Top 25 File Types used in Data Engineering

In Data Engineering, these are the top 25 file types used to store and transfer data.:

1. CSV (Comma-Separated Values) - CSV files store tabular data in plain text format. Each row represents a record, and each column represents a field.
2. XML (Extensible Markup Language) - XML files store structured data in a hierarchical format using tags.
3. JSON (JavaScript Object Notation) - JSON files store structured data in a text format using key-value pairs.
4. Excel - Excel files store tabular data in a proprietary binary format used by Microsoft Excel.
5. Database-specific files - Some databases, such as MySQL and Oracle, have their own file types for exporting and importing data.
6. Fixed-width files - Fixed-width files store data in a text format, where each column has a fixed width.
7. Parquet - Parquet is a columnar storage format that is optimized for use with big data processing frameworks such as Apache Spark and Hadoop.
8. Avro - Avro is a binary data format used to serialize data in a compact and efficient way.
9. ORC (Optimized Row Columnar) - ORC is a columnar storage format that is optimized for use with Apache Hive.
10. Text files - Text files are simple files that store data as plain text. They can be used to store unstructured data or semi-structured data in a human-readable format.
11. Binary files - Binary files are files that store data in binary format. They are used for storing complex data structures or binary data such as images, audio, and video.
12. RDF (Resource Description Framework) - RDF is a standard for representing metadata about resources on the web. It uses triples to describe the relationships between resources.
13. HL7 (Health Level 7) - HL7 is a standard for exchanging healthcare information between different systems. It uses message formats to exchange information about patients, treatments, and other healthcare-related data.
14. EDI (Electronic Data Interchange) - EDI is a standard for exchanging business documents between different systems. It uses a standardized format to exchange data such as purchase orders, invoices, and shipping notices.
15. YAML (YAML Ain't Markup Language) - YAML is a human-readable data serialization format that is often used for configuration files.
16. SAS (Statistical Analysis System) - SAS is a software suite used for data management and statistical analysis. It uses its own file format for storing datasets, which can be used for ETL processes.
17. ZIP (ZIP archive) - ZIP files are used to compress and archive one or more files or directories. They can be used to package and transfer data for ETL processes.
18. XLS (Microsoft Excel) - XLS files are used to store spreadsheets in a binary format used by older versions of Microsoft Excel. They can be used for ETL processes where the source data is in an XLS format.
19. SQL (Structured Query Language) - SQL files contain SQL statements used to interact with a relational database. They can be used to extract, transform, and load data from a database.
20. TXT (Plain Text) - TXT files contain unformatted plain text and can be used to store data in a simple, human-readable format.
21. PDF (Portable Document Format) - PDF files are used for storing and sharing documents in a fixed layout format. They can be used for ETL processes where data is extracted from PDF files.
22. YAML (YAML Ain't Markup Language) - YAML is a human-readable data serialization format that is often used for configuration files.
23. HDF5 (Hierarchical Data Format) - HDF5 is a file format used for storing and managing large datasets. It supports efficient storage and retrieval of multidimensional arrays and structured data.
24. ARFF (Attribute-Relation File Format) - ARFF is a file format used for storing data sets for use with machine learning algorithms. It includes metadata about the data and is supported by several machine learning tools.
25. DICOM (Digital Imaging and Communications in Medicine) - DICOM is a standard used for storing and exchanging medical images and associated information.