SAP HANA Architecture

In this article we will discuss about the architecture overview of the In-Memory Computing Engine of SAP HANA. The SAP HANA database is developed in C++ and runs on SUSE Linux Enterpise Server. SAP HANA database consists of multiple servers and the most important component is the Index Server. SAP HANA database consists of Index Server, Name Server, Statistics Server, Preprocessor Server and XS Engine. Index Server contains the actual data and the engines for processing the data. It also coordinates and uses all the other...

SAP HANA - An Introduction for the beginners

SAP HANA: High-Performance Analytic Appliance (HANA)is an In-Memory Database from SAP to store data and analyze large volumes of non aggregated transactional data in Real-time with unprecedented performance ideal for decision support & predictive analysis. The In-Memory Computing Engine is a next generation innovation that uses cache-conscious data-structures and algorithms leveraging hardware innovation as well as SAP software technology innovations. It is ideal for Real-time OLTP and OLAP in one appliance i.e. E-2-E solution from Transactional to high performance Analytics. SAP HANA can also be used...

Building the Next Generation ETL data loading Framework

Do you wish for an ETL framework that is highly customizable, light-weight and suits perfectly with all of your data loading needs? We too! Let's build one together... What is an ETL framework? ETL Or "Extraction, Transformation and Loading" is the prevalent technological paradigm for data integration. While ETL in itself is not a tool, ETL processes can be implemented though varied tools and programming methods. This includes, but not limited to, tools like Informatica PowerCentre, DataStage, BusinessObjects Data Services (BODS), SQL Server Integration Services (SSIS), AbInitio etc. and programming methods like...

Incremental Loading for Dimension Table

In our previous article we have discussed the concept of incremental loading in general. In this article we will see how to perform incremental loading for dimension tables. Should we do incremental loading for dimensions? In a dimensional model, we may perform incremental loading for dimension tables also. One may argue that this wont be necessary as data volume in dimension tables are not as high as the data volumes in the fact tables, hence we can simply do a full load every time. I personally do not agree to this argument. This is because during the last few years I have seen tremendous growth in the...

Using Informatica Normalizer Transformation

Normalizer transformation is a native transformation in Informatica that can ease many complex data transformation requirements. Learn how to effectively use normalizer in this tutorial. What is a Noramalizer Transformation? In a snapshot, here is what a Normalizer is or does: Active Transformation Can output multiple rows for each input row Can transpose the data (transposing columns to rows A Normalizer is an Active transformation that returns multiple rows from a source row, it returns duplicate data...

Incremental Loading for Fact Tables

In the previous articles, we have discussed the general concepts of incremental data loading as well as how to perform incremental data loading for dimension tables. In this article we will discuss the methods and issues of loading data incrementally in Fact tables of a data warehouse. METHOD OF LOADING Generally speaking, incremental loading for Fact tables is relatively easier as, unlike dimension tables, here you do not need to perform any look-up on your target table to find out if the source record already exists in the target or not. All you need to do is to select incremental records from source (as shown below...

SAP BODS Transforms

This article deals with the various types of transformations available in SAP BODS. Transformations are in-built, optional objects used in dataflow to transform source data to desired output dataset objects available in Local Object Library under the Transforms tab. There are four categories of Transform available in SAP BODS namely Data Integrator, Data Quality, Platform and Text Data Processing. List of available transforms Data Integrator- Data_Transfer, Date_Generation, Effective_Date, Hierarchy_Flattening, History_Preserving,...

What is Active Lookup Transformation

Informatica 9x allows us to configure Lookup transformation to return multiple rows. So now we can retrieve multiple rows from a lookup table thus making Lookup transformation an Active transformation type. How to configure a Lookup as Active? To use this option, while creating the transformation, we must configure the Lookup transformation property "Lookup Policy on Multiple Match" to Use All Values. Once created we cannot change the mode between passive and active. When ever the Lookup policy on multiple match attribute...

CDC Implementation using Flatfile

This article shows how to use a flatfile to implement Change data Capture. Suppose we want to maintain the last extraction date in a flatfile, based on that value we want to capture the changed data of our business table. First we will discuss what we are going to do followed by how we are going to do. Suppose we have an employee table in the source system. We want to load the Delta or Changed employee data to our target data warehouse. We want to maintain the last extraction date in a flatfile instead of maintaining...

Top Informatica Interview Questions with Answers

Welcome to the finest collection of Informatica Interview Questions with standard answers that you can count on. Read and understand all the questions and their answers below and in the following pages to get a good grasp in Informatica. What are the differences between Connected and Unconnected Lookup? The differences are illustrated in the below table Connected LookupUnconnected Lookup Connected lookup participates in dataflow and receives input directly from the pipelineUnconnected lookup receives input...

WELCOME TO MICRO INFORMATICA!

Since our inception over 22 years ago, Micro Informatica has taken pride in delivering the highest quality and best value to our customers. This philosophy has helped us grow into an industry leader, distributing a wide range of computer hardware and peripherals throughout Latin American and Caribbean markets at heavily discounted prices.I would like to take this opportunity to communicate directly with you and all of our customers as Micro Informatica takes this significant step forward. Following the traumatic events at the beginning of this century in New York, which deeply touched all of us, economic conditions...

Terra Informatica

New features: [CSS] background-attachment: scroll | local | fixed; is back. [CSSS!] "string".compare("other string") – lexical string comparison. [TIS] "string".lexicalCompare("other string") – lexical string comparison. [CSS] image-transformation, additive cascade: combining lists from different rules. Allows to combine transformations from different rules. See: sdk/samples/image-transformations.css++/additive-transformations.htm [CSS] behavior:marquee is back. See: sdk/samples/effects/marquee.htm Sciter2 port of behavior_tabs.cpp...

BMJ Informatica

Informatica Systems, part of the BMJ Group, delivers performance management systems and innovative software solutions to primary care such as FrontDesk, Contract+, Audit+ and Health Checks. Since 1992, Informatica Systems has been providing decision support and benchmarking support tools for doctors and developing systems for primary care data extraction and analysis. The Welsh Assembly Government relies upon Informatica's technology for its Primary Care Data Quality Service. One of the few companies certified by BSi for our ISO27001 Information Security Management System, Informatica Systems has also...