I have an ETL process where supplemental/delta load is generated by source system vendor team in a json file and given to Dev team to load in table. And source system has agreed to provide the testing team with excel spreadsheet with changes/updates to data. Is there a way where Json file can be converted to Excel using some code/macro. There is no indicator or date field to track changes in the table loaded. SO inputs are excel sheet and json file. Since it is a regulated industry, using online converters is not recommended. Any ideas on how to do this, or better any other other approach for testing data would be helpful.
Is there a way where Json file can be converted to Excel using some code/macro
Maybe, but asking for such "libraries" is off topic here.
You've listed Hadoop in your tags, so you are welcome to drop JSON into HDFS, load a table schema over it in Hive (or Impala) using JSONSerde.
Then you can render the data into Excel using an ODBC connector for Hive (or Impala)
Related
I have around 30000 sheets of excel with standardized report.
The goal is to provide online dashboard to view the data.
My first thought as programmer is to create a database and find a way to import the data and then build front end on the top to create a customized dashboard.
Any easier way to do this?
If your reports are always going to be in excel, I don't think it would be a good approach to convert them to a database. It will only add an overhead of converting the data and creating the frontend for it, that would be an overengineering.
Instead what you can do is you can use data visualization tools like retool which already offer visualization components on top of any source data. The source can be anything be it an excel sheet or a database.
There are other alternatives as well like redash which also offers connections to CSV files.
However, if you still feel that creating a database like MySQL or any other database of your choice is a better approach to go. Then you should consider using Metabase or superset. These are excellent tools for data visualization and only require the database credentials to connect to the DB. These are feature-rich, accepted within the industry and you can create possibly all the visualizations as per your need.
Also, the best part is all the tools that I have mentioned here are totally open source or have a nice trial period.
FYI, For a better and more effective solution, I would recommend running a SQL Server on your machine and uploading the excel report to the SQL server and then connecting the SQL server instance to the Metabase, That would do everything that you need and you don't have to spend time to write any code to manage all these stuff. Below is a glimpse of a Metabase Visualisation Dashboard:
Is there any tool I can use to:
monitor a folder, when a xml file is added, it checks its name validate it(if exists in a list of names), validates it against a schema xsd, and extract data contained in xml and load it to an oracle database, if any error occurs in that process it rejects the file (write its name in a file of rejected files). I don't expect it to be able to fullfill all these features but at least help me with the monitoring and automating the process.
thanks in advance,
Yes, any ETL or data integration tool should be able to do that. I’ve implemented a project that had most of those features in the past using Pentaho Data Integration.
Is it possible to use the saiku-ui component with a different jolap provider than mondrian, or with a different server backend than the saiku-server component?
I have been looking but I have not found an architecture description of how these pieces fit together and what interfaces they use to communicate. Can anyone point me towards an understanding of what the saiku-ui wants to speak with and what the saiku-server is providing?
The reason for my interest is that I have a set of data spread across hundreds of csv files that I would like to query with a pivot and charting tool. It looks like the standard way to use this with saiku would be to have an ETL process to load in to an RDBMS. However, this would not be a simple process because the files and content and the way the files relate to each other vary, so the ETL would have to do a lot of inspection of the data sources to figure it out.
Given this it seems to me that I would have three options in how to use saiku:
1) write a complex ETL to load in to a rdbms, and then use a standard jdbc driver to provide the data to modrian. A side function of the ETL would be to analyze the inputs and write the mondrian schema file describing the cubes.
2) write a jdbc driver to access the data natively. This driver would parse sql and provide access to the underlying tables. Essentially this would be a custom r/o dbms written on top of the csv files. The jdbc connection would be used by mondrian to access the data. A side function of this custom dbms would be to produce the mondrian schema file.
3) write a tool that provides a jolap interface to the native data (accepts discovery and mdx queries). This would bypass mondrian entirely and interface with the ui.
I may be a bit naive here but I consider each of the three options to be feasible. Option #1 is my least preferred because of the likelihood of the data in the rdbms becoming out of sync with the cvs files. Option #3 is most preferred because the data are simple, so not much aggregating required and I suspect that mdx will be easier to parse than sql.
So, if i could produce my own jolap data source would it be possible to hook the saiku-ui tools up to it? Where would I look to find out the interface configuration details?
Many years ago, #ronaldbouman created xmondrian - the set of tools with the olap server, and web ui tools for xmla browsing and visualusation. But that project was not updating, and has no source code.
I just updated olap server and libraries to the latest versions.
You may get it here and build:.
https://github.com/Muritiku/xmondrian-build.
You may use web package as the example. The mondrian server works with the saiku-ui.
IMHO,
I would not be as confident as your are, because it took Julian Hyde more than a decade to build Mondrian (MDX->SQL) and Calcite (SQL), fulfilling your last two proposals.
You might simply consider using Calcite, or even better Dremio. Dremio has a JDBC interface, and can query directories of CSV files in SQL. I tested Saiku over Dremio successfully (with a schema based on two separate RDBMS). Just be careful to setup tables' schema accordingly in the Mondrian v4 schema.
Best regards,
Fabrice Etanchaud
Dremio
I use Integration Services 2012 in project deployment mode. I want to replace existing ODBC data source with OLE DB data source in existing package without breaking all the links that cascade down the package into the data destination.
I have tried deleting the ODBC & adding OLE DB data source. Then I lost all my output aliases after the first MERGE JOIN data flow. What can I do about it?
First fix all of the metadata in your source components, by opening them for edit. Then edit each component in order in the data flow. This will often fix downstream components as you go, but if data types changed (i.e. unicode to non-unicode) then you may have conversions to do.
I am new to the reporting world. Wanted to know which is the right solution to about for generating a single report by querying for data from multiple databases. We are planning to use some reporting solution like Jasper Reports or BIRT. Generally the databases are going to be postgresql.
Please do feel free to let me know about any other better solutions as well.
Thanks.
With BIRT you can use as many data sources as you like; independently or together as joint data sets. A Joint Data Set is basically a join you create at the report level. The cool think here is that you can in effect create the join accross data bases, even instances.
All the expected sources are supported, even some not so expceted ones. Any JDBC DB, Web Servce, Flat File, POJOs (via a Scripted Data Source), XML, Native DB Driver (i.e. Oracle, SQL Server, etc...). You can even use on BIRT Report as a data source for a secondary BIRT report. That gets a bit beyond the scope of the question, but opens up a huge amount of options in terms of deployment and felxibility.
In JasperReports if you are generating the report on the server, and streaming it back to the client as PDF or HTML, then you can use any datasources you want, being it:
Multiple databases
Objects, i.e. Java Beans
Text files/XML
Web services
... etc