Описание: Microsoft Power Automate is a workflow automation solution included in Microsoft 365. This book explores the core concepts of workflow automation, such as working with connectors, triggers, and actions, along with their practical implementation in automating business tasks and simplifying digital processes to boost enterprise productivity.
Описание: Data mining is an important branch of computer science and information technology management that deals with the discovery and analysis of datasets. This book covers in detail some existent theories as well as innovative concepts revolving around data mining such as bio data analytics, analysis of social structures and patterns, correlations and fluctuations, etc. With its detailed analyses and data, this book will prove immensely beneficial to professionals and students involved in this area at various levels.
Описание: This illuminating text/reference surveys the state of the art in data science, and provides practical guidance on big data analytics. presents techniques for machine learning for big data, and identifying duplicate records in data repositories;
Описание: Offers information related to issues and solutions in data mining and the influence of political and socioeconomic factors. This book includes coverage of issues and technological solutions in data mining, and covers problems with applicable laws governing such issues.
Описание: Provides case studies developed by faculty and graduates of the University of Louisville`s PhD program in Applied and Industrial Mathematics. The studies use non-traditional, exploratory data analysis and data mining tools to examine health outcomes, finding patterns and trends in observational data. It is ideal for the next generation of data mining practitioners.
Автор: Sarka Dejan Название: Data Science with SQL Server Quick Start Guide ISBN: 1789537126 ISBN-13(EAN): 9781789537123 Издательство: Неизвестно Рейтинг: Цена: 8079.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: SQL Server started to fully support data science only with its last two editions. If you are a professional from both worlds, SQL Server and data science, and interested in using SQL Server and Machine Learning Services for their projects, then this is the ideal book for you.
Are you looking for a complete guide on sql? If yes, keep reading...
As programming is commonly intensive, the same may be said with SQL because it also takes different pathways for the successful development of an operational database system. Some may term SQL as a computer programming language because it takes the form of commands, which consists of instructions for the system to engage in a particular action like most programming tools. On the other hand, others refer to it as a data management system as it involves the creation of multiple tables organized under one or more databases essential for the storage of data.
Therefore, scientists and developers conclude that SQL is a standard computer language which helps in the communication between different database systems.
The first SQL model was developed by Ted Code, who introduced the ability of communication between different storage units. His idea was later acquired by Donald Chamberlin and Raymond Boyce and developed the model in the 1970s.
However, the version at the time was referred to as SEQUEL (Structured English Query Language) specifically designed to help in data storage and retrieval. More modifications were made over the years in IBM, with the first being done in a laboratory in San Jose, California, United States, where the first subscript notation was introduced. After testing the effectiveness of the software in customer test websites, SQL was then developed for use commercially after its usefulness and practicality determined.
Today, nearly all businesses around the world have turned into digital handling of data, which keeps growing daily. Ranging from small online business stores to large organizations such as Fortune 500 utilize databases as a way to store and manage this information. This way, SQL has gained popularity over time with demand for more database administrators increasing each passing day.
There are a lot of times when we will want to work with a database to help our business to grow and to keep all of the data and information that we have that concerns our business in order. And the SQL language is going to ensure that we are able to make all of this happen for our needs.
This book covers:
SQL (What it is and What it is used for)
Operators
Data Definition Language
Data Control Language
Data Manipulation Language
Data Control Language
Data Control Language
Stored Program
Subquery and many more
If you're trying to dive into learning SQL, you may feel frazzled and lost. It may look like a bunch of meaningless words and texts put in random order. Rest assured, there is sense to this language and it is quite easy to navigate through when you are given the necessary tools to understand it. In a lot of ways, SQL can have many similarities to the English language itself. You just need to understand how to formulate commands in order to be successful with the language. In the same way that we formulate sentences every day in order to communicate with individuals around us, the same goes for SQL when it comes to databases.
When you are ready to learn more about SQL and how this language can make the management and all of the other parts of running our database easier, make sure to read through this guidebook to help you get started.
Автор: Paola Pucci; Fabio Manfredini; Paolo Tagliolato Название: Mapping Urban Practices Through Mobile Phone Data ISBN: 331914832X ISBN-13(EAN): 9783319148328 Издательство: Springer Рейтинг: Цена: 7836.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book explains the potential value of using mobile phone data to monitor urban practices and identify rhythms of use in today`s cities.
Описание: This book aims to identify promising future developmental opportunities and applications for Tech Mining. Specifically, the enclosed contributions will pursue three converging themes:The increasing availability of electronic text data resources relating to Science, Technology and Innovation (ST&I).The multiple methods that are able to treat this data effectively and incorporate means to tap into human expertise and interests.Translating those analyses to provide useful intelligence on likely future developments of particular emerging S&T targets. Tech Mining can be defined as text analyses of ST&I information resources to generate Competitive Technical Intelligence (CTI). It combines bibliometrics and advanced text analytic, drawing on specialized knowledge pertaining to ST&I. Tech Mining may also be viewed as a special form of “Big Data” analytics because it searches on a target emerging technology (or key organization) of interest in global databases. One then downloads, typically, thousands of field-structured text records (usually abstracts), and analyses those for useful CTI. Forecasting Innovation Pathways (FIP) is a methodology drawing on Tech Mining plus additional steps to elicit stakeholder and expert knowledge to link recent ST&I activity to likely future development. A decade ago, we demeaned Management of Technology (MOT) as somewhat self-satisfied and ignorant. Most technology managers relied overwhelmingly on casual human judgment, largely oblivious of the potential of empirical analyses to inform R&D management and science policy. CTI, Tech Mining, and FIP are changing that. The accumulation of Tech Mining research over the past decade offers a rich resource of means to get at emerging technology developments and organizational networks to date. Efforts to bridge from those recent histories of development to project likely FIP, however, prove considerably harder. One focus of this volume is to extend the repertoire of information resources; that will enrich FIP.Featuring cases of novel approaches and applications of Tech Mining and FIP, this volume will present frontier advances in ST&I text analytics that will be of interest to students, researchers, practitioners, scholars and policy makers in the fields of R&D planning, technology management, science policy and innovation strategy.
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