products Introduction to Data and Analytics Engineering for Non-Programmers

Building Data Products Introduction to Data and Analytics Engineering for Non-Programmers
Author: Brian McMillan
Publisher:
Total Pages: 475
Release: 2021-07-20
Genre:
ISBN: 9781737536536

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Introducing Data and Analytics Engineering to a diverse group of non-technical people requires a broad exposure to specific technical skills and tools. However, in order to be effective, everyone involved, including non-technical managers, needs to understand the larger philosophy of software development. This book covers both. If you are a manager focused on the difficulties of running a business faced with constant change and competition, this book introduces a number of ways to identify, manage, communicate, and measure what is most valuable. If you are an analyst faced with the simple fact that there are never enough hours in the day to get everything done, this book balances the typical technical demonstrations with software development philosophy and business management strategies you can use to maintain focus on delivering the things with the highest business value in a sustainable way. For seasoned engineers and educators, this book is intended to serve as an introduction to teaching the hard and soft skills needed to effectively understand the entire product lifecycle and foundational philosophies of data and analytics engineering.

Handbook of Data Analysis

Handbook of Data Analysis
Author: Melissa A Hardy
Publisher: SAGE
Total Pages: 729
Release: 2009-06-17
Genre: Social Science
ISBN: 1446203441

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′This book provides an excellent reference guide to basic theoretical arguments, practical quantitative techniques and the methodologies that the majority of social science researchers are likely to require for postgraduate study and beyond′ - Environment and Planning ′The book provides researchers with guidance in, and examples of, both quantitative and qualitative modes of analysis, written by leading practitioners in the field. The editors give a persuasive account of the commonalities of purpose that exist across both modes, as well as demonstrating a keen awareness of the different things that each offers the practising researcher′ - Clive Seale, Brunel University ′With the appearance of this handbook, data analysts no longer have to consult dozens of disparate publications to carry out their work. The essential tools for an intelligent telling of the data story are offered here, in thirty chapters written by recognized experts. ′ - Michael Lewis-Beck, F Wendell Miller Distinguished Professor of Political Science, University of Iowa ′This is an excellent guide to current issues in the analysis of social science data. I recommend it to anyone who is looking for authoritative introductions to the state of the art. Each chapter offers a comprehensive review and an extensive bibliography and will be invaluable to researchers wanting to update themselves about modern developments′ - Professor Nigel Gilbert, Pro Vice-Chancellor and Professor of Sociology, University of Surrey This is a book that will rapidly be recognized as the bible for social researchers. It provides a first-class, reliable guide to the basic issues in data analysis, such as the construction of variables, the characterization of distributions and the notions of inference. Scholars and students can turn to it for teaching and applied needs with confidence. The book also seeks to enhance debate in the field by tackling more advanced topics such as models of change, causality, panel models and network analysis. Specialists will find much food for thought in these chapters. A distinctive feature of the book is the breadth of coverage. No other book provides a better one-stop survey of the field of data analysis. In 30 specially commissioned chapters the editors aim to encourage readers to develop an appreciation of the range of analytic options available, so they can choose a research problem and then develop a suitable approach to data analysis.

How to Become a Data Analyst

How to Become a Data Analyst
Author: Paul Freeman
Publisher: Independently Published
Total Pages: 0
Release: 2024-01-28
Genre: Education
ISBN:

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Unlock the secrets of data and step into the exciting world of "How to Become a Data Analyst." This book is your go-to guide, making the journey from curious explorer to skilled data analyst an adventure of discovery. Dive into the pages of this comprehensive guide, where you'll learn the art and science of decoding data. From understanding the role of a data analyst to mastering powerful tools and techniques, this book is a roadmap for anyone fascinated by the stories hidden in numbers. Whether you're a student with a passion for data or someone looking to kickstart a career in analytics, this book will equip you with the skills needed to navigate the dynamic landscape of data analysis. Uncover the mysteries, embrace the challenges, and become a master of the captivating art and science of data analytics with this essential guide in hand. Your journey to becoming a proficient data analyst starts here!