Informatica Tutorial

 Informatica is a widely used ETL tool for extracting the source data and loading it into the target after applying the required transformation. In the following section, we will try to explain the usage of Informatica in the Data Warehouse environment with an example. Here we are not going into the details of data warehouse design and this tutorial simply provides the overview about how INFORMATICA can be used as an ETL tool. Note: The exchanges/companies that are explained here is for illustrative purpose only. Bombay Stock Exchange (BSE) and National Stock Exchange (NSE) are two major stock exchanges in India...

Informatica Upgrade Process:

Informatica Upgrade Process: Stages across upgrade can be categorized as below: Upgrading the domain and server file: run the Informatica server installer and select the upgrade option. The domain upgrade wizard installs the server files and configures the domain. If the domain has multiple nodes, you must upgrade on all the nodes. The following table describes the actions that the installer performs when you upgrade Informatica: Tasks Description 1. Installs Informatica. Installs Informatica...

Design Tip #155 Going Agile? Start with the Bus Matrix

Many organizations are embracing agile development techniques for their DW/BI implementations. While we strongly concur with agile’s focus on business collaboration to deliver value via incremental initiatives, we’ve also witnessed agile’s “dark side.” Some teams get myopically focused on a narrowly-defined set of business requirements. They extract a limited amount of source data to develop a point solution in a vacuum. The resultant standalone solution can’t be leveraged by other groups and/or integrated with other analytics. The agile deliverable may have been built quickly, so it’s deemed a success. But when organizations...

White Paper: Evolving Role of the Enterprise Data Warehouse in the Era of Big Data Analytics

The enterprise data warehouse (EDW) community has entered a new realm of meeting new and growing business requirements in the era of big data. Common challenges include:     extreme integration     semi- and un-structured data sources     petabytes of behavioral and image data accessed through MapReduce/Hadoop     massively parallel relational database     structural considerations for the EDW to support predictive and other advanced analytics.  These pressing needs raise more than a few urgent questions, such as:     How do...