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If multiple users are using multiple replicas of the table, then it is likely that they will end up assigning the same values to AutoNumber fields in new rows that they add, causing replication conflicts when the replicas are merged. [2] This problem is addressed in two ways. First, it is possible to use Replication IDs for such AutoNumbers. [2]
It can edit and format text in cells, calculate formulas, search within the spreadsheet, sort rows and columns, freeze panes, filter the columns, add comments, and create charts. It cannot add columns or rows except at the edge of the document, rearrange columns or rows, delete rows or columns, or add spreadsheet tabs.
Data cleansing may also involve harmonization (or normalization) of data, which is the process of bringing together data of "varying file formats, naming conventions, and columns", [2] and transforming it into one cohesive data set; a simple example is the expansion of abbreviations ("st, rd, etc." to "street, road, etcetera").
In situations where the number of unique values of a column is far less than the number of rows in the table, column-oriented storage allow significant savings in space through data compression. Columnar storage also allows fast execution of range queries (e.g., show all records where a particular column is between X and Y, or less than X.)
A spreadsheet consists of a table of cells arranged into rows and columns and referred to by the X and Y locations. X locations, the columns, are normally represented by letters, "A," "B," "C," etc., while rows are normally represented by numbers, 1, 2, 3, etc. A single cell can be referred to by addressing its row and column, "C10".
In SQL, the unique keys have a UNIQUE constraint assigned to them in order to prevent duplicates (a duplicate entry is not valid in a unique column). Alternate keys may be used like the primary key when doing a single-table select or when filtering in a where clause, but are not typically used to join multiple tables.
In many Type 2 and Type 6 SCD implementations, the surrogate key from the dimension is put into the fact table in place of the natural key when the fact data is loaded into the data repository. [1] The surrogate key is selected for a given fact record based on its effective date and the Start_Date and End_Date from the dimension table.
List the columns that describe each dimension (region name, branch name, business unit name). Determine the lowest level (granularity) of summary in a fact table (e.g. sales dollars). An alternative approach is the four-step design process described in Kimball: [ 1 ] select the business process, declare the grain, identify the dimensions, and ...
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