How Can Businesses Best Leverage Data scrubbing?

1. How Can Businesses Best Leverage Data scrubbing ?

2. The hype around data is hardly news. It is a critical part of a business and rightly so. It is the ultimate competitive differentiator and referred to as the new oil of the world that of course, can’t be used raw and needs to undergo various processes of refinement such as data scrubbing cleansing and modification.

3. Why do businesses need Data Scrubbing ? More than twenty per cent of revenue is lost because of bad quality data. Over forty per cent companies are dealing with messy data plaguing their systems across BI, marketing and CRM and eventually hampering their growth. Only sixteen per cent of businesses acknowledge that their data is accurate and secure.

4. People change jobs, locations, e-mail IDs, phone numbers and job functions. When the information isn’t synced with the database, it results in bad data. Often businesses utilise a third-party database, which leads to duplication of incorrect data, flooding the system with wrong, outdated and incomplete data.

5. are semi automated, and manual. The data can be customised following a business’ specific need and challenge. The expert and seasoned data engineers work through the vast sets of data in the following phases:  Data scrubbing service

6. Rectification of records : De-Duplication Enhancement of data Standardization of data Data addendum

7. Difference between and Data scrubbing is an evolved and more technical process merging, translating and filtering out the inconsistencies in data Data cleansing is referred to as the identification and elimination of inaccurate and incomplete records in a data set. Data Scrubbing Data Cleansing encompassing the

8. How does data go bad ? Research by  Marketing Sherpa  found out that up to thirty per cent of data becomes inaccurate. When a business doesn’t work proactively towards to counter the effects of poor-quality data, the growth goes for a toss.

9. It is a disaster waiting to happen. Several factors contribute to bad data, which are: Legacy Systems Silos in Business Processes: People Database

10. Best Practices for Businesses Data Scrubbing A  report by Forrester established that a Fortune 1000 company could add more than $65 million in revenue to its annual net income with a ten per cent increase in data quality! Who knew bringing in a whopping million is ‘this’ easy and doable! Some of the best pratices are : Data should be standardized. Align your approach Validate and Verify. Training and Education.

11. Data Scrubbing As the Ultimate Solution According to industry experts, only  three per cent  of companies meet the basic quality standard of data.  Ronald Van Loon  in Top 3 Global Machine Learning and Big Data Influencer explains that the data needs to be maintained regularly whereas Big Data Marr believes that it should be thoroughly cleaned before being used to yield any insights. Expert  Bernard

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