Data Cleansing

What is Data Cleansing?

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Data cleansing cleans up messy data. People call it data cleaning or data scrubbing too. It finds and fixes bad data in datasets. Bad data can be wrong missing stuff, or not important.

Data cleansing makes data better and more accurate. It wants data to make sense, be trustworthy, and work well for looking at . This job has a few steps:

• Error Spotting: Finding and marking wrong data entries.
• Fixing Data: Fixing mistakes like typos or wrong numbers.
• Getting Rid of Doubles: Taking out repeated info from the data set.
• Dealing with Missing Stuff: Filling in or removing blank spots.
• Making Things Match: Getting data to look the same way.
• Checking: Making sure the data is right and complete.

Why is Data Cleansing important?

Cleaning data matters a lot. It has an impact on how well we can use data to make choices. Here's why cleaning data is key:

Clean data improves analysis accuracy. Bad data leads to wrong decisions and poor plans. Redman,1998. Clean data saves time and effort when processing info. It makes things run smoother. Accurate and complete data helps companies follow rules and avoid legal trouble.

Good data gives better customer insights. This leads to better service and happier loyal customers.

Clean data has an influence on many areas. It makes data quality better. It has an impact on how a company works. It helps to comply with rules. It also causes a revolution in customer happiness. These benefits show why clean data matters so much for businesses today. Reliable data allows companies to create accurate reports and insights. These reports play a key role in planning strategies and measuring how well a company performs. Companies need this information to make smart choices.

Good data helps businesses see what's going on. It lets them spot trends and fix problems . Without solid data, companies might make wrong decisions. They could miss chances to grow or waste money on things that don't work. So, having trustworthy data is super important for any business that wants to do well.

What are benefits of using Data Cleansing?

Data cleansing makes data better and more useful in many ways:

1. Clean data helps leaders make smarter choices. It gives them reliable info to work with, so they can figure out what's best for the company (Redman 1998). Fixing mistakes in data and getting rid of stuff you don't need can save a bunch of money. You won't have to spend as much on storing, dealing with, or managing all that information (Haug, Zachariassen, & van Liempd 2011).

2. When your data is clean, you don't have to waste time fixing it by hand or checking if it's right. This frees up people to do more important stuff and gets more work done overall (Rahm & Do, 2000).

3. Data cleansing makes different data sources work better together. It helps data fit together . This makes it easier to combine and study information from various places. Kimball and Caserta talked about this in 2004.

4. A strong data cleansing process plays a big role in managing data well. It makes sure data stays accurate and follows company rules. Khatri and Brown pointed this out in 2010. Good data cleaning helps keep everything in line with what the organization wants.

How Alltius AI Enables Organizations to use Data Cleansing?

Alltius' provides leading enterprise AI technology for enterprises and governments to harness and extract value from their current data using variety of technologies Alltius' Gen AI platform enables companies to create, train, deploy and maintain AI assistants for sales, support agents and customers in a matter of a day. Alltius platform is based on 20+ years of experience at leading researchers at Wharton, Carnegie Mellon and University of California and excels in improving customer experience at scale using Gen AI assistants catered to customer's needs. Alltius' successful projects included but are not limited to Insurance(Assurance IQ), SaaS (Matchbook), Banks, Digital Lenders, Financial Services (AngelOne) and Industrial sector(Tacit).

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