Data Analytics Basics
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Data Analytics Basics
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Author : Simplilearn
language : en
Publisher: IndraStra Whitepapers
Release Date : 2020-12-14
Data Analytics Basics written by Simplilearn and has been published by IndraStra Whitepapers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-14 with Computers categories.
Data analytics is increasingly becoming a key element in shaping a company’s business strategy. Today, data influences every decision made by an organization, and this is driving the wide-scale adoption of data analytics, including machine learning technologies and artificial intelligence solutions. The heightened focus is propelling a surge in data analytics spending, reflected in various studies conducted by leading market research firms. The field of data analytics offers some amazing salaries and is not only the hottest IT job, but it is also one of the best-paying jobs in the world. This guide aims at providing the readers with everything they need to know about the data analytics field, basic terminologies, key concepts, real-life use cases, skills you must master in order to scale up your career, and training and certifications you might need to reach your dream job.
Hbr Guide To Data Analytics Basics For Managers Hbr Guide Series
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Author : Harvard Business Review
language : en
Publisher: Harvard Business Press
Release Date : 2018-03-13
Hbr Guide To Data Analytics Basics For Managers Hbr Guide Series written by Harvard Business Review and has been published by Harvard Business Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-13 with Business & Economics categories.
Don't let a fear of numbers hold you back. Today's business environment brings with it an onslaught of data. Now more than ever, managers must know how to tease insight from data--to understand where the numbers come from, make sense of them, and use them to inform tough decisions. How do you get started? Whether you're working with data experts or running your own tests, you'll find answers in the HBR Guide to Data Analytics Basics for Managers. This book describes three key steps in the data analysis process, so you can get the information you need, study the data, and communicate your findings to others. You'll learn how to: Identify the metrics you need to measure Run experiments and A/B tests Ask the right questions of your data experts Understand statistical terms and concepts Create effective charts and visualizations Avoid common mistakes
Fundamentals Of Data Analytics
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Author : Russell Dawson
language : en
Publisher: Jws Publishing
Release Date : 2023-12-20
Fundamentals Of Data Analytics written by Russell Dawson and has been published by Jws Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-20 with Computers categories.
Gain a competitive edge in today's data-driven world and build a rich career as a data professional that drives business success and innovation... Did you know that every minute, people around the world make 5.9 million searches on Google, share 1.7 million posts on Facebook, and watch 1 million hours of videos? And that's not even all of it! In total, the world creates a massive 328 million terabytes of data every day! Data is everywhere... and it has become the essential building block of this modern society, shaping the future of businesses, technology, and human interactions. It's no wonder that data professional roles, such as data analysts, data scientists, and data architects are now highly in demand in this data-driven world. And that's why now is the perfect time to pursue a career in data. But what does it take to become a competent data professional? This book has all the answers! Building a successful career in data is all about cultivating the necessary mindset, knowledge, and skills. This book is your ultimate guide to understanding the fundamentals of data analytics, helping you unlock the expertise of efficiently solving real-world data-related problems. Here is just a fraction of what you will discover: A comprehensive guide to the data analytics process - a beginner-friendly 5-step framework to kickstart your journey into analyzing and processing data How to get started with the fundamental concepts, theories, and models for accurately analyzing data Everything you ever needed to know about data mining and machine learning principles - your gateway to unlocking the secrets of data's hidden potential Why business run on a data-driven culture, and how you can leverage it using real-time business intelligence analytics Strategies and techniques to build a problem-solving mindset that can overcome any complex and unique dataset How to create compelling and dynamic visualizations that help generate insights and make data-driven decisions The 4 pillars of a new digital world - discover how emerging technologies will transform the landscape of analyzing data And much more. Believe it or not, you can be terrible in math or statistics and still pursue a career in data. Yes, you need a good grasp of the basics but always keep in mind that knowledge can be acquired and skills can be developed. The key is to not be intimidated by the strings of characters and numbers. Focus, instead, on building a mindset that thirsts for knowledge. You'll be surprised by how much you're able to do with just that. And this book is here to guide you throughout this journey, so that crunching data becomes second nature to you. So, what are you waiting for? Ready to master the fundamentals and build a successful career in data analytics?
Things To Know About Data Analysis
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Author : Patrick Richeson
language : en
Publisher:
Release Date : 2021-03-29
Things To Know About Data Analysis written by Patrick Richeson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-29 with categories.
As the process of analyzing raw data to find trends and answer questions, the definition of data analysis captures the wide range of the field. Whether you are a beginner or an experienced person, mastering your data analysis skills is always a challenge. You want to learn about data analysis but can't find a book with the right computer concept distribution, Or you are trying to improve your data analysis skills but want interesting examples taste with them? This book here is for you Here are some key features of this book. -Emphasis on practical examples and how the advanced techniques described in the chapters can be used in real-life to improve clarity and understanding. -Various topics such as sophisticated algorithms or even the Euclidean Square Estimate are approached in a way that the reader can understand the very basics of it and then be introduced to the technical jargon. -This ensures that the reader does not get lost in all of the mathematical and statistical words. -Efficient demonstration of almost every practical topic with the use of Python so that the readers can recreate the projects by themselves. If you're interested in taking a journey through the realms of advanced data analytic, this book is very suitable for you. Buy it right now
An Introduction To Data Analysis
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Author : Jarrod Daehn
language : en
Publisher: Independently Published
Release Date : 2022-01-26
An Introduction To Data Analysis written by Jarrod Daehn and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-26 with categories.
It is just the initial step, be that as it may, which is the reason the accompanying parts will examine all that you want to be familiar with information examination overall and prescient investigation explicitly. This implies there are nitty-gritty sections on information gathering, information mining, relapse methods, AI strategies, discrete decision models, and that's just the beginning. You will likewise observe a top to bottom glance at a significant number of the most widely recognized slip-ups that organizations make with regards to information the executives and how to keep away from them. At last, things will wrap up with a point-by-point conversation of the best open-source programs that can make them examine information this very evening. Inside you will find: -A Complete Breakdown of the Basics of Data Analytics and Predictive Analysis -The Secrets the Pros Use When It Comes to Data Mining and Data Gathering -Information Management Mistakes to Avoid -The Best Beginner Regression and Machine Learning Techniques -The Best Free Programs to Get You Started -What's more a whole lot more...
Learn Data Analytics For Beginners To Core Advance
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Author : Janani Sathish
language : en
Publisher: Independently Published
Release Date : 2021-05
Learn Data Analytics For Beginners To Core Advance written by Janani Sathish and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05 with categories.
Data science has taken the planet by storm. Every field of study and area of business has been affected as people increasingly realize the worth of the incredible quantities of knowledge being generated. But to extract value from those data, one must be trained within the proper data science skills. The R programming language has become the de facto programming language for data science. Its flexibility, power, sophistication, and expressiveness have made it a useful tool for data scientists round the world. This book is about the basics of R programming. you'll start with the fundamentals of the language, find out how to control datasets, the way to write functions, and the way to debug and optimize code. With the basics provided during this book, you'll have a solid foundation on which to create your data science toolbox. during this book you'll learn what you would like to understand to start assembling and leading a knowledge science enterprise, albeit you've got never worked in data science before. You'll get a crash program in data science in order that you'll be familiar with the sector and understand your role as a pacesetter . You'll also find out how to recruit, assemble, evaluate, and develop a team with complementary skill sets and roles. You'll learn the structure of the info science pipeline, the goals of every stage, and the way to stay your team on track throughout. Finally, you'll learn some down-to-earth practical skills which will assist you overcome the common challenges that regularly derail data science projects Reproducibility is that the concept data analyses should be published or made available with their data and software code in order that others may verify the findings and repose on them.
Python Data Analytics And Visualization
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Author : Phuong Vo.T.H
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-03-31
Python Data Analytics And Visualization written by Phuong Vo.T.H and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-31 with Computers categories.
Understand, evaluate, and visualize data About This Book Learn basic steps of data analysis and how to use Python and its packages A step-by-step guide to predictive modeling including tips, tricks, and best practices Effectively visualize a broad set of analyzed data and generate effective results Who This Book Is For This book is for Python Developers who are keen to get into data analysis and wish to visualize their analyzed data in a more efficient and insightful manner. What You Will Learn Get acquainted with NumPy and use arrays and array-oriented computing in data analysis Process and analyze data using the time-series capabilities of Pandas Understand the statistical and mathematical concepts behind predictive analytics algorithms Data visualization with Matplotlib Interactive plotting with NumPy, Scipy, and MKL functions Build financial models using Monte-Carlo simulations Create directed graphs and multi-graphs Advanced visualization with D3 In Detail You will start the course with an introduction to the principles of data analysis and supported libraries, along with NumPy basics for statistics and data processing. Next, you will overview the Pandas package and use its powerful features to solve data-processing problems. Moving on, you will get a brief overview of the Matplotlib API .Next, you will learn to manipulate time and data structures, and load and store data in a file or database using Python packages. You will learn how to apply powerful packages in Python to process raw data into pure and helpful data using examples. You will also get a brief overview of machine learning algorithms, that is, applying data analysis results to make decisions or building helpful products such as recommendations and predictions using Scikit-learn. After this, you will move on to a data analytics specialization—predictive analytics. Social media and IOT have resulted in an avalanche of data. You will get started with predictive analytics using Python. You will see how to create predictive models from data. You will get balanced information on statistical and mathematical concepts, and implement them in Python using libraries such as Pandas, scikit-learn, and NumPy. You'll learn more about the best predictive modeling algorithms such as Linear Regression, Decision Tree, and Logistic Regression. Finally, you will master best practices in predictive modeling. After this, you will get all the practical guidance you need to help you on the journey to effective data visualization. Starting with a chapter on data frameworks, which explains the transformation of data into information and eventually knowledge, this path subsequently cover the complete visualization process using the most popular Python libraries with working examples This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Getting Started with Python Data Analysis, Phuong Vo.T.H &Martin Czygan Learning Predictive Analytics with Python, Ashish Kumar Mastering Python Data Visualization, Kirthi Raman Style and approach The course acts as a step-by-step guide to get you familiar with data analysis and the libraries supported by Python with the help of real-world examples and datasets. It also helps you gain practical insights into predictive modeling by implementing predictive-analytics algorithms on public datasets with Python. The course offers a wealth of practical guidance to help you on this journey to data visualization
Predictive Analytics For Dummies
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Author : Anasse Bari
language : en
Publisher: John Wiley & Sons
Release Date : 2014-03-06
Predictive Analytics For Dummies written by Anasse Bari and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-06 with Business & Economics categories.
Combine business sense, statistics, and computers in a new and intuitive way, thanks to Big Data Predictive analytics is a branch of data mining that helps predict probabilities and trends. Predictive Analytics For Dummies explores the power of predictive analytics and how you can use it to make valuable predictions for your business, or in fields such as advertising, fraud detection, politics, and others. This practical book does not bog you down with loads of mathematical or scientific theory, but instead helps you quickly see how to use the right algorithms and tools to collect and analyze data and apply it to make predictions. Topics include using structured and unstructured data, building models, creating a predictive analysis roadmap, setting realistic goals, budgeting, and much more. Shows readers how to use Big Data and data mining to discover patterns and make predictions for tech-savvy businesses Helps readers see how to shepherd predictive analytics projects through their companies Explains just enough of the science and math, but also focuses on practical issues such as protecting project budgets, making good presentations, and more Covers nuts-and-bolts topics including predictive analytics basics, using structured and unstructured data, data mining, and algorithms and techniques for analyzing data Also covers clustering, association, and statistical models; creating a predictive analytics roadmap; and applying predictions to the web, marketing, finance, health care, and elsewhere Propose, produce, and protect predictive analytics projects through your company with Predictive Analytics For Dummies.
Data Science 101
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Author : Andrew Park
language : en
Publisher: Andrew Park
Release Date : 2021-02-13
Data Science 101 written by Andrew Park and has been published by Andrew Park this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-13 with categories.
★ 55% OFF for Bookstores! NOW at $ 23,97 instead of $33.97! LAST DAYS! ★ Your Customers Will Never Stop To Use This Amazing Guide! Do you want to know how Data science helps in business? This book will discuss everything that we need to know when it comes to data science and how to complete the process of data science with Python. There are so many different parts that come together when we work on data science, but if you are able to put it all together, and work to really analyze the information that you have to beat out the competition, you will find that data science with Python can be the right move for you. We will explore how so many businesses will take the time to gather up information, usually from a variety of sources, and then will be unsure of what they should do with that information once they have collected it. We can then take a look at the data life cycle and how we can take that information, clean it off, analyze it, and come up with insights and predictions that help grow our business more than ever before. We will spend this time looking what Python is about, how to download the program on your chosen operating system, and some of the basics that come with coding in Python. This guidebook went through all of the steps that you need to know in order to get started with data science and some of the basic parts of the Python code. We can then put all of this together in order to create the right analytical algorithm that, once it is trained properly and tested with the right kinds of data, will work to make predictions, provide information, and even show us insights that were never possible before. And all that you need to do to get this information is to use the steps that we outline and discuss in this guidebook. There is a lot of buzz in the business world, no matter what industry it is, about machine learning, the Python language, and of course, data science, and being able to put these terms together and learn how they work can make a big difference in how well your business will do now and in the future. There are already a ton of companies out there who have been able to gain a competitive edge with data science and the various models and algorithms of Python that go with it, and you can as well. This book covers: What is Data Science? The Python Coding Language Some of the Basic Coding in Python The Best Python Libraries to Use with Data Science The Basics of Jupyter and Why We Should Use It Working with Anaconda in Python The Basics of the Pandas Library What is WinPython and How Can We Use It? Common Tasks to Do in Info Science Different Data Types to Work With The Future of Data Science and Where It Will Go from Here There are so many great ways that you can use the data you have been collecting for some time now and being able to complete the process of data visualization will ensure that you get it all done. When you are ready to get started with Python data science, make sure to check out this guidebook to learn how. There is so much that can come into play when we work with data science, and it is one of the best ways for a business to differentiate from the competition and actually see some results in the process. And the Python language is a great option to learn to help us analyze and create a model that works with the info that we have. When we are ready to learn more about data science, and how to use the Python coding language to go with it, make sure to check out this guidebook to help you get started. Buy it NOW and let your customers get addicted to this amazing book!
Fundamentals Of Data Analytics
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Author : Rudolf Mathar
language : en
Publisher: Springer Nature
Release Date : 2020-09-15
Fundamentals Of Data Analytics written by Rudolf Mathar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-15 with Mathematics categories.
This book introduces the basic methodologies for successful data analytics. Matrix optimization and approximation are explained in detail and extensively applied to dimensionality reduction by principal component analysis and multidimensional scaling. Diffusion maps and spectral clustering are derived as powerful tools. The methodological overlap between data science and machine learning is emphasized by demonstrating how data science is used for classification as well as supervised and unsupervised learning.