Types of Data

• Structured Data (rows/columns CSV, Excel)

• Semi-Structured Data (JSON / XML)

• Unstructured Data (Video, Audio, Document, Email)

Structured Data

ID	Name	Join Date
101	Rachel Green	2020-05-01
201	Joey Tribianni	1998-07-05
301	Monica Geller	1999-12-14
401	Cosmo Kramer	2001-06-05

Semi-Structured Data

JSON

[
   {
      "id":1,
      "name":"Rachel Green",
      "gender":"F",
      "series":"Friends"
   },
   {
      "id":"2",
      "name":"Sheldon Cooper",
      "gender":"M",
      "series":"BBT"
   }
]

XML

<?xml version="1.0" encoding="UTF-8"?>
<actors>
   <actor>
      <id>1</id>
      <name>Rachel Green</name>
      <gender>F</gender>
      <series>Friends</series>
   </actor>

   <actor>
      <id>2</id>
      <name>Sheldon Cooper</name>
      <gender>M</gender>
      <series>BBT</series>
   </actor>
</actors>

Unstructured Data

1. Text Logs: Server logs, application logs.

2. Social Media Posts: Tweets, Facebook comments.

3. Emails: Customer support interactions.

4. Audio/Video: Customer call recordings and marketing videos.

5. Customer Reviews: Free-form text reviews.

6. Images: Product images user profile pictures.

7. Documents: PDFs, Word files.

8. Sensor Data: IoT data streams.

These can be ingested into modern data warehouses for analytics, often after some preprocessing. For instance, text can be analyzed with NLP before storing, or images can be processed into feature vectors.