Start this new year with clean data in your organization

Start This New Year with Clean Data in Your Organization Data cleansing helps businesses to maintain clean and relevant data that is essential to achieve overall operational efficiency.

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Banks, government organizations as well as small to medium enterprises may have to deal with big data. Inaccurate data levels can grow quickly, compromising the database and reducing business efficiency. Data cleansing services are critical to make sure that only the highest quality, reliable data is retained. Regular data cleaning can resolve bad data issues.

A clean and up-to-date customer database offers multiple benefits such as: •

Increased efficiency of transactions

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More accurate prospect information

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Reduced wastage in the form of incorrect emails

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Compliance with the Data Protection Act

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Better sales targeting and management

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Reduced service response time

By getting rid of bad data you can focus on current and relevant information alone. A regular data cleansing process in place would help firms to continue improving data quality.

Data Cleansing Process -- Steps Involved A step by step scrubbing process targets those areas where the data is weak and needs more attention.

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Identify the data to be cleaned – The first step is to identify the data set that is critical for your business processes. Statistical and database methods can be used to detect anomalies and inaccuracies affecting the quality of data.

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Parsing – This process identifies individual data elements in the source files and breaks down a complex field into a number of fields based on the meaning of data and context.

For example, an address can be sorted into structured data.

8596 E. 101st Street, Suite H Tulsa, OK 74133

Number: 8596 E Street: 101 Suite: H City: Tulsa State: OK

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8006702809

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Standardization - During this step, data can be transformed into the preferred format using both standard and custom business rules. For example, as “Oklahoma” and “OK” will be identified as the same value it can be replaced with one user-defined value. This step also ensures that the details are all in their respective columns.

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De-duplication - Duplicate records can be detected in this stage by checking for misspelling, missing values or different address orders. Consolidation of data can be done and additional information such as phone numbers or additional contacts can also be added.

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Automation - The final step is to automate data quality processes which allow firms to maintain a certain level of data quality over a long period.

One of the most challenging aspects of data cleansing is to maintain a clean list of data. Employing the services of an expert data cleansing company would help to convert your large volume data into valuable information, which is vital for smooth business operations. Outsourcing such time-consuming tasks will also guarantee that you can use your time and resources to focus on core business activities, and thus improve productivity.

www.managedoutsource.com

8006702809