Data Discovery
What are the methods of data discovery?
Methods include data profiling, visualization, querying, and exploratory data analysis to uncover patterns, relationships, and insights within datasets.
What are the goals of data discovery?
Goals encompass uncovering hidden patterns, identifying trends, validating assumptions, and gaining actionable insights to support decision-making and business strategies.
What are the two types of data discovery?
Ad-hoc data discovery involves spontaneous exploration, while structured data discovery follows a predefined approach for systematic analysis and insight generation.
What are the process of Data Discovery?
Involves data preparation, exploration, visualization, hypothesis testing, pattern recognition, and insight generation, fostering a deeper understanding of the data and informing informed decision-making.
What is Data Discovery?
Data discovery is a pivotal step in the data analysis and business intelligence process, allowing organizations to make informed decisions, achieve dynamic growth, and stay competitive in the marketplace.
Table of Content
- What is Data Discovery?
- Key Aspects of Data Discovery
- Why is Data Discovery important ?
- Categories of Data Discovery
- History of Data Discovery
- How is Data Discovered? – Process
- 1. Define the Subject
- 2. Data Collection
- 3. Data Cleaning and Preparation
- 4. Data Analysis and Exploration
- 5. Communicate Findings and Iterate
- Common Data Discovery Challenges
- How to Overcome Common Data Discovery Challenges?
- Data Discovery Use Cases
- 1. Business Intelligence (BI) and Reporting
- 2. Customer Analytics
- 3. Fraud Detection and Security mechanisms
- 4. Supply Chain Optimization
- 5. Healthcare Analytics
- Conclusion