A naukri.com initiative
Hackernoon
1d
193
Image Credit: Hackernoon
The Marketing Data Cleaning Query Cookbook
- In the world of Agentic AI, data quality is crucial as autonomous systems drive marketing decisions based on CRM and analytics data.
- Gartner reports that poor data quality costs organizations an average of $12.9 million annually, affecting efficiency and decision-making.
- The article offers a SQL query cookbook for marketers to clean and enhance data using SQL Server Management Studio.
- Marketers can now describe data issues in plain English, generate SQL queries, and run them without advanced technical support.
- Queries include tasks like fixing name capitalization, identifying and fixing suspicious or swapped names, building full names, and trimming extra spaces.
- Additionally, the cookbook covers fuzzy matching, standardizing text, dealing with missing data, and avoiding duplicate data using SQL queries.
- It also addresses out-of-range values, contradictory data, invalid emails, identifying internal or test contacts, and splitting data into multiple columns.
- Lastly, the article suggests training GPT models on specific schemas for more accurate SQL assistance.
- Clean data is emphasized as the key to successful AI implementation in marketing, facilitated by SQL queries and ChatGPT.
- Marketers are encouraged to leverage the cookbook, engage with ChatGPT, and enhance their data management skills for efficient AI utilization.
Read Full Article
11 Likes
For uninterrupted reading, download the app