In big data arena a lot of unstructured information is generated which may be essential at present or in future for business decision making. In few years companies may generate too much data for which real time analysis would be a norm rather than an option. Since both structured and unstructured data is being generated, what are the ways to stitch it together and how real time analysis be done with data at hand.
Hi Owais,
Mappings have already beed studied to transfer data from relationnal databases to graph store. For example : R2RML is a good start. https://www.w3.org/TR/r2rml/
I never saw an reverse solution (RDF to RDB).
Sadly, I'm not aware of any relevant real time analysis solution.
Dear Mr. Gilles,
Thank you for the input. I will go through the link to understand more about R2RML.
Kind Regards
Owais Qureshi
You can link data from many sources through Microsoft Power BI or Tableau Desktop. The former has longer trial period, while the latter has only 14 days of trial (Academics can take free licence).
Through either you can add data from SQL, Excel, Text, Web, ... in a very easy and convenient way. Then you can analyze, and visualize them in the same software.
See the links below:
https://powerbi.microsoft.com/en-us/
https://www.tableau.com/products/trial
I highly recommend Power BI
Apache Kafka is used in research and industry for data ingestion and data preparation. With its connectors, you can ingest, transform and export data to several formats and tools. Its very fast, horizontal scaling, no back pressing, capability for exactly-once-messaging, might be used with e.g. Apache Spark for analytics, and has a very simple API. Take a look.
Henning.
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