@aleksgerashchenko: #fyp#viral#trends#tiktok#foryou#slow#tiktokviral

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Tuesday 22 October 2024 14:13:13 GMT

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Антонина Булавина :

Молодец супер 😊

2024-10-31 06:19:41

1

Irina Orobets :

Саша, ти чудова людина,щастя тобі безмежного!!!!!🌸🌺🌹🔥😘

2024-11-12 08:25:15

0

Natali :

Не перестаю захоплюватися цим харизматичним і крутим чоловіком.🥰🥰🥰 Супер , мега круто..👍👍👍

2024-10-23 02:59:11

0

Света Грабар :

КРАСУНЧИК 🇺🇦

2024-10-23 06:47:07

0

Jacqueline Alves :

🫶🏻👏🏻👏🏻👏🏻👏🏻

2024-10-22 16:14:24

0

Taira :

умничок,супер!

2024-10-22 14:33:37

0

Вадим кваснюк :

❤❤❤

2024-12-18 07:13:07

0

Vasif Isgenderov :

🥰🥰🥰

2024-12-08 05:09:01

0

PRAGARO SKALIKAS :

🥰🥰🥰

2024-10-24 17:19:09

0

Márcia Aguiar s.souza :

🥰🥰🥰

2024-10-23 19:02:23

0

Queen🖤 :

🥰😍😘

2024-10-23 13:10:46

0

Валентина :

🥰

2024-10-23 07:07:50

0

Оля Шалай :

✌️👍😉

2024-10-22 18:13:28

0

💫Оля💫 :

👍👍👍

2024-10-22 16:48:19

0

Оксана :

🥰🥰🥰

2024-10-22 14:51:08

0

Volodymyr Tsepin :

😂😂😂бухарик

2024-10-25 08:27:11

0

💚🍀 Angel Flowers Silva 🍀💚 :

Passando pra retribuir o carinho nos meus vídeos e te desejar muito sucesso 🙏

2024-10-23 04:29:48

0

Robby :

🚂😎👍💯🥰

2024-10-23 00:40:50

0

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Essential Data Terms to Know in 2024: 1. Data Mining: The process of discovering hidden patterns, correlations, and insights in large datasets using methods like statistics, machine learning, and database systems. 2. Data Analytics: The science of examining raw data to draw conclusions, uncover trends, and support decision-making. It involves techniques such as data mining, predictive analytics, and statistical analysis. 3. Data Visualization: The practice of translating complex data into visual representations like charts, graphs, and maps, making it easier to understand and communicate insights. 4. Data Contract: A formal agreement between a service provider and a client that defines the structure, format, and constraints of the data being exchanged, ensuring compatibility and reliability. 5. Data Modeling: The process of creating a conceptual representation of data structures, defining entities, attributes, and relationships to organize and manage data effectively. 6. Data Integration: The practice of combining data from disparate sources into a unified view, enabling a comprehensive analysis of information across an organization. 7. Data Cleaning: The process of identifying and correcting inaccurate, incomplete, or irrelevant data to improve data quality and ensure reliable analysis. 8. Data Warehouse: A centralized repository that stores structured data from various sources, optimized for querying, reporting, and data analysis. 9. Data Mart: A subset of a data warehouse focused on a specific business function or department, designed for faster query performance and ease of use. 10. Data Lake: A storage architecture that holds vast amounts of raw, unstructured, and semi-structured data in its native format until needed for analysis. 11. Delta Lake: An open-source storage layer that brings reliability, scalability, and performance improvements to data lakes, enabling ACID transactions and data versioning. 12. Data Pipeline: A series of processes that move and transform data from source systems to target destinations, ensuring data quality, consistency, and availability. 13. Data Mesh: A decentralized approach to data architecture that treats data as a product, with domain-specific teams responsible for data ownership, quality, and governance. 14. Data Lake House: A modern data architecture that combines the flexibility of data lakes with the structure and performance of data warehouses, enabling diverse workloads and use cases. 15. Data Swamp: An unmanaged, chaotic data environment where data is stored without proper organization, governance, or quality control, making it difficult to derive value. 16. Data Fabric: An architecture that weaves together data from multiple sources, creating a unified, integrated view of an organization's data assets for seamless access and analysis. #data #dataengineering #softwareengineering

Essential Data Terms to Know in 2024: 1. Data Mining: The process of discovering hidden patterns, correlations, and insights in large datasets using methods like statistics, machine learning, and database systems. 2. Data Analytics: The science of examining raw data to draw conclusions, uncover trends, and support decision-making. It involves techniques such as data mining, predictive analytics, and statistical analysis. 3. Data Visualization: The practice of translating complex data into visual representations like charts, graphs, and maps, making it easier to understand and communicate insights. 4. Data Contract: A formal agreement between a service provider and a client that defines the structure, format, and constraints of the data being exchanged, ensuring compatibility and reliability. 5. Data Modeling: The process of creating a conceptual representation of data structures, defining entities, attributes, and relationships to organize and manage data effectively. 6. Data Integration: The practice of combining data from disparate sources into a unified view, enabling a comprehensive analysis of information across an organization. 7. Data Cleaning: The process of identifying and correcting inaccurate, incomplete, or irrelevant data to improve data quality and ensure reliable analysis. 8. Data Warehouse: A centralized repository that stores structured data from various sources, optimized for querying, reporting, and data analysis. 9. Data Mart: A subset of a data warehouse focused on a specific business function or department, designed for faster query performance and ease of use. 10. Data Lake: A storage architecture that holds vast amounts of raw, unstructured, and semi-structured data in its native format until needed for analysis. 11. Delta Lake: An open-source storage layer that brings reliability, scalability, and performance improvements to data lakes, enabling ACID transactions and data versioning. 12. Data Pipeline: A series of processes that move and transform data from source systems to target destinations, ensuring data quality, consistency, and availability. 13. Data Mesh: A decentralized approach to data architecture that treats data as a product, with domain-specific teams responsible for data ownership, quality, and governance. 14. Data Lake House: A modern data architecture that combines the flexibility of data lakes with the structure and performance of data warehouses, enabling diverse workloads and use cases. 15. Data Swamp: An unmanaged, chaotic data environment where data is stored without proper organization, governance, or quality control, making it difficult to derive value. 16. Data Fabric: An architecture that weaves together data from multiple sources, creating a unified, integrated view of an organization's data assets for seamless access and analysis. #data #dataengineering #softwareengineering

Ikan Sepat Ikan Teri Adakah Pap Mu Hari Ini😋 #notification #notifwhatsapp #soundviral #notifikasi #notif #febringtone

Ikan Sepat Ikan Teri Adakah Pap Mu Hari Ini😋 #notification #notifwhatsapp #soundviral #notifikasi #notif #febringtone

#duet with @XRP_DigiGold Jesus is coming! The holyspirit is moving over this nation! #Jesus #iraniantiktok #Biblical #Endtimes

#duet with @XRP_DigiGold Jesus is coming! The holyspirit is moving over this nation! #Jesus #iraniantiktok #Biblical #Endtimes

this is my song

this is my song

I live for golden hour 🌞 #mauihi #mauihawaii #mauihikes #hana #hanamaui #hanahawaii #hawaii #pacificocean #emptybeach #loveformaui #smileoften #beachgirl #lovemaui #iloveyou

I live for golden hour 🌞 #mauihi #mauihawaii #mauihikes #hana #hanamaui #hanahawaii #hawaii #pacificocean #emptybeach #loveformaui #smileoften #beachgirl #lovemaui #iloveyou

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