Databases for Small Business
Databases for Small Business

Author: Anna Manning

Publisher: Apress

Published: 2015-11-21

Total Pages: 319

ISBN-13: 1484202775

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This book covers the practical aspects of database design, data cleansing, data analysis, and data protection, among others. The focus is on what you really need to know to create the right database for your small business and to leverage it most effectively to spur growth and revenue. Databases for Small Business is a practical handbook for entrepreneurs, managers, staff, and professionals in small organizations who are not IT specialists but who recognize the need to ramp up their small organizations’ use of data and to round out their own business expertise and office skills with basic database proficiency. Anna Manning—a data scientist who has worked on database design and data analysis in a computer science university research lab, her own small business, and a nonprofit—walks you through the progression of steps that will enable you to extract actionable intelligence and maximum value from your business data in terms of marketing, sales, customer relations, decision making, and business strategy. Dr. Manning illustrates the steps in the book with four running case studies of a small online business, an engineering startup, a small legal firm, and a nonprofit organization. Databases for Small Business teaches non-techie entrepreneurs and professionals how to: Design a small business database from scratch Extract the maximum profit from your data Follow guidance on data protection law Effectively use data collection and data cleansing techniques Train staff to leverage your data

Practical Data Analysis
Practical Data Analysis

Author: Hector Cuesta

Publisher: Packt Publishing Ltd

Published: 2016-09-30

Total Pages: 330

ISBN-13: 1785286668

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A practical guide to obtaining, transforming, exploring, and analyzing data using Python, MongoDB, and Apache Spark About This Book Learn to use various data analysis tools and algorithms to classify, cluster, visualize, simulate, and forecast your data Apply Machine Learning algorithms to different kinds of data such as social networks, time series, and images A hands-on guide to understanding the nature of data and how to turn it into insight Who This Book Is For This book is for developers who want to implement data analysis and data-driven algorithms in a practical way. It is also suitable for those without a background in data analysis or data processing. Basic knowledge of Python programming, statistics, and linear algebra is assumed. What You Will Learn Acquire, format, and visualize your data Build an image-similarity search engine Generate meaningful visualizations anyone can understand Get started with analyzing social network graphs Find out how to implement sentiment text analysis Install data analysis tools such as Pandas, MongoDB, and Apache Spark Get to grips with Apache Spark Implement machine learning algorithms such as classification or forecasting In Detail Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service. This book explains the basic data algorithms without the theoretical jargon, and you'll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark. Style and approach This is a hands-on guide to data analysis and data processing. The concrete examples are explained with simple code and accessible data.

Big Data in Small Business
Big Data in Small Business

Author: Lund Pedersen, Carsten

Publisher: Edward Elgar Publishing

Published: 2021-09-21

Total Pages: 272

ISBN-13: 1839100168

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This important book considers the ways in which small and medium-sized enterprises (SMEs) can thrive in the age of big data. To address this central issue from multiple viewpoints, the editors introduce a collection of experiences, insights, and guidelines from a variety of expert researchers, each of whom provides a piece to solve this puzzle.