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Database Cleansing

The data within a database to either remove or update information that is incomplete, incorrect, improperly formatted, duplicated, or irrelevant.

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Data cleansing or data cleaning is the process of detecting and correcting (or removing) corrupt or inaccurate records from a recordset, table, or database and refers to identifying incomplete, incorrect, inaccurate, or irrelevant parts of the data and then replacing, modifying, or deleting the bad records or coarse data. Data cleansing may be performed interactively with data wrangling tools, or as batch processing through scripting and formating to structure data.

Defining Data cleansing

Data cleaning consists primarily in implementing error prevention strategies before they occur (see data quality control procedures later in the document). However, error-prevention strategies can reduce but not eliminate common errors and many data errors will be detected incidentally during activities such as:

When collecting or entering data
When transforming/extracting/transferring data
When exploring or analyzing data
When submitting the draft report for peer review

What are the benefits of data cleansing?

There are many benefits to having clean data:

1. It removes major errors and inconsistencies that are inevitable when multiple sources of data are being pulled into one dataset.

2. Using tools to clean up data will make everyone on your team more efficient as you’ll be able to quickly get what you need from the data available to you.

3. Fewer errors mean happier customers and fewer frustrated employees.

4. It allows you to map different data functions, better understand what your data is intended to do, and learn where it is coming from.

Clean data means clear direction
Good decisions, bad decisions: they all hinge upon the quality of the data that informs them. Errors cost money, take time to correct, and can damage your brand. Data cleansing is one way to make sure that you can trust the data that your business relies on. And when you trust your data, you can make decisions with accuracy, precision, and confidence.

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Data Cleansing Techniques

Our primary source of data building

We have covered more than 40% market including Information Technology, Computer software, Internet, Telecommunication, Computer network, Computer network & security. Our majority of clients come from IT businesses. If you are a technology company and looking for competitive technology installed base user’s information, then you are on the right page. Using our portal you can review the number of companies using a particular technology. You can search more than 40k+ technologies including IaaS, SaaS, PaaS, Storage, and ERP along with Virtualization Software getting used globally and also place a sample request for data validation and quality review.

Our Technology database covered more than 400+ tech categories and has 10k+ verified Tech vendors operating in the global market.

100+ Million Digital Documents

15+ Million active website

40k+ Installed Technologies

10+ Million News/PR Alerts

100+ Recruitment Agencies

30+ Global Datacentres

200+ Research Firms

20+ Partner APIs

B2B Data Attributes

IRCOIT STREAMLINED PROCESS

Market Research

We deploy a multiple market research activities to gain the perfect data & insights of each projects

Data Building

Once the research analysis is over, we gather all the semi-structured data in one place

Data Validation

All the data get through a proper validation under several resources and legal compliance

Privacy Updates

During the data validation program, we also deploy an opt-out campaigner to let the audience unsubscribe on demand of each project approval. These activities help us to get the accurate file upon delivery.

Database Delivery

Upon satisfaction of data nurturing, validation, privacy updates, now it's time to prepare an excel/.csv file and upload them to the server so the client can download the file through an end-to-end encrypted server.

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