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Dealing with heterogeneous data surely is a tedious task, but as the volume of data increases, it only gets more tiresome. This is where the ETL tools help in transforming this data into homogeneous data. Now, this transformed data is easy to analyze and derive the necessary information from it. In this blog on Talend ETL, I will be talking about how Talend works exceptionally as an ETL Tool to harness valuable insights from Big Data.
In this Talend ETL blog, I will be discussing the following topics:
You could also go through this elaborate video tutorial where our Talend for Big Data Expert explains Talend ETL and data processing with it in a detailed manner with crisp examples.
Talend ETL Tutorial | Talend Online Training | Edureka
What Is ETL Process?
ETL stands for Extract, Transform and Load. It refers to a trio of processes which are required to move the raw data from its source to a data warehouse or a database. Let me explain each of these processes in detail:
Extract
Extraction of data is the most important step of ETL which involves accessing the data from all the Storage Systems. The storage systems can be the RDBMS, Excel files, XML files, flat files, ISAM (Indexed Sequential Access Method), hierarchical databases (IMS), visual information etc. Being the most vital step, it needs to be designed in such a way that it doesn’t affect the source systems negatively. Extraction process also makes sure that every item’s parameters are distinctively identified irrespective of its source system.
Transform
Transformation is the next process in the pipeline. In this step, entire data is analyzed and various functions are applied on it to transform that into the required format. Generally, processes used for the transformation of the data are conversion, filtering, sorting, standardizing, clearing the duplicates, translating and verifying the consistency of various data sources.
Load
Loading is the final stage of the ETL process. In this step, the processed data, i.e. the extracted and transformed data, is then loaded to a target data repository which is usually the databases. While performing this step, it should be ensured that the load function is performed accurately, but by utilizing minimal resources. Also, while loading you have to maintain the referential integrity so that you don’t lose the consistency of the data. Once the data is loaded, you can pick up any chunk of data and compare it with other chunks easily.
Now that you know about the ETL process, you might be wondering how to perform all these? Well, the answer is simple using ETL Tools. In the next section of this Talend ETL blog, I will be talking about the various ETL tools available.
Various ETL Tools
But before I talk about ETL tools, let’s first understand what exactly is an ETL tool.
As I have already discussed, ETL are three separate processes which perform different functions. When all these processes are combined together into a single programming tool which can help in preparing the data and in the managing various databases. These tools have graphical interfaces using which results in speeding up the entire process of mapping tables and columns between the various source and target databases.
Some of the major benefits of the ETL Tools are:
- It is very easy to use as it eliminates the need for writing the procedures and code.
- Since the ETL Tools are GUI based they provide a visual flow of the system’s logic.
- The ETL tools have built-in error-handling functionality because of which they have operational resilience.
- When dealing with large and complex data, ETL tools provide a better data management by simplifying the tasks and assisting you with various functions.
- ETL tools provide an advanced set of cleansing functions as compared to the traditional systems.
- ETL tools have an enhanced business intelligence which directly impacts the strategic and operational decisions.
- Because of the use of the ETL tools, the expenses reduces by a lot and the businesses are able to generate higher revenue.
- Performance of the ETL tools is much better as the structure of its platform simplifies the construction of a high-quality data warehousing system.
There are various ETL tools available in the market, which are quite popularly used. Some of them are:
Among all these tools, in this Talend ETL blog, I will be talking about how Talend as an ETL Tool.
Talend ETL Tool
Talend open studio for data integration is one of the most powerful data integration ETL tool available in the market. TOS lets you to easily manage all the steps involved in the ETL process, beginning from the initial ETL design till the execution of ETL data load. This tool is developed on the Eclipse graphical development environment. Talend open studio provides you the graphical environment using which you can easily map the data between the source to the destination system. All you need to do is drag and drop the required components from the palette into the workspace, configure them and finally connect them together. It even provides you a metadata repository from where you can easily reuse and re-purpose your work. This definitely will help you increase your efficiency and productivity over time.
With this, you can conclude that Talend open studio for DI provides an improvised data integration along with strong connectivity, easy adaptability and a smooth flow of extraction and transformation process.
In the next section of this Talend ETL blog, let’s see how you can perform the ETL process in Talend.
Talend Open Studio: Running An ETL Job
To demonstrate the ETL process, I will be extracting data from an excel file, transform it by applying a filter to the data and then loading the new data into a database. Following is the format of my excel dataset:
From this data set, I will be filtering out the rows of data based on the customer type and store each of them in a different database table. To perform this follow the below steps:
STEP 1: Create a new job and from the palette, drag and drop the following components:
- tMysqlConnection
- tFileExcelInput
- tReplicate
- (tFilterRow)X4
- (tMysqlOutput)X4
STEP 2: Connect the components together as shown below:
STEP 3: Go to the component tab of tMysqlConnection and from the ‘Property Type’ select which type of connection you are using; Built-in or Repository. If you are using a built-in connection then you have to specify the following details:
- Host
- Port
- Database
- Username
- Password
But if you are using a Repository connection then it will pick up the details by default from the Repository.
STEP 4: Double-click on the tFileInputExcel and in its component tab specify the path of your source file, number of rows used for the header in the ‘Header’ field and number of the column from where Talend should start reading your data in the ‘First Column’ field. In the ‘Edit schema’ design the schema according to your dataset file.
STEP 5: In the component tab of tReplicate, click on ‘Sync columns’.
STEP 6: Go to the component tab of the first tFilterRow and check the schema. According to your condition, you can select the column(s) and specify the function, operator and the value on which data should be filtered.
STEP 7: Repeat the same for all the tFilterRow components.
STEP 8: Finally, in the tMysqlOutput’s component tab, check mark on ‘Use an existing connection’. Then specify the table name in ‘Table’ field and select the ‘Action on table’ and ‘Action on data’ as per requirement.
STEP 9: Repeat the same for all the tMysqlOutput components.
STEP 10: Once done, go to the ‘Run’ tab and execute the job.
This brings us to the end of this blog on Talend ETL. I would conclude this blog with a simple thought which you must follow:
“The future belongs to those who can control their data”
If you found this Talend ETL blog, relevant, check out the Talend for DI and Big Data Certification Training by Edureka, a trusted online learning company with a network of more than 250,000 satisfied learners spread across the globe. The Edureka Talend for DI and Big Data Certification Training course helps you to master Talend and Big Data Integration Platform and easily integrate all your data with your Data Warehouse and Applications, or synchronize data between systems.
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