As a developer I was involved in collecting the requirements from business end user, according understood the business needs and involved in designing the universe for sales department ,As a first step we understand the structure of the universe and depending upon the fact tables n dimension tables created classes ,objects ,defined joins ,cardinalities ,created derived tables, custom Hierarchies .
To improve the performance of the reports at universe level: * Generate LOV for required objects.
* use aggregate tables in universe design.
* Use pre defined conditions and formulas.
* check context (if there resolve it)
* check loops (if there resolve it through alias table)
Involved in resolving the join path problems like loops in universe. Check the structure of universe, used @functions to create Predefined connections and prompts to filter the data at universe level. Test the universe and export it to repository. Deployed reports accordingly to run on daily/weekly/monthly basis using webintelligence for sales department
Used different functions like sort,filters ,break,sections to create webi reports for sales and finance department
implemented dense rank features in bo reports, Created complex webi and crystal reports using merged dimensions, Linking two reports at report level using hyperlink, Applied slice and dice and drill down options for multidimensional purpose: .
* Using crystal reports Created subreports and pass date parameters to sub reports and use them in the selection criteria * Used various functions to develop crystal reports
Worked on rolling dates and how to subtract one datetime field from another and displaydays hours,minutes and seconds.Here I used date function syntax: [DateDiff(intervaltype,StartDateTime,EndDateTime]
Environment: my environment their are 500 Business End Users and 4 report Developers and Two Universe Designer and one Administrator
Structure: I was involved in designing the universe from different multiple datamodels like starschema,snowflakes schema
Joins between tables:
Join is a bidirectional relationship between 2 tables, A join is a condition that links the data in seperate but related tables.
Fact table: : A fact table contains statistical information about transactions. For example, it may contain figures such as Sales Revenue or Profit.
In a universe, most but not all, measures are defined from fact tables
Involved in linking facttables:Example. custumer fact table is connected to loan fact table via customer_id, and each record in loan fact table is uniquely identified by a primary key on cod_acct_no. Similarly customer table can be connected to Savings fact table through customer id. OLAP - Online Analytical Processing, which deals with analysis of data. It has to deal with historical data too (for analysis purpose) Not updated frequently. If required bulk update is allowed.
OLTP - Online Transactional Processing, which deals with transactions. For e.g. withdrawals at ATM machines. It involves many transactions. The databases have to be updated more frequently after the successful completion of a transaction.
Checked the cardinalities between the tables, Detect cardinalities in joins options in the Database tab of the Options dialog box, Designer detects and retrieves the cardinalities of the joins Cardinality expresses the minimum and maximum number of instances of an entity B that can be associated with an instance of an entity A. The minimum and the maximum number of instances can be equal to 0, 1, or N.
Because a join represents a bi-directional relationship, it must always have two cardinalities.
There are two main methods for detecting or editing cardinalities: * the Detect Cardinalities command
* the Edit Join dialog box
If you do not use this option, you can...