It is a best practice to aggregate the data as much as
possible. Doing so ensures the best performance in a dashboard and
avoids unexpected results, such as too many rows or gauges, or incorrect
summaries.
CAUTION:
The default maximum number of rows returned by any data source is
10,000.
If the source data
contains more than 10,000 rows, an error message about making an adjustment
appears. If possible, aggregate the data to reduce the number of rows
to return.
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If the source data has too many
rows, summarize the data.
Summarize data at the indicator data or in the source data. Do not rely on the indicator to perform the summary.
Tip
For an SQL query, you can
summarize data using aggregation functions such as AVG() and the distinct
keyword.
Another summarization strategy is to summarize the data into a summary table. The summary table is then used as the basis
for the SQL query or as the base table for the information map. In the following figure, the first illustration shows the
SAS BI Dashboard indicator data using a query that combines data from multiple tables. The second illustration shows the same
two tables being summarized
by an ETL program. The SAS BI Dashboard indicator data then uses this summarized table.
The first method is easier to set up and might result in more timely data, but the second method is more flexible and is probably
more scalable. You can use a similar strategy when creating information maps that will be used by the SAS BI Dashboard indicator
data.
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(Information Map data sources) If you choose fewer columns
in the query, it is possible to avoid the row limit or an inefficiently
large number of rows.
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(Information Map data sources) An information map data source easily aggregates data in such a flexible manner that a single
information map can drive several dashboard indicators.
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