Data Integration Solutions: Performance Tips

Informatica PowerCenter Pushdown Optimization a Hybrid ELT Approach

Informatica PowerCenter Pushdown Optimization an ELT Approach

Informatica Pushdown Optimization Option increases performance by providing the flexibility to push transformation processing to the most appropriate processing resource. Using Pushdown Optimization, data transformation logic can be pushed to source database or target database or through the PowerCenter server. This gives the option for the ETL architect to choose the best of the available resources for data processing.

Implementing Informatica PowerCenter Session Partitioning Algorithms

Implementing Different Informatica PowerCenter Session Partitioning Algorithms

Informatica PowerCenter Session Partitioning can be effectively used for parallel data processing and achieve faster data delivery. Parallel data processing performance is heavily depending on the additional hardware power available. In additional to that, it is important to choose the appropriate partitioning algorithm or partition type. In this article lets discuss the optimal session partition settings.

Informatica PowerCenter Partitioning for Parallel Processing and Faster Delivery

In addition to a better ETL design, it is obvious to have a session optimized with no bottlenecks to get the best session performance. After optimizing the session performance, we can further improve the performance by exploiting the under utilized hardware power. This refers to parallel processing and we can achieve this in Informatica PowerCenter using Partitioning Sessions.

Use Informatica Persistent Lookup Cache and Reduce Fact Table Load Time

Use Informatica Persistent Cache and Reduce Fact Table Load Time

In a matured data warehouse environment, it is very common to see fact tables with dozens of dimension tables linked to it. If we are using informatica to build this ETL process, we would expect to see dozens of lookup transformations as well; unless any other design techniques are used. Since lookup is the predominant transformation, turning this will help us gain some performance. Lets see how we can use persistent lookup cache for this performance improvement.

Design approach to Update Huge Tables Using Oracle MERGE

Design approach to Update Huge Tables in Informatica powercenter workflow

One of the issues we come across during the ETL design is "Update Large Tables". This is a very common ETL scenarion especially when you treat with large volume of data like loading an SCD Type 2 Dimension. We discussed about a design approach for this scenarion in one of our prior articles. Here in this updated article lets discuss a different approach to update Larger tables using Informatica Mapping.

Concurrent Workflows to Reduce Warehouse ETL Load Time

In large data integration projects, it is quite common to source data from multiple systems, sources, regions etc... As the number of data sources increases, the ETL load time also increases, because of the increasing data volume. One way to reduce the load time is by running different ETL process in parallel. Informatica PowerCenter's capability to run workflow concurrently can be used in such scenarios to reduce the ETL load time.

Update Without Update Strategy for Better Session Performance

You might have come across an ETL scenario, where you need to update a huge table with few records and occasional inserts. The straight forward approach of using LookUp transformation to identify the Inserts, Update and Update Strategy to do the Insert or Update may not be right for this particular scenario, mainly because of the LookUp transformation may not perform better and start degrading as the lookup table size increases.

Use CHECKSUM Number to Make the LookUp Transformation Simple

CHECKSUM Number in Informatica powercenter workflow

Lookup is one of the frequently used transformations in Informatica PowerCenter. This transformation is considered to be relatively simple, but at times this can become complex because of the amount of data to be cached, number of columns used in the lookup condition, checks on columns fetched from lookup table etc... In this article lets see how we can take care of couple of these issues using CHECKSUM number.

Popular Posts

Random Posts

Posts Being Viewed