我們?yōu)槟峁└茫欤嗫膳渲玫腟harePoint表格。不用打開一個SharePoint屬性列表就能獲取即時的交互結果,如分組,排序和嵌套。使用ComponentOne DataGrid™ for SharePoint,它與添加DataGrid Web Part到您的頁面和指向您的數(shù)據(jù)源一樣容易!
We give you a better, faster, more configurable grid for SharePoint. Get instant interactivity such as grouping, sorting, and nesting without opening a SharePoint property list. With ComponentOne DataGrid™ for SharePoint it's as easy as adding the DataGrid Web Part to your page and pointing to your data source!
容易配置
所有的的ComponentOne Web Part使用的是一個板載的設計器,其可以快速地配置外觀,行為,數(shù)據(jù)和首選項。在Web Part的左上角懸停使設計器的處理手柄出現(xiàn)。只要按一下手柄,就可以開始配置您的Web Part。
數(shù)據(jù)分組
在分組區(qū)域上任意拖放一列,DataGrid for SharePoint將會自動地為您的數(shù)據(jù)分組。并且分組的SharePoint List和SQL Server數(shù)據(jù)從未這樣簡單。您甚至可以通過拖放額外的列來分組多層次數(shù)據(jù)。
滾動功能
有幾百甚至上千行的數(shù)據(jù)集是很常見的;尤其是在訪問SQL Server數(shù)據(jù)時。DataGrid for SharePoint允許您能平滑地滾動任意數(shù)量的數(shù)據(jù)而不用等待頁面的刷新。
主-從關系
使用DataGrid for SharePoint能夠能容易而簡單的實現(xiàn)和建立導航相關的數(shù)據(jù)庫表格和列表。該板載的設計器用于選擇表格和相關的列,然后對于任意數(shù)據(jù)行,您可以快速地獲取到細節(jié)內容。
Easy Configuration
All of the ComponentOne Web Parts use an on-board designer that makes configuring the appearance, behavior, data, and preferences a snap. Hovering over the upper-left corner of the Web Part causes the designer’s handle to appear. Just click the handle to begin configuring your Web Part.
Data Grouping
Drag-and-drop a column onto the grouping area and DataGrid for SharePoint will automatically group your data. Grouping SharePoint List and SQL Server data has never been easier. You can even group multiple levels by dragging additional columns.
Scrolling
It is common to have hundreds, even thousands of rows in a data set; especially when accessing SQL Server data. DataGrid for SharePoint allows you to scroll smoothly and confidently through any amount of data without waiting for a page refresh!
Master-Detail Relationships
Navigating related database tables and lists is simple to implement and easy to set up with DataGrid for SharePoint. Use the on-board designer to select tables and related columns, then for any data row you can quickly drill into the details.