Posts

Showing posts with the label Data visualization

Featured Post

14 Top Data Pipeline Key Terms Explained

-
Image
 Here are some key terms commonly used in data pipelines 1. Data Sources Definition: Points where data originates (e.g., databases, APIs, files, IoT devices). Examples: Relational databases (PostgreSQL, MySQL), APIs, cloud storage (S3), streaming data (Kafka), and on-premise systems. 2. Data Ingestion Definition: The process of importing or collecting raw data from various sources into a system for processing or storage. Methods: Batch ingestion, real-time/streaming ingestion. 3. Data Transformation Definition: Modifying, cleaning, or enriching data to make it usable for analysis or storage. Examples: Data cleaning (removing duplicates, fixing missing values). Data enrichment (joining with other data sources). ETL (Extract, Transform, Load). ELT (Extract, Load, Transform). 4. Data Storage Definition: Locations where data is stored after ingestion and transformation. Types: Data Lakes: Store raw, unstructured, or semi-structured data (e.g., S3, Azure Data Lake). Data Warehous...
Post a Comment
Read more

What is so Trendy in Data Visualization and Reporting

-
Data Visualization: Data visualization is the process that defines any effort to assist people to understand the importance of data by placing it in a visual context.  Patterns, trends, and correlations that might be missed in text-based data can be represented and identified with data visualization software. It is a graphical representation of numerical data. This is one of the Hot skills in the market, you will get the highest salary. Types of data visualization Visual Reporting Visual reporting uses charts and graphics to represent business performance, usually defined by metrics and time-series information. The best dashboards and scorecards enable the users to drill down one or more levels to view more detailed information about a metric A dashboard is a visual exception report that signifies the ambiguities in performances using visualization techniques Visual Analysis Visual-analysis allows users to visually explore the data to observe the data and dis...
Post a Comment
Read more

5 Emerging Trends in Data Visualization

-
Image
Nowadays, we deeply drowned in data of diverse kinds due to the increased computational power and accessibility. Specifically, in addition to public data available on the Internet (e.g., census, demographics, environmental data), data pertaining personal daily activities are now more easily collected. For example, through mobile devices that can log people's running distances and time or their manual record of nutrition consumption. Due to such expanded sources of data, there appear new applications that involve data collection, visualization, exploration, and distribution in daily contexts. These applications do, not only display static information but also let users navigate the data in forms of interactive visualizations. 5 Emerging Trends in Data Visualization. #1: This emerging trend has brought both opportunities and challenges to interaction designers to develop new approaches to designing data-based applications. #2: Conveying information has been one of main functio...
Post a Comment
Read more