The data cleansing process becomes challenging when organizations run in countries with different languages and multiple time zones. Most outsourcing options involve collaborating with contractors who are not fluent in English. And finding an ISO-certified data cleansing service provider is always a challenge. You need a dependable data cleaning consultant who understands your requirements, aligns with your business goals, and offers 100% accurate services with quick TATs.
But data cleansing is time-consuming and can require additional employees. Partner with Flatworld Solutions for data scrubbing services; we enable organizations to overcome time and cost challenges by offering top-notch services at the best rates. Reserve your focus for core business functions while we make your business data more coherent.
Flatworld Solutions helps you with data enrichment services to improve data quality in all file formats and computer systems including digital and offline databases. Our data enrichment solutions extend to social media data, in-house and cloud-based CRM data, point of sale systems, and omnichannel retailing data.
Our data validation services help C-level executives and managers eliminate inferior quality data and ensure that decisions are based on consistent and correct information. Our data validation team finds, corrects, and removes inaccuracies, inconsistencies, and corrupted data records in all file formats and locations.
The primary purpose of our data mining services is to eliminate redundant data and reduce storage overhead expenses. During the last two decades, our ISO-certified outsourcing experts have provided outstanding data mining outcomes to 18,000+ global clients. Our clientele includes Fortune 1000 companies and individuals, small businesses, and private enterprises.
We are a leading data cleansing company that employs a customer-centric and customized outsourcing approach to meet the specific requirements and budgets of each client. Our workflow includes the following steps -
Definition of data cleansing requirements
(optional) - Delivery of a trial data cleansing project that establishes quality standards. After client approval of the test project
Service level agreement terms such as pricing and scheduling
Appointment of a Project Manager and allocating data cleansing tasks
Importing unclean data (Excel, CSV or Tab-separated text file format) into our cleansing system
Deduplicating data by identifying potential duplicate entries and eliminating them. This task is manually reviewed for mission-critical data
Exporting data in formats that include XML, Excel, PDF and others as needed
Quality check to monitor data cleansing accuracy and make any required revisions
Final delivery via the method specified by the client
We are an ISO-certified data cleansing company that offers high-quality database cleansing services to international clients. Our services adhere to international guidelines; they are EU GDPR compliant. The benefits of partnering with us include -
Outsource data cleansing services to us today. As reflected by our work style and business practices, it is easy to collaborate with us -
FWS aided a financial giant with quick and exact invoice data entry services by using 5 dedicated data entry specialists. This reduced their workload by 50% and helped them save 60% of their costs.
FWS helped a U.S.-based company to complete their cleansing and enrichment services for their existing Salesforce database in just 30 days.
Flatworld Solutions is a one-stop global outsourcing provider. In addition to data hygiene services, our international team of experts can help with specialized tasks such as visual analytics, industry analysis, and packaging design services.
Ensuring hygiene of existing data is done by scrubbing the old data and appending it with the latest ones. In some cases fixing errors due to inaccurate data entry.
A clean data helps business grow by accelerating decision making. On the other hand, bad data can cause chaos and can increase the overhead to attempt fixing.
In statistics, the hypothesis depends on pattern interpretation and it is only possible when you have clean data to work with. A process of removing or replacing a bad point in a dataset with clean ones.