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How to Work With Tuple in Python

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Tuple in python is one of the streaming datasets. The other streaming datasets are List and Dictionary. Operations that you can perform on it are shown here for your reference. Writing tuple is easy. It has values of comma separated, and enclosed with parenthesis '()'. The values in the tuple are immutable, which means you cannot replace with new values. #1. How to create a tuple Code: my_tuple=(1,2,3,4,5) print(my_tuple) Output: (1, 2, 3, 4, 5) ** Process exited - Return Code: 0 ** Press Enter to exit terminal #2. How to read tuple values Code: print(my_tuple[0]) Output: 1 ** Process exited - Return Code: 0 ** Press Enter to exit terminal #3. How to add two tuples Code: a=(1,6,7,8) c=(3,4,5,6,7,8) d=print(a+c) Output: (1, 6, 7, 8, 3, 4, 5, 6, 7, 8) ** Process exited - Return Code: 0 ** Press Enter to exit terminal #4.  How to count tuple values Here the count is not counting values; count the repetition of a given value. Code: sample=(1, 6, 7, 8, 3, 4, 5, 6, 7, 8) print(sample

4 Essential Points on Modern Data Warehouse 2.0

The new data warehouse often called “Data Warehouse 2.0,” is the fast-growing trend of doing away with the old idea of huge, off-site, mega-warehouses stuffed with hardware and connected to the world through huge trunk lines and big satellite dishes.
modern data warehouse

How Modern Data warehouse You Can Implement

The replacement is very different from that highly controlled, centralized, and inefficient ideal towards a more cloud-based, decentralized preference of varied hardware and widespread connectivity.

In today’s world of instant, varied access by many different users and consumers, data is no longer nicely tucked away in big warehouses.

How Data Will Be Stored in Modern Data Warehouse

Instead, it is often stored in multiple locations (often with redundancy) and overlapping small storage spaces that are often nothing more than large closets in an office building. 

The trend is towards always-on, always-accessible, and very open storage that is fast and friendly for consumers yet complex and deep enough to appease the most intense data junkie.

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