Everyday technology is constantly changing, and it’s hard to keep up with it at times. What is all this talk about automation, STEM, analytics and super-computers, and how will it really affect my daily life at work and in the home? This book is a simple guide to everyday technology and analytics written in plain language. It starts with explaining how computer networks are increasing in speed so fast that we can do more in less time than ever before. It explains the analytical jargon in plain English and why robotics in the home will be aided by the new technology of the quantum computer. Richly furnished with over 200 illustrations, photos and with minimal equations, A Simple Guide to Technology and Analytics is a ready reference book for those times when you don’t really understand the technology and analytics being talked about. It explains complicated topics such as automated character recognition in a very simple way, and has simple exercises for the reader to fully understand the technology (with answers at the back). It even has explanations on how home appliances work, which are very useful the next time you go shopping for a microwave or TV. Even the Glossary at the back can be used as a quick look-up explanation for those on the go.

While exposure to data has become more or less a daily ritual for the rank-and-file knowledge worker, true understanding-treated in this book as data literacy-resides in knowing what lies behind the data. Everything from the data's source to the specific choice of input variables, algorithmic transformations, and visual representation shape the accuracy, relevance, and value of the data and mark its journey from raw data to business insight. It's also important to grasp the terminology and basic concepts of data analytics as much as it is to have the financial literacy to be successful as a decisionmaker in the business world. In this book, we make sense of data analytics without the assumption that you understand specific data science terminology or advanced programming languages to set you on your path. Topics covered in this book: Data Mining Big Data Machine Learning Alternative Data Data Management Web Scraping Regression Analysis Clustering Analysis Association Analysis Data Visualization Business Intelligence

Gain the competitive edge with the smart use of business analytics In today’s volatile business environment, the strategic use of business analytics is more important than ever. A Practitioners Guide to Business Analytics helps you get the organizational commitment you need to get business analytics up and running in your company. It provides solutions for meeting the strategic challenges of applying analytics, such as: Integrating analytics into decision making, corporate culture, and business strategy Leading and organizing analytics within the corporation Applying statistical qualifications, statistical diagnostics, and statistical review Providing effective building blocks to support analytics—statistical software, data collection, and data management Randy Bartlett, Ph.D., is Chief Statistical Officer of the consulting company Blue Sigma Analytics. He currently works with Infosys, where he has helped build their new Business Analytics practice.

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

Advancement in technology and the resulting shifts in everyday practice have brought about a fast-growing "parallel world" with new material, new data, and new sources. Irrespective of how anyone describes it, the data trend is becoming increasingly real, increasingly prevalent, and far more significant. Collating and gathering data is one thing while processing it is an entirely separate issue. It is not something that can be accomplished carelessly by merely staring at the data. If you are hoping to derive reasonable insights from the data generated, you must understand the data you are gathering, the approaches that are required, and the appropriate techniques to use when analyzing this data. How exactly can all this be achieved - well, this is exactly where this book comes in. The book presents the A-Z on the realms of data analytics. It is a beginner's friendly guide. Hence, if you are totally new in the world of data analytics, we've got you covered! In this book, you'll find useful strategies and resources that can be used to derive reasonable insight on the data generated. Hey! Data analytics is not the scary jargon you've probably have heard about. Why not start by buying this book today and uncover those simple yet comprehensive strategies employed in the world of data analytics!What to expect in this book: -Uncover the nitty-gritty of data and big data-The two common data structures employed in data analytics-The essentials of machine learning and how it relates to data analytics-The data analytics life cycle-Unraveling probability distributions and inferential statistics processes-Some machine learning approaches to data analytics-How to clean your data for analysis-Data visualization tools and strategies-Some common analytical and statistical packages in R, -And much more!Let me work with you side by side as we discover the realms of data analytics! Grab your copy now!

Big Data Analytics with Spark is a step-by-step guide for learning Spark, which is an open-source fast and general-purpose cluster computing framework for large-scale data analysis. You will learn how to use Spark for different types of big data analytics projects, including batch, interactive, graph, and stream data analysis as well as machine learning. In addition, this book will help you become a much sought-after Spark expert. Spark is one of the hottest Big Data technologies. The amount of data generated today by devices, applications and users is exploding. Therefore, there is a critical need for tools that can analyze large-scale data and unlock value from it. Spark is a powerful technology that meets that need. You can, for example, use Spark to perform low latency computations through the use of efficient caching and iterative algorithms; leverage the features of its shell for easy and interactive Data analysis; employ its fast batch processing and low latency features to process your real time data streams and so on. As a result, adoption of Spark is rapidly growing and is replacing Hadoop MapReduce as the technology of choice for big data analytics. This book provides an introduction to Spark and related big-data technologies. It covers Spark core and its add-on libraries, including Spark SQL, Spark Streaming, GraphX, and MLlib. Big Data Analytics with Spark is therefore written for busy professionals who prefer learning a new technology from a consolidated source instead of spending countless hours on the Internet trying to pick bits and pieces from different sources. The book also provides a chapter on Scala, the hottest functional programming language, and the program that underlies Spark. You’ll learn the basics of functional programming in Scala, so that you can write Spark applications in it. What's more, Big Data Analytics with Spark provides an introduction to other big data technologies that are commonly used along with Spark, like Hive, Avro, Kafka and so on. So the book is self-sufficient; all the technologies that you need to know to use Spark are covered. The only thing that you are expected to know is programming in any language. There is a critical shortage of people with big data expertise, so companies are willing to pay top dollar for people with skills in areas like Spark and Scala. So reading this book and absorbing its principles will provide a boost—possibly a big boost—to your career.

Thought you couldn’t learn statistics? You can – and you will! Even You Can Learn Statistics and Analytics, Third Edition is the practical, up-to-date introduction to statistics – for everyone! Now fully updated for "big data" analytics and the newest applications, it'll teach you all the statistical techniques you’ll need for finance, marketing, quality, science, social science, and more – one easy step at a time. Simple jargon-free explanations help you understand every technique, and extensive practical examples and worked problems give you all the hands-on practice you'll need. This edition contains more practical examples than ever – all updated for the newest versions of Microsoft Excel. You'll find downloadable practice files, templates, data sets, and sample models – including complete solutions you can put right to work! Learn how to do all this, and more: Apply statistical techniques to analyze huge data sets and transform them into valuable knowledge Construct and interpret statistical charts and tables with Excel or OpenOffice.org Calc 3 Work with mean, median, mode, standard deviation, Z scores, skewness, and other descriptive statistics Use probability and probability distributions Work with sampling distributions and confidence intervals Test hypotheses with Z, t, chi-square, ANOVA, and other techniques Perform powerful regression analysis and modeling Use multiple regression to develop models that contain several independent variables Master specific statistical techniques for quality and Six Sigma programs Hate math? No sweat. You’ll be amazed at how little you need. Like math? Optional "Equation Blackboard" sections reveal the mathematical foundations of statistics right before your eyes. If you need to understand, evaluate, or use statistics in business, academia, or anywhere else, this is the book you've been searching for!