Why is Data Discovery important ?
Data discovery has a lot of importance for many reasons particularly in modern data driven decision, problem solving & business intelligence. The following are some key factors explaining why Data Discovery is Important:
- Generating Insights – Data discovery allows us to deeply analyze and understand the pattern in a given dataset,this helps in giving us an insight for the future. For example, business data analytics can gain a better understanding of market trends, customer preferences, planning strategies for growth of business and to compete in the marketplace.
- Informed Decision – Access to meaningful insights derived from data discovery leads to making a firmed decision and strategic choices. This improves efficiency and gets a competitive advantage in a market place.
- Continuous Improvement – Data Discovery is not a one time activity it’s an ongoing process. Regular exploration and analyzing in the business leads to the personal growth of the business as due to continuous analyzation of data it gets to know the pattern & loops to run a business smoothly leading to growth.
- Adaptability to Change – In a dynamic business environment an organization needs to adapt changes very quickly to compete in the marketplace. Data Discovery provides the real time insights, allowing business to respond quickly to the changing market, emerging new trends, strategies and changing the customer preferences.
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