關於Data Shaping技術,特急!!

Jameszht 2002-05-13 05:03:58
我的工程用到data shaping.

數據源的提供者應是MsDataShape,但是在connecton.open中,系統提示,不能初始化數據源.

如果提供者是sqloledb.1,在recordset.open中則提示語法錯誤。請在這方面有經驗的同志們給予幫助.
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Jameszht 2002-05-13
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Jameszht 2002-05-13
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但是系統不能初始化MSDateShape數據源,是怎麼回事?
kevincomein 2002-05-13
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以下范例说明了访问分级 Recordset 中的行的所需步骤:

authors 和 titleauthors 表中的 Recordset 对象通过 author ID 进行关联。


外循环显示每个作者的姓名、州/省别和身份。


每行所追加的 Recordset 都从 Fields 集合进行检索并分配给 rsChapter。


内循环显示追加的 Recordset 中每行的四个字段。
范例

Sub datashape()
Dim cnn As New ADODB.Connection
Dim rst As New ADODB.Recordset
Dim rsChapter As Variant

cnn.Provider = "MSDataShape"
cnn.Open "Data Provider=MSDASQL;" & _
"DSN=vfox;uid=sa;pwd=vfox;database=pubs”
'步骤 1
rst.StayInSync = FALSE
rst.Open "SHAPE {select * from authors}
APPEND ({select * from titleauthor} AS chapter
RELATE au_id TO au_id)",
cnn
'步骤 2
While Not rst.EOF
Debug.Print rst("au_fname"), rst("au_lname"),
rst("state"), rst("au_id")
'步骤 3
Set rsChapter = rst("chapter")
'步骤 4
While Not rsChapter.EOF
Debug.Print rsChapter(0), rsChapter(1),
rsChapter(2), rsChapter(3)
rsChapter.MoveNext
Wend
rst.MoveNext
Wend
End Sub

Key Features An easy to follow guide taking you through every step of the data wrangling process in the best possible way Work with different types of datasets, and reshape the layout of your data to make it easier for analysis Simple examples and real-life data wrangling solutions for data pre-processing Book Description Around 80% of time in data analysis is spent on cleaning and preparing data for analysis. This is, however, and important task, and is a prerequisite to the rest of the data analysis workflow, including visualization, analysis and reporting. Python and R are considered a popular choice of tool for data analysis, and have packages which can be best used to manipulate different kinds of data, as per your requirement. This book will show you the different data wrangling techniques, and how you can leverage the power of Python and R packages to implement them. You will start with understanding the data wrangling process and get a solid foundation for working with different types of data. You will work with different data structures and aqquire and parse data from various locations. The book will also show you how to reshape the layout of data and manipulate, summarize, and join data sets. Finally, the book includes a quick primer on accessing and processing data from databases, conduct data exploration, and store and retrieve data quickly using databases. The book will include practical examples on each of the above pointers using simple and real-world datasets for easier understanding. By the end of the book, you will have a thorough understanding of all the data wrangling concepts and how to implement them in the best possible way. What you will learn Read a csv file into python and R, and print out some statistics on the data. Gain knowledge of the data formats and programming stuctures involved in retrieving API data. Make effective use of regular expression in the data wrangling process. Explore the tools and packages available for preparing numerical data for analysis. Learn how to have better control over the manupulation of the structure of the data. Create a dexterity for programmatically reading, auditing, correcting, and shaping data. Write and complete programs for taking in, formatting and outputting datasets.
Analyzing Data with Power BI and Power Pivot for Excel (Business Skills) by Alberto Ferrari English | 25 Apr. 2017 | ASIN: B0713N6BBW | 256 Pages | AZW3 | 21.78 MB Renowned DAX experts Alberto Ferrari and Marco Russo teach you how to design data models for maximum efficiency and effectiveness. How can you use Excel and Power BI to gain real insights into your information? As you examine your data, how do you write a formula that provides the numbers you need? The answers to both of these questions lie with the data model. This book introduces the basic techniques for shaping data models in Excel and Power BI. It’s meant for readers who are new to data modeling as well as for experienced data modelers looking for tips from the experts. If you want to use Power BI or Excel to analyze data, the many real-world examples in this book will help you look at your reports in a different way–like experienced data modelers do. As you’ll soon see, with the right data model, the correct answer is always a simple one! By reading this book, you will: • Gain an understanding of the basics of data modeling, including tables, relationships, and keys • Familiarize yourself with star schemas, snowflakes, and common modeling techniques • Learn the importance of granularity • Discover how to use multiple fact tables, like sales and purchases, in a complex data model • Manage calendar-related calculations by using date tables • Track historical attributes, like previous addresses of customers or manager assignments • Use snapshots to compute quantity on hand • Work with multiple currencies in the most efficient way • Analyze events that have durations, including overlapping durations • Learn what data model you need to answer your specific business questions About This Book • For Excel and Power BI users who want to exploit the full power of their favorite tools • For BI professionals seeking new ideas for modeling data

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