This video is part of a series of three that I'd recommend to watch in combination. The other two are: th-cam.com/video/HRfR4dJoKDc/w-d-xo.html and th-cam.com/video/Ausqifk0ZiM/w-d-xo.html
Hi Torstein! Very informative lightboard video. I literally spent two hours this morning and took notes about every fine points. I wish I could someday work under you. I would learn so much. 😊
This guy adding that extra S on process like 2 minutes later is so funny to me lololol. Besides that this vid is so good thank you for breaking everything down and explaining it visually!! Appreciate it!!
Good explanation, thank you. However, talk can get started with "Big Data" - which means data lakes are intended to store, manage and serve large Big volume, variability, velocity. Data is ingested in native format. It need to be kept organized, controlled and managed - governance. Data needs to be served in native or processed further for other needs - reporting and visualization, recommendations, process automations and more. Some real-life use cases to start the discussions also will help.
Hi there! You can say that data pipelines run inside data lakes (through various services). A data lake is a cloud-native mechanism that supplies large volumes of quite diverse data to analytics, so that IT and business organizations can generate various business insights. It's basically a centralized place where an organization stores all their different data, allowing for many types of analytics at a larger scale (e.g social media data). While a data pipeline is a system that filters these large amounts of data in order to provide a more concise and insightful set of analytics to the organization. It is used for more efficient and detailed reporting and it serves a specific purpose. Hope this answers your question! 🙂
Depends on the cloud platform that you are using... for example with Microsoft Azure you can use Azure Data Factory for the orchestration and transformation
It is funny and ridiculous that these awesome videos by IBM get ridiculously low views on youtube, whilst so many crappier and much less clear videos with shittz slides get a ton more views… Extremely peculiar
So far the best explanation of the concept I have watched. Well done
Super informative video.. I am thankful to both IBM and Torsten for sharing this video.. IBM should be proud of having such a great people.
Thanks for watching, Mehran! & for the lovely feedback. 🙏 😊
Excellent work! and I must say I absolutely love this style of presentation with transparent glass and colored pens. I must definitely try that.
This video is part of a series of three that I'd recommend to watch in combination. The other two are: th-cam.com/video/HRfR4dJoKDc/w-d-xo.html and th-cam.com/video/Ausqifk0ZiM/w-d-xo.html
Thanks Torsten!
Hi Torstein!
Very informative lightboard video.
I literally spent two hours this morning and took notes about every fine points.
I wish I could someday work under you. I would learn so much. 😊
This guy adding that extra S on process like 2 minutes later is so funny to me lololol. Besides that this vid is so good thank you for breaking everything down and explaining it visually!! Appreciate it!!
Good explanation, thank you. However, talk can get started with "Big Data" - which means data lakes are intended to store, manage and serve large Big volume, variability, velocity. Data is ingested in native format. It need to be kept organized, controlled and managed - governance. Data needs to be served in native or processed further for other needs - reporting and visualization, recommendations, process automations and more. Some real-life use cases to start the discussions also will help.
굉장히 감사합니다.
Well done, guys. Applauding
Excellent information.
Great job on the video, thank you for sharing it with us.
What's the difference between data lakes and data pipeline. Is it same
Hi there!
You can say that data pipelines run inside data lakes (through various services).
A data lake is a cloud-native mechanism that supplies large volumes of quite diverse data to analytics, so that IT and business organizations can generate various business insights. It's basically a centralized place where an organization stores all their different data, allowing for many types of analytics at a larger scale (e.g social media data).
While a data pipeline is a system that filters these large amounts of data in order to provide a more concise and insightful set of analytics to the organization. It is used for more efficient and detailed reporting and it serves a specific purpose.
Hope this answers your question! 🙂
Does data lake contains unstructured data and what kind of mechanism is used to bring it in object storage?
Depends on the cloud platform that you are using... for example with Microsoft Azure you can use Azure Data Factory for the orchestration and transformation
Hey, thx for this - can you please make a hands one guide for IBM Cloud?
Hi, Eloy! You can access knowledge and resources about IBM Cloud in here 👉 ibm.co/2YZLygx
It would've made more sense had Data Lake been referred to as Data Ingestion Framework
Excellent post
Nice video. Just one callout though: One of the marker's squeaking sound is very annoying.
It is funny and ridiculous that these awesome videos by IBM get ridiculously low views on youtube, whilst so many crappier and much less clear videos with shittz slides get a ton more views… Extremely peculiar