Data Analysis Online Course | Data Analytics Training in Hyderabad

 

Overview of Datasource

Data analytics is the process of examining, cleaning, transforming, and interpreting data to discover valuable insights, make informed decisions, and support business goals. - Data Analytics Online Training

The source of data for analytics can come from various places and can be categorized into several types:

1. Structured Data: Structured data is highly organized and typically stored in relational databases. It is easy to query and analyze. Common sources of structured data include:

 - Relational databases (e.g., MySQL, PostgreSQL, Oracle)

 - Spreadsheets (e.g., Microsoft Excel, Google Sheets)

 - Enterprise Resource Planning (ERP) systems

2. Unstructured Data : Unstructured data lacks a specific format and can be more challenging to analyze. Common sources of unstructured data include:

 - Text documents (e.g., Word documents, PDFs)

 - Social media posts

 - Emails

 - Multimedia content (e.g., images, videos)

 - Web content - Data Analytics Course in Hyderabad

3. Semi-Structured Data: Semi-structured data falls between structured and unstructured data. It has some organization but doesn't conform to a rigid structure. Examples of semi-structured data sources include:

 - JSON and XML files

 - Log files

 - NoSQL databases (e.g., MongoDB, Cassandra)

4. Streaming Data: Streaming data is generated continuously and in real-time. It's common in applications such as IoT (Internet of Things) and social media. Sources of streaming data include:

- Sensor data

- Social media feeds

- Clickstream data from websites - Data Analysis Online Training Course

5. Public Data Sources: Many organizations and governments provide open data for public use. This data can be valuable for various types of analytics, including:

- Government data (e.g., census data, weather data)

- Economic data

- Healthcare data

6. APIs (Application Programming Interfaces): APIs allow you to access and retrieve data from various online platforms and services. Common sources of data via APIs include:

- Social media APIs (e.g., Twitter, Facebook)

- Financial data APIs

- Geospatial data APIs (e.g., Google Maps)

7. Internal Systems and Applications: Data can also be sourced from your organization's internal systems and applications, such as:

 - CRM (Customer Relationship Management) systems

 - E-commerce platforms

 - Supply chain management systems - Data Analytics Online Training Institute

8. External Data Providers: Some companies specialize in aggregating and providing data for specific industries. You can purchase data from these providers for various purposes, including market research and competitive analysis.

It's essential to consider data quality, accuracy, relevance, and privacy when selecting and preparing data sources for analytics. Additionally, data governance and compliance with relevant regulations (e.g., GDPR, HIPAA) are essential considerations when working with data from various sources.

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