i AM FROM COMMERCE STREAM. iF YOU HAVE MADE ME UNDERSTAND THIS.. WELL YOU ARE A GOOD SOURCE TO HELP EVEN THE WEAKEST PERSON IN TECHNOLOGY SKILLS.. THANKS A TON DEAR SIR..
@@DataAcademyIN vanakkam. I have made a humble beginning to learn data analytics with out spending a paisa. All my browsing will be from you tube. Hope my learnings turn into monetary rewards later on.
Very nice explanation. Thank you for providing such a good information. One small request if possible please can you make video on Delphix. Or can you provide any information regarding Delphix
Thanks for the easy laymen explanation. Much appreciated! How long does the DV layer hold the data it receives from the Upstream systems since (generally) there is no data storage on DV layer?
Hello Murtuza, Thank you for your comment. To answer your question - The DV may or may not have a data cache. Usually it is a very short lived cache that is subject to the application requirements. If at all the DV stores data for longer, then it is technically not a DV, but rather a Data Lake. But some people may differ from my opinion :) PS: Apologies for the late response.
Thank you Tony. Appreciate your open feedback. I was an amateur with video recording when I made this video. Let me know if it is a show stopper, and I will upload another video with amplified audio. Thank you!
Hello Manoj, Thanks for Subscribing. To your question about approach for Data Virtualization testing - - Data Virtualization involves "real-time" integration of data. Hence your test cases & test scripts must encompass multiple data-sources - The availability of real or mock-up data is crucial for testing. The mock-up data must be generated per data source, and also they must be well integrated. This means, that the test data generation is expected to be quite complex and tedious. - The Quality Assurance team must also understand the data availability and latency associated with each data source. In a Data Virtualization system, often the freshness of the data directly depends on that one data source with the highest latency (in other words, the weakest link in the chain) - Test cases must address various scenarios that may occur at runtime, such as - data availability (no data, partial data), data source timeout, performance variation with data volume - Also focus on the Caching capabilities of the Data Virtualization platform. Most Data Virtualization tools support some sort of internal data caching mechanism to improve performance. As part of QA, one must understand how the caching works, and what rules are applied for invalidating & refreshing the cache. - Data Security: In most Data Virtualization projects there is immense focus on Data Security. Since data originates from multiple systems, we should understand how the data source applies these rules, and what other rules are applied by the Data Virtualization system itself These are some pointers that I could come up with. But of course, all the remaining test cases with any data related projects are implicit, such as - business rules, data format consistency etc. I hope this helps !
DataAcademy.in Thanks for clarifying. I would like know is it required programming skill to learn denodo . I am having 7 years experience in database testing but no programming knowledge. Is it good move. Pls clarify.
Hello @@Sreenu1523 . You do not need any programming skills to learn Denodo, although basics would certainly help to build custom modules. Denodo serves as a low-code platform, so it can be easily learnt just like any other Drag-and-Drop interface. Since you have 7 years experience in Database Testing, I am sure you are pretty good with SQL and Database concepts. That is more than enough to get started with Denodo. Hope this helps !
That was a clear and matured explanation. Thanks a lot !!!!
Thank you Yuvaraj ! Please do subscribe
Great explanation. Very helpful
Thank you very much 🙏 please do Like, Share and Subscribe
Thank you! Fantastic resource!!
Thank you. Glad you found it useful. Please do Like, Share & Subscribe!
Big Thanks for simplifying the concept of Data Virtualization. God bless you.
Thank you Andishe. Please do subscribe, like and share. Cheers !
i AM FROM COMMERCE STREAM. iF YOU HAVE MADE ME UNDERSTAND THIS.. WELL YOU ARE A GOOD SOURCE TO HELP EVEN THE WEAKEST PERSON IN TECHNOLOGY SKILLS.. THANKS A TON DEAR SIR..
Vanakkum. Thank you. Your kind comments made me smile and made my day :)
@@DataAcademyIN vanakkam. I have made a humble beginning to learn data analytics with out spending a paisa. All my browsing will be from you tube. Hope my learnings turn into monetary rewards later on.
TH-cam has a ton of useful content. You just need to spend some time looking for the right one. Wish you all the very best
very clear, to the point and concise - explanation. excellent !!! keep up the good work. best wishes
Thank you Shaibal. Please do subscribe !
Well explained. Thanks for this.
Thanks for your feedback Mahendra. Please do subscribe and browse my channel for more such useful videos. Cheers !
Very well explained in 15 mins
Many thanks Karan ! Please do subscribe to my channel. Cheers !
Well explained. Thanks.
Thank you Kingshuk !
Great explanation !! Thank You.
Glad it was helpful!
great job thank you for your efforts
Thank You !
Very nice explanation. Thank you for providing such a good information.
One small request if possible please can you make video on Delphix. Or can you provide any information regarding Delphix
I am not an expert in Delphix. Thank you for your comments !
Thanks for a Nice explanation
Thanks Yogesh. Please do subscribe to get notified of new uploads. Cheers !
great explaination
Thank you Yashika. Please do like, share & Subscribe !
Thanks for the easy laymen explanation. Much appreciated!
How long does the DV layer hold the data it receives from the Upstream systems since (generally) there is no data storage on DV layer?
Hello Murtuza,
Thank you for your comment.
To answer your question - The DV may or may not have a data cache.
Usually it is a very short lived cache that is subject to the application requirements.
If at all the DV stores data for longer, then it is technically not a DV, but rather a Data Lake.
But some people may differ from my opinion :)
PS: Apologies for the late response.
So clear !
Glad you think so!
The explanation is clear, but the volume of the voice is too low.
Thank you Tony. Appreciate your open feedback. I was an amateur with video recording when I made this video. Let me know if it is a show stopper, and I will upload another video with amplified audio. Thank you!
Very well explaied
Thanks Shriram! Please do subscribe.
Hi, Thank you and the channel subscribed!
Also, could you explain what could be the approach to perform Data Virtualization testing
Hello Manoj,
Thanks for Subscribing. To your question about approach for Data Virtualization testing -
- Data Virtualization involves "real-time" integration of data. Hence your test cases & test scripts must encompass multiple data-sources
- The availability of real or mock-up data is crucial for testing. The mock-up data must be generated per data source, and also they must be well integrated.
This means, that the test data generation is expected to be quite complex and tedious.
- The Quality Assurance team must also understand the data availability and latency associated with each data source. In a Data Virtualization system, often the freshness of the data directly depends on that one data source with the highest latency (in other words, the weakest link in the chain)
- Test cases must address various scenarios that may occur at runtime, such as - data availability (no data, partial data), data source timeout, performance variation with data volume
- Also focus on the Caching capabilities of the Data Virtualization platform. Most Data Virtualization tools support some sort of internal data caching mechanism to improve performance. As part of QA, one must understand how the caching works, and what rules are applied for invalidating & refreshing the cache.
- Data Security: In most Data Virtualization projects there is immense focus on Data Security. Since data originates from multiple systems, we should understand how the data source applies these rules, and what other rules are applied by the Data Virtualization system itself
These are some pointers that I could come up with. But of course, all the remaining test cases with any data related projects are implicit, such as - business rules, data format consistency etc.
I hope this helps !
DataAcademy.in Thanks for clarifying. I would like know is it required programming skill to learn denodo .
I am having 7 years experience in database testing but no programming knowledge. Is it good move. Pls clarify.
Hello @@Sreenu1523 . You do not need any programming skills to learn Denodo, although basics would certainly help to build custom modules.
Denodo serves as a low-code platform, so it can be easily learnt just like any other Drag-and-Drop interface.
Since you have 7 years experience in Database Testing, I am sure you are pretty good with SQL and Database concepts.
That is more than enough to get started with Denodo.
Hope this helps !
Can i get the ppt