Data Analysis and Databases – Telegram
Data Analysis and Databases
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282 files
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Learn how to analyze data effectively and manage databases with ease.

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17 - NumPy Fundamentals.zip
156.8 MB
17 - NumPy Fundamentals
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18 - NumPy DataTypes.zip
121.2 MB
18 - NumPy DataTypes
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19 - Working with Arrays.zip
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19 - Working with Arrays
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20 - Generating Data with NumPy.zip
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20 - Generating Data with NumPy
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21 - Statistics with NumPy.zip
243.8 MB
21 - Statistics with NumPy
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22 - NumPy - Preprocessing - Part 01.zip
387.9 MB
22 - NumPy - Preprocessing - Part 01
22 - NumPy - Preprocessing - Part 02.zip
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22 - NumPy - Preprocessing - Part 02
22 - NumPy - Preprocessing - Part 03.zip
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22 - NumPy - Preprocessing - Part 03
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23 - A Loan Data Example with NumPy - Part 01.zip
375.4 MB
23 - A Loan Data Example with NumPy - Part 01
23 - A Loan Data Example with NumPy - Part 02.zip
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23 - A Loan Data Example with NumPy - Part 02
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24 - The Absenteeism Exercise - Introduction.zip
25.1 MB
24 - The Absenteeism Exercise - Introduction
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25 - Solution to the Absenteeism Exercise - Part 01.zip
290 MB
25 - Solution to the Absenteeism Exercise - Part 01
25 - Solution to the Absenteeism Exercise - Part 02.zip
341.8 MB
25 - Solution to the Absenteeism Exercise - Part 02
25 - Solution to the Absenteeism Exercise - Part 03.zip
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25 - Solution to the Absenteeism Exercise - Part 03
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26 - Data Visualization - Part 01.zip
368.1 MB
26 - Data Visualization - Part 01
26 - Data Visualization - Part 02.zip
374.7 MB
26 - Data Visualization - Part 02
26 - Data Visualization - Part 03.zip
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26 - Data Visualization - Part 03
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27 - Conclusion.zip
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27 - Conclusion
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🔰 Data Analysis With Python
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📖 Visualizing a SQL query
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📖 7 must-know strategies to scale your database.

1 - Indexing:
Check the query patterns of your application and create the right indexes.

2 - Materialized Views:
Pre-compute complex query results and store them for faster access.

3 - Denormalization:
Reduce complex joins to improve query performance.

4 - Vertical Scaling
Boost your database server by adding more CPU, RAM, or storage.

5 - Caching

Store frequently accessed data in a faster storage layer to reduce database load.

6 - Replication
Create replicas of your primary database on different servers for scaling the reads.

7 - Sharding
Split your database tables into smaller pieces and spread them across servers. Used for scaling the writes as well as the reads.
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