What is a Data Lake?

A data lake is a centralized repository that allows you to store a vast amount of raw data in its native format until it is needed. Data-driven businesses often use this storage architecture to get more business value from their data assets.

Check out this quick overview video with Adam Kocoloski as he goes through a data lake architecture and explains how data lakes can empower you to collaborate and analyze data in different ways that will help you make make smarter and faster business decisions.

#DataLake #CloudStorage #IBMCloud

[MayankDhuria]

I was way too distracted by the way he was writing in reverse. I was switching between being in awe as how well he was writing in reverse, and his explanation. Thus, I have to watch it again after accepting the fact that he is a genius, and then finally get to understand everything. Great explanation.

[karrcatmusic]

Amazing that you can write mirroring letters ....

[carthur]

Very clear and helpful. He writes like Ira Joe Fisher

[johnnytorres]

Why is it that every data lake explanation is full of theory without any concrete examples? Aren't all of us here because we're SQL or Cube programmers and want to know whats so great about Data Lakes? All I see is the same thing I do with sql databases: import the data, prep and transform it and then query it directly or create dashboard applications.

[datasleek]

Interesting but Data Lake is not only used by ML. It usually used to store unstructured raw data. Some governance can be applied, however, you don’t build Dashboard out of the data lake. You first need to model that data into a Data Warehouse using dimensional modeling (allowing you to extract different dimension of your data). This multi dimension represented by few tables will allow you to slice the data in multiple ways, making reporting, thus dashboards easy to build.
This is why Airbyte/Fivetran + Snowflake + DBT are the most popular data stack on the market right now.

[sreenivasamadenahall]

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 discussion.

If the viewer already knows bits of data world (databases, datawarehouse, data lake etc), this helps to consolidate that understanding.

[BlackLibertyGT]

Need to explain this to Snr Management, this video is very helpful in breaking it down into something I can explain to others.

[Ali-dsiy]

Man this is an awesome idea to stand behind the mirror and write it..👍🏼

[enyart]

You almost had me with the mirrored letters, until I realized- your wedding ring is on your right hand in this video. Very nice camera trick.

[pogococo]

do you use data warehouse at the "store" phase?

[MasterofPlay]

ibm is still using the traditional rdbms right? what about hadoop?

[surfhr]

data is really the new oil! nice explanation

[justincooke]

So does a Data Lake fall under Document Store due to it ingesting all types of Meta-Data such as Audio /Media, and text ?

[ashtarathena]

Mirroring letters was a bit spooky/distracting at first.
But great and simple content. Thanks.

[BourbonDrinker]

Great video. I posted this to my LinkedIn.

[centurion]

What does “infuse” mean in this context ? I could not find an answer searching on the Internet.

[jeroboam]

I still have no idea what concretely is a data lake!

[adityaprasad]

Thanks, but I don't understand how this differs from data warehouses and ETL.

[bavuvan]

Thank you! can you make video compare with data lake and data warehouse?

[Thee.Mighty]

Left-handed.... It explains everything