ETL Tools

ETL TOOLS

The times of increasing data-dependence forced a lot of companies to invest in complicated data warehousing systems. Their differentiation and incompatibility led to an uncontrolled growth of costs and time needed to coordinate all the processes. The ETL (Extract, transform, load) tools were created to simplify the data management with simultaneous reduction of absorbed effort. 

Depending on the needs of customers there are several types of tools. 
One of them perform and supervise only selected stages of the ETL process like data migration tools(EtL Tools , “small t”tools) , data transformation tools(eTl Tools , “capital T”tools).Another are complete (ETL Tools ) and have many functions that are intended for processing large amounts of data or more complicated ETL projects. 

Some of them like server engine tools execute many ETL steps at the same time from more than one developer , while other like client engine tools are simpler and execute ETL routines on the same machine as they are developed. 
There are two more types. First called code base tools is a family of programing tools which allow you to work with many operating systems and programing languages.The second one called GUI base tools remove the coding layer and allow you to work without any knowledge (in theory) about coding languages.

How do the ETL tools work ? |ETL Tools Selection in Data Warehousing

How do the ETL tools work?

The first task is data extraction from internal or external sources. After sending queries to the source system data may go indirectly to the database. However usually there is a need to monitor or gather more information and then go to Staging Area . Some tools extract only new or changed information automatically so we dont have to update it by our own. 
The second task is transformation which is a broad category: 
-transforming data into a stucture wich is required to continue the operation (extracted data has usually a sructure typicall to the source) 
-sorting data 
-connecting or separating 
-cleansing 
-checking quality 

The third task is loading into a data warehouse. 

As you can see the ETL Tools have many other capabilities (next to the main three: extraction , transformation and loading) like for instance sorting , filtering , data profiling , quality control, cleansing , monitoring , synchronization and consolidation.

ETL Process ,ETL Tools Selection in Data Warehousing

ETL PROCESS

The three-stage ETL process and the ETL tools implementing the concept might be a response for the needs described above.

The ‘ETL’ shortcut comes from 'Extract, transform, and load' – the words that describe the idea of the system. The ETL tools were created to improve and facilitate data warehousing.

The Etl process consists of the following steps:
1. Initiation
2. Build reference data
3. Extract from sources
4. Validate
5. Transform
6. Load into stages tables
7. Audit reports
8. Publish
9. Archive
10. Clean up

Sometimes those steps are supervised and performed indirectly but its very time-consuming and may be not so accurate.
The purpose of using ETL Tools is to save the time and make the whole process more reliable.

Extract, transform, load |ETL Tools Selection in Data Warehousing

Nowadays, most companies’ existence depends on data flow. When plenty of information is generally accessible and one can find almost everything he needs, managing became easier than ever before. The Internet simplifies cooperation – time needed to send and receive requested data gets shorter as more and more institutions computerize their resources. Also, the communication between separate corporation departments became easier – no one needs to send normal letters (or even the office boys) as the process is replaced by e-mails. Although the new ways of communication improved and facilitated managing, the ubiquitous computerization has its significant disadvantages.

The variety of data – as positive phenomenon as possible – got a little bit out of control. The unlimited growth of databases’ size caused mess that often slows down (or even disable) data finding process.

It’s all about effective information storing. Uncategorized data is assigned to different platforms and systems. As a consequence, finding wanted data brings a lot of troubles – user needs to know what data he administers, where it is located (and whether he has proper access), finally how to take them out.
Wrong was someone who thought that the hardest task was making decisions basing on data. No – finding data itself is often much more annoying. But users are not the only ones suffering for databases’ overgrowth. The IT departments – usually responsible for keeping the systems work – have to struggle with data in different formats and systems. ‘Keeping it alive’ is extremely time-consuming what delays the company’s work.
Slow (or sometimes omitted at all) transformation of data causes that it’s usually impossible to provide demanded information in demanded time. Formed divergence between data provided and data really existing in the moment of need harms the IT departments’ image.

To achieve better results, companies invest in external systems – computing power and resources. Not enough power causes lacks of synchronization of data. Transporting information between separate units lasts too long to work effectively. On the other side, computing power increasing – that might be an example solution – is expensive and lead to overgrowth of the operation costs.
Supposing that example company managed to prepare well-working database responsible for supporting designated operation. A lot of money and time got spent. Everything seems wonderful until it comes to another operation. Suddenly it appears that once created system doesn’t really fit the requirements of new operation and the best idea is to create a new system from the beginning. Yes, modifications might be made but there is no single developer common for all parts of the projects, so it demands cooperation of at least a few subjects – that hardly disables the idea.

Some List of ETL Tools
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Here is a list of the most popular comercial and freeware(open-sources) ETL Tools.
Comercial ETL Tools:

• IBM Infosphere DataStage
• Informatica PowerCenter
• Oracle Warehouse Builder (OWB)
• Oracle Data Integrator (ODI)
• SAS ETL Studio
• Business Objects Data Integrator(BODI)
• Microsoft SQL Server Integration Services(SSIS)
• Ab Initio
• Freeware, open source ETL tools:
• Pentaho Data Integration (Kettle)
• Talend Integrator Suite
• CloverETL
• Jasper ETL