Building Data Warehouse with CloverETL: Slowly Changing Dimension Type 2


In the last part of our data warehouse (DWH) tutorial, I showed you how to load a dimension table that stores historical data according to the Slowly Changing Dimension Type 1 (SCD1). In today’s post, I will focus on a Slowly Changing Dimension Type 2 (SCD2) dimension table. I think that SCD2 is the most challenging sub-task of ETL part of DWH design and each ETL architect should be able to deal with it.[Continue reading]

CloverETL as a High-throughput XML Processor

Mapping definition

XML is a markup language that has been around for some years now. Originally, it comes from the world of documents - used in web hypertext, word processors and other representations. Today, it is very popular in many areas, including the world of data exchange. The reasons are simple - the format is straightforward, well defined, and easily transferable accross platforms. XML can be easily read and modified by users in contrast to proprietary and binary formats. It also represents structured hierarchical data, which can be very difficult to express in plain CSV format. XML is self-descriptive, which heavily increases the user's ability to understand data and eliminates the need of data format description and parsing instructions.[Continue reading]

Data Profiling with CloverETL


Before you start to develop any data transformation you should explore your data (make data profiling). There are a lot of tools on the market that can help you. But why to install and learn another software when you can use the tool you are familiar with? CloverETL is mainly data transformation tool but it can be easily used for data profiling as well (as I will show you in this blog post).[Continue reading]

Parallel Data Processing Comparison – CloverETL vs. Talend vs. Pentaho (Part 3)


As I have promised I bring you a complex comparison of ETL tools: CloverETL, Talend and Pentaho.
Short summary of my previous posts: For testing I used two transformations based on TPCH test and the input data generated by dbgen utility. The transformations were run on my laptop with Windows Vista Home Premium. For detail information see part 1 and part 2.[Continue reading]

ParallelReader Component: Performance Boost in Data Processing

In October release 2.8.1 of Clover we introduced a new component which definitely should attract your attention – the Parallel Reader. The name itself already suggests the goal of the component – improve reading speed by going parallel. The component is very similar to Universal Data Reader in function – it reads delimited flat files like CSV, tab delimited, etc. - much hasn't changed here. But the real difference comes from under the hood.[Continue reading]