Pentaho Self Service – One tool for entire data pipeline

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In today’s world, one has to deal with a large amount of data. This large level of data integration is possible with the help of the self-service tool – Pentaho. It involves the gathering of data which is stored in so many sources enabling BI and DI to be together. It then presents users with an integrated interface known as a dashboard on which they can see graphs and reports. As data is increasing at a rapid pace when you know every object is emitting data and that data can be too relevant. It then needs transaction processing systems like ERP, CRM which would make the data integration easier.

How Pentaho can act as a single tool for entire data pipeline

Let’s look more into details. There is one organization who wants to use Pentaho self-service for data pipeline. It wants to deliver complex data integration solution to its customers. So, how would it be able to complete this process when you know that data is very big to be handled? It has to be involved in various tasks like extraction of data and then transforming the data by using some logic. Whatever the final product it got, it has to load into a reporting database. It can be anything SQL or NoSQL. In this process, you will be creating a data model while processing this solution. That organization will be able to deliver its customers with various transformation and ETL capabilities and the client will get the job done using various graphs. He doesn’t even have to bother about the code. I can say with Pentaho one can deliver a data pipeline which has a very rich library and is very scalable. It would be having a good data source and warehousing support. So, you can see how for entire data pipeline a single tool can be used.

Let’s dig into more details of what we actually mean data integration. You set up the database, created the data model and at last analytics has helped you to create a graph which is of business interest. The way you can achieve data integration is by converting the output of transformation step into a data service. In this way, your output service can be queried as if the data was stored in a SQL database. You can manipulate or query the data and this data can be published on the Pentaho server. Isn’t the data integration done in the most beautiful way?

Also, not only during transformation step but while maintaining and preparing warehouse, you can make use of Pentaho and make your data pipeline more efficient. When you want your data to be blended with the system then you have to make use of Pentaho. In this way, you can visualize fast moving data and even the flaws can be detected much before the stage, they are actually integrated. Let’s take an example of an e-commerce site which sells various products. If you are having a competitor and you want to compare prices to different products on the fly then, you should create a transformation. The output step should be converted into a data service and with the help of this service, you can query the database and then, results would be displayed on the analyzer.

Also, Pentaho service provides you with a testing tool. This tool generates several logs and reports. It should be used to refine the data for optimizations. You can have a data service which publishes the result of some table on a server. You can have optimizations enabled on this service such as the test type. It will enable that data service runs more quickly.

So, you have seen that how Pentaho as a single tool can be used all over the data pipeline.Let’s see how to create a Pentaho data service.

• First, you have to open the transformation in the PDI client. You have to then review the transformation so as to understand which SQL commands are supported.
• You can then save the transformation to the Pentaho server.
• You can right click on the transformation step which you want to use as a data service. Then you have to select one option as Data Services. In that, you have to click on a new option.
• You have to then enter a name for the data service which you are transforming. After that, a virtual table which will be created which will be having the same name which you have provided to the data service.
• Remember to enter a unique name for the data service and it should not be used anywhere locally or on remote on the Pentaho server.
• Now, you have to verify whether you have selected the right step which you want to transform. If you feel that this is not the right step. You can go ahead and change it and make another step as a data service.
• Now, if you are working with streaming data, you have to select Streaming for the data service you selected. So, it depends on the model you are working on.
• Now you can simply click on OK button. It will save the service and you will be able to exit the window. Also, you will be able to see a data service badge on the transformation step icon.

• You can then verify the data service by running the test. You have to click on execute SQL. You can then analyze the results obtained. You can re-run the test by clearing the system’s cache. Testing a Pentaho data service is very necessary because testing will only tell you where exactly the bottlenecks are. You can then eliminate them using optimization techniques.

Conclusion So, now you have studied about Pentaho BI Services which can be used as one tool for entire data pipeline. It can be used in data preparation, data generation and testing phase which makes a data pipeline complete. So, analyze the data well with Pentaho server and you will definitely get awesome customer response. All the best!!