Discussion, debate, software capabilities, usability, more here soon!
http://www.rittmanmead.com/2008/08/27/ragged-hierarchy-handling-in-obiee/
http://www.informit.com/articles/article.aspx?p=446454
A well-structured set of business-driven business intelligence requirements sets the stage for delivering successful business intelligence projects.
Google takes its first step into the OLAP world by partnering with the same company that helped Microsoft’s entry a decade earlier!
Based on a number of highly visible implementations and cases, the central driver of IT-enabled business performance in 2006 will be advanced analytics in an integrated information environment. We expect to see many more companies migrate to an enterprise data warehouse (EDW), which demonstrably provides uniquely correct and detailed answers to any question, any time, anywhere.
Ok so most of you using SQL 2005/2008 will have inbuilt reports for this kind of thing, but for those having to work with SQL 2000 database (may also work on other RDBMS’s) this script is handy to list all tables in any given database, and show the row count, space allocaitn, space reserved, used and indexes. Very handy when seeing what tables are the culprits behind very bloated databases!
CREATE PROC listDBTableSizes @dbName VARCHAR(100)
AS
DECLARE @tableName VARCHAR (1000)
DECLARE @cmd VARCHAR (1000)
DECLARE @sql VARCHAR (1000)
DECLARE @sql1 VARCHAR (1000)
CREATE …
To estimate the size of the data warehouse, all tiers of data need to be factored in, including any landed and staged data, presentation data, pre-aggregated tables or cubes (depending on your chosen architecture) as well as any metadata stored in the data warehouse.
Estimate the Size of the Base-Level Data Warehouse
The base-level data warehouse is composed mainly of fact tables and their associated dimension tables.
Using the Logical Data Warehousing Model estimate the size of the fact and dimension data by estimating the average field length and average number of occurrences …
In previous columns, I’ve talked about how you can improve the likelihood of achieving your desired results in building a data management center of excellence and in managing enterprise information. This month, I’d like to narrow the focus to one particular aspect of the enterprise information management spectrum: data warehouse (DW) design.
Contrary to popular sentiment, data warehousing is not a moribund technology; it’s alive and kicking. Indeed, most companies deploy data warehousing technology to some extent, and many have an enterprise-wide DW.
However, as with any technology, a DW can quickly become a quagmire …