國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Advanced analytics with Transact-SQL...

Sarka, Dejan.

Advanced analytics with Transact-SQLexploring hidden patterns and rules in your data /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Advanced analytics with Transact-SQLby Dejan Sarka.
其他題名:	exploring hidden patterns and rules in your data /
作者:	Sarka, Dejan.
出版者:	Berkeley, CA :Apress :2021.
面頁冊數:	xix, 302 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Big data.
電子資源:	https://doi.org/10.1007/978-1-4842-7173-5
ISBN:	9781484271735$q(electronic bk.)

Advanced analytics with Transact-SQLexploring hidden patterns and rules in your data /
Sarka, Dejan.

Advanced analytics with Transact-SQLexploring hidden patterns and rules in your data /[electronic resource] :by Dejan Sarka. - Berkeley, CA :Apress :2021. - xix, 302 p. :ill., digital ;24 cm.

Part I. Statistics -- 1. Descriptive Statistics -- 2. Associations Between Pairs of Variables -- Part II. Data Preparation and Quality -- 3. Data Preparation -- 4. Data Quality and Information -- Part III. Dealing with Time -- 5. Time-Oriented Data -- 6. Time-Oriented Analyses -- Part IV. Data Science -- 7. Data Mining -- 8. Text Mining.

Learn about business intelligence (BI) features in T-SQL and how they can help you with data science and analytics efforts without the need to bring in other languages such as R and Python. This book shows you how to compute statistical measures using your existing skills in T-SQL. You will learn how to calculate descriptive statistics, including centers, spreads, skewness, and kurtosis of distributions. You will also learn to find associations between pairs of variables, including calculating linear regression formulas and confidence levels with definite integration. No analysis is good without data quality. Advanced Analytics with Transact-SQL introduces data quality issues and shows you how to check for completeness and accuracy, and measure improvements in data quality over time. The book also explains how to optimize queries involving temporal data, such as when you search for overlapping intervals. More advanced time-oriented information in the book includes hazard and survival analysis. Forecasting with exponential moving averages and autoregression is covered as well. Every web/retail shop wants to know the products customers tend to buy together. Trying to predict the target discrete or continuous variable with few input variables is important for practically every type of business. This book helps you understand data science and the advanced algorithms use to analyze data, and terms such as data mining, machine learning, and text mining. Key to many of the solutions in this book are T-SQL window functions. Author Dejan Sarka demonstrates efficient statistical queries that are based on window functions and optimized through algorithms built using mathematical knowledge and creativity. The formulas and usage of those statistical procedures are explained so you can understand and modify the techniques presented. T-SQL is supported in SQL Server, Azure SQL Database, and in Azure Synapse Analytics. There are so many BI features in T-SQL that it might become your primary analytic database language. If you want to learn how to get information from your data with the T-SQL language that you already are familiar with, then this is the book for you. You will learn to: Describe distribution of variables with statistical measures Find associations between pairs of variables Evaluate the quality of the data you are analyzing Perform time-series analysis on your data Forecast values of a continuous variable Perform market-basket analysis to predict customer purchasing patterns Predict target variable outcomes from one or more input variables Categorize passages of text by extracting and analyzing keywords.

ISBN: 9781484271735$q(electronic bk.)

Standard No.: 10.1007/978-1-4842-7173-5doiSubjects--Topical Terms:

609582
Big data.

LC Class. No.: QA76.9.B45 / S37 2021

Dewey Class. No.: 005.7

Advanced analytics with Transact-SQLexploring hidden patterns and rules in your data /
LDR:04021nmm a2200325 a 4500 001 605643
003 DE-He213
005 20210716093243.0
006 m d
007 cr nn 008maaau
008 211201s2021 cau s 0 eng d
020 $a 9781484271735$q(electronic bk.)
020 $a 9781484271728$q(paper)
024 7 $a 10.1007/978-1-4842-7173-5 $2 doi
035 $a 978-1-4842-7173-5
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.B45 $b S37 2021
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
072 7 $a PBT $2 thema
082 0 4 $a 005.7 $2 23
090 $a QA76.9.B45 $b S245 2021
100 1 $a Sarka, Dejan. $3 901896
245 1 0 $a Advanced analytics with Transact-SQL $h [electronic resource] : $b exploring hidden patterns and rules in your data / $c by Dejan Sarka.
260 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2021.
300 $a xix, 302 p. : $b ill., digital ; $c 24 cm.
505 0 $a Part I. Statistics -- 1. Descriptive Statistics -- 2. Associations Between Pairs of Variables -- Part II. Data Preparation and Quality -- 3. Data Preparation -- 4. Data Quality and Information -- Part III. Dealing with Time -- 5. Time-Oriented Data -- 6. Time-Oriented Analyses -- Part IV. Data Science -- 7. Data Mining -- 8. Text Mining.
520 $a Learn about business intelligence (BI) features in T-SQL and how they can help you with data science and analytics efforts without the need to bring in other languages such as R and Python. This book shows you how to compute statistical measures using your existing skills in T-SQL. You will learn how to calculate descriptive statistics, including centers, spreads, skewness, and kurtosis of distributions. You will also learn to find associations between pairs of variables, including calculating linear regression formulas and confidence levels with definite integration. No analysis is good without data quality. Advanced Analytics with Transact-SQL introduces data quality issues and shows you how to check for completeness and accuracy, and measure improvements in data quality over time. The book also explains how to optimize queries involving temporal data, such as when you search for overlapping intervals. More advanced time-oriented information in the book includes hazard and survival analysis. Forecasting with exponential moving averages and autoregression is covered as well. Every web/retail shop wants to know the products customers tend to buy together. Trying to predict the target discrete or continuous variable with few input variables is important for practically every type of business. This book helps you understand data science and the advanced algorithms use to analyze data, and terms such as data mining, machine learning, and text mining. Key to many of the solutions in this book are T-SQL window functions. Author Dejan Sarka demonstrates efficient statistical queries that are based on window functions and optimized through algorithms built using mathematical knowledge and creativity. The formulas and usage of those statistical procedures are explained so you can understand and modify the techniques presented. T-SQL is supported in SQL Server, Azure SQL Database, and in Azure Synapse Analytics. There are so many BI features in T-SQL that it might become your primary analytic database language. If you want to learn how to get information from your data with the T-SQL language that you already are familiar with, then this is the book for you. You will learn to: Describe distribution of variables with statistical measures Find associations between pairs of variables Evaluate the quality of the data you are analyzing Perform time-series analysis on your data Forecast values of a continuous variable Perform market-basket analysis to predict customer purchasing patterns Predict target variable outcomes from one or more input variables Categorize passages of text by extracting and analyzing keywords.
650 0 $a Big data. $3 609582
650 0 $a Business intelligence $x Data processing. $3 283177
650 0 $a SQL (Computer program language) $3 189402
650 1 4 $a Statistics, general. $3 275684
650 2 4 $a Microsoft and .NET. $3 760507
650 2 4 $a Database Management. $3 273994
650 2 4 $a Applied Statistics. $3 805583
650 2 4 $a Data Structures and Information Theory. $3 825714
650 2 4 $a Artificial Intelligence. $3 212515
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-1-4842-7173-5
950 $a Professional and Applied Computing (SpringerNature-12059)