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Need to blend and visualize fast moving data sets on the fly?
May be its time to look at creating Pentaho Data Service.
In recent years, many of the enterprise customers are inclined to build self-service analytics, where members in specific business users have on-demand access to query the data. This not only helps enhancing the IT productivity, but also empowers the business users to perform a quick analysis.
Many organizations which need to blend and visualize large data sets find it challenging to build the data warehouse. This is where building Pentaho Data Service can help analyze the data on the fly. For example, if you have transformation with output of large data-set of various departments of organization, you can create a data service and publish it to DI server. You can provide access to group of users from various departments of an organization for them to query their respective set of data by connecting to this data service. Pentaho’s Data Service feature turns transformation into a data source of virtual table that can be queried from Pentaho Report Designer, Interactive Reporting and also from tools like R Studio, Squirrel, DBVisualizer or by simple SQL statements. Pentaho also provides push down optimization feature which helps to optimize Pentaho Data Service. This feature helps Pentaho Data Service to push the filters directly to data source instead of DI server’s memory. This helps users to get fresh slice of respective department’s data quickly. Users can use Pentaho Interactive Reporting tool or tool such as R Studio to further analyze and visualize the results.
To create a data service select the transformation step whose output data you want to expose to data service. Once the data service is created you can share it with other users who can connect and query based on the access provided.
Pentaho Data Services supports a subset of SQL. For more details see the Pentaho Data Service SQL Support Reference and Other Development Considerations. Also, for a complete list of traditional data sources that Pentaho support, see Components Reference .
To learn to create and connect to a Pentaho Data Service you may like to read these Pentaho articles
- Develop and Optimize a Pentaho Data Service
- Connect to a Pentaho Data Service
- Pentaho Data Service SQL Support Reference and Other Development Considerations
In summary, If you require to blend large data sets and to further slice & dice the sub set of this large date set on the fly to analyze and visualize the results then it’s time to look at Pentaho for its Data Service capability.
– Sandeep Khuperkar, Director and CTO – Ashnik, India
Sandeep is the Director and CTO at Ashnik. He brings more than 21 years of Industry experience (most of it spans across Red Hat & IBM India), with 14+ years in open source and building open source and Linux business model. He is on Advisory Board of JJM College of Engineering (Electronics Dept.) And visiting lecturer with few of Engineering colleges and works towards enabling them on open source technologies. He is author, Enthusiast and community moderator at Opensource.com. He is also member of Open Source Initiative, Linux Foundation and Open Source Consortium Of India.