I am an Assistant Manager at a large comms service provider.
I would appreciate more information on Data Strategy solutions. Which Data Strategy solution have you used? What are the pros and cons of Data Strategy solutions?
Thank you for your help.
Consulting Practice Partner - Data, Analytics & AI at FH
Oct 10, 2021
Hi @Evgeny Belenky - great question.
Here is the best answer crafted by Talend
Purpose of Data
Not Yet Determined
Currently In Use
Highly accessible and quick to update
More complicated and costly to make change
Please read more here https://www.talend.com/resourc...
Many of the comparisons of data lake and data warehouse that you see (such as the one below from Talend) are based on an out-of-date or dumbed-down idea of the data warehouse.
The more advanced data warehouse engines:
- support a wide range of data types and formats
- can access external data (e.g., in object storage) that has never been ingested
- support data scientists as well as business users (e.g., with an ability to run Python, R, SAS routines and data science libraries on data in place in parallel in the data warehouse)
- support operational query on live, rapidly changing data
While also providing capabilities and services never provided on data lakes or their cloud-based equivalents. Data warehouses, properly operated and housing data that is properly curated, are much more efficient, cost-effective and performant for data that is intensively shared and widely used.
Data lakes are good repositories for data that is more lightly or locally used and does not merit the level of curation usually desired in a data warehouse.
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