Data cleansing outsourcing- hiring a third-party vendor to clean, upgrade, and maintain your database -is a cost-effective business strategy.
Clean data directly impacts businesses processes, improves productivity, and fuels informed decision-making. However, frequent validation of large data volumes requires time, concentration, understanding of data sources, and training in certain tools.
If you outsource data cleansing, you can get the advantage of a coherent database with minimal effort and at a reasonable cost, given you choose a suitable vendor.
So, how do you select the right data cleansing outsourcing company? Here’s the answer.
Industries That Require Data Cleansing Services The Most
Data cleansing is a critical business process. It leads to accurate, high-quality information, reduces overhead costs, and improves the efficiency of data-related tasks.
Most industries that regularly deal with vast amounts of information require data cleansing. For example, real estate companies and hospitals utilize updated data to avoid operational errors and run all their functions smoothly.
Here are some other domains that frequently need clean, updated, and accurate data.
1. Market research companies
Market research companies perform research tasks for clients, which involves creating a vast database of customers, competitors, suppliers, vendors, wholesalers, manufacturers, and various other players involved with the business.
Their data needs to be up to date and well organized to avoid any business errors, so they prefer data cleansing outsourcing.
2. eCommerce companies
Clean data is the backbone of eCommerce businesses. Online retail usually operates on a versatile database of customer contacts, product listings, vendors and supplier details, etc. And, because that information is dynamic, it requires frequent validation, verification, and synchronization.
That is also why most eCommerce companies outsource data cleansing.
3. Artificial intelligence and machine learning
Businesses specializing in Artificial intelligence (AI) and machine learning (MI) also require high-quality data cleansing services. It helps remove errors & noise and enhance data quality. This clean data is then used to train AI and ML models for better outputs.
Reasons Why Businesses Outsource Data Cleansing
Outsourcing data cleansing can save time and money by streamlining and increasing operational efficiency. It also helps businesses redirect their focus on growth activities without worrying about the credibility of their database.
Here are some of the most significant data cleansing outsourcing benefits.
1. Increase business productivity
By outsourcing data cleansing services, an organization gets the advantage of experienced professionals and specialists. Such dedicated support leads to high functional efficiency and better overall productivity.
2. Reduce turnaround time
Quick results are one of the most significant data cleansing outsourcing benefits.
When it comes to data, even a slight delay can affect projects in a big way, affecting the productivity of vendors and their clients. Outsourcing data cleansing helps reduce that turnaround time by a large margin.
3. Get your data security covered
The guarantee of safety and confidentiality is another major advantage of data cleansing outsourcing.
Data cleansing companies take responsibility for their client’s data and ensure 100% data safety. They create data backups and employ techniques to prevent loss, leakage, or tampering with the data.
4. Assured high return on investment
Business investments involve money, time, and effort. The return on those particular investment aspects can be pretty high with reputed data cleansing outsourcing companies.
The reason- high-quality services, advanced tools, and professional support.
Choosing The Right Outsourcing Partner For Data Cleansing
Picking one out of many data cleansing outsourcing companies in the market can be a challenging task. However, following systematic research, analysis, and elimination approaches can help you find the best fit for your needs.
Here is how you can choose the best data scrubbing outsourcing partner for your business.
1. Identify your requirements
Identifying your requirements is one of the most crucial aspects of data cleansing outsourcing. Unfortunately, many businesses ignore this aspect and reach out to experts without knowing what to expect of them.
- Create a list of the critical data points that need cleansing
- Review your data collection and database building strategy
- Flag problem areas in your datastore
- Determine an appropriate cleansing standard
Use this information to establish deliverables for your data outsourcing partner. These may include the number of files to be processed, required accuracy rate, number of copies, centralization of data, etc.
2. Research multiple data cleansing company profiles
Collect details about different data cleansing outsourcing companies. Doing so will give you an idea about their portfolio, total experience, and expertise. Also, research the individual profiles of their teams, if possible.
Use this information to shortlist the companies you like and approach them one by one. Then, compare the vendors accordingly to choose the best deal.
3. Get a budget and time estimate from data cleansing companies
Deadlines and cost are critical contract differentiators.
While you won’t mind spending the extra buck when it comes to availing high-quality services for your business, the pricing should be reasonable and in line with the deliverables, industry standards, and timelines.
Decide after considering all these factors.
4. Discuss different means of communication with data cleansing companies
The most profitable (high-quality+reasonable) data cleansing companies are often remote (or offshore.) Therefore, seamless communication is critical to ensure better outcomes.
Find out how you can interact with your data cleansing outsourcing company and how they plan to establish maximum transparency.
5. Request a data cleansing trial
If possible, get a data cleansing trial.
You can forward some old databases in the form of files and ask data cleansing companies to provide an analysis. A decent vendor should clean the data, point out the errors, and suggest necessary changes.
6. Choose the best data cleansing outsourcing company
Choose the best fit that caters to all your requirements and falls within your budget.
You can also use other filters, like infrastructure, the latest data cleansing tools, etc. We suggest conducting virtual interviews to judge the resources that may be assigned to you by a data cleansing outsourcing company.
Negotiate to get the best price and time estimate as well.
What To Expect From Your Data Cleansing Outsourcing Partner
All data cleansing outsourcing companies have their strengths and weaknesses. To choose the right one, you must seek a balance between what you want and what they offer.
Here are a few things you can expect from your data cleansing outsourcing partner:
1. A good understanding of your business requirements
One thing you should always expect of your data cleansing partner is understanding. They must grasp your vision, goals, and expectations and develop an actionable plan to provide you with the required services that will lay the foundation for further processes.
2. Quality data cleansing services
There is absolutely nothing wrong with expecting high levels of quality and accuracy while availing data cleansing services from experts. The final data prepared by your outsourcing partner should be business-ready and free from any errors that can hamper your business. Expect your partner to list key data points and valuable insights that can drive your sales.
3. Customer-oriented data cleansing service
The way your data cleansing outsourcing partner deals with you and your vision is crucial. Expect your partner to think out of the box and go out of their way while helping you achieve your short-term and long-term goals.
4. Latest tools
Most good data companies use the most sophisticated and latest data cleansing tools. Some of these tools are mentioned below. Make sure that the company you choose utilizes these tools as well.
Top three tools used by data cleansing outsourcing companies
IBM Infosphere, Data Ladder, Tibco Clarity, Melissa Clean Suite, Openrefine, Trifacta Wrangler, & Winpure are some of the best data cleansing tools available. Most reputed service providers use these devices to enhance their service offerings.
So, make sure your data cleansing outsourcing partner also uses a few of these tools.
1. Tibco Clarity
Tibco Clarity is one of the best data cleansing tools, which utilizes an interactive interface for data transformation using visualizations and rules-based validation. Tibco Clarity helps standardize, validate and deduplicate business data, resulting in high-quality finalized data that can be used for further processing and analysis.
2. Winpure Clean & Match
Winpure Clean & Match is beneficial in dealing with consumer data and customer relationship management (CRM) data. It is a user-friendly and cost-effective tool that can deal with various database formats such as SQL Server, Access, and Dbase files.
3. IBM Infosphere Quality Stage
IBM Infosphere Quality Stage helps in database cleaning, warehousing, and managing Big Data needs. Most data cleansing outsourcing companies use this tool for data monitoring and transformation. Blocking unclean and poor-quality data is one of its biggest strengths.
We hope this article simplified data cleansing outsourcing for you.
If you need more help with this, join hands with one of the most experienced data cleansing outsourcing companies in the industry- Data-Entry-India.com.
Data-Entry-India supports businesses with high-quality data cleaning, scrubbing, standardization, enrichment, and enhancement services. We also offer reasonable quotes, advanced infrastructure, and flexible engagement models. With over 1,000 clients and a presence in over 30 countries, we are recognized for quick deliveries and impeccable data qualities. You can get a free quote or request a sample by emailing requirements to firstname.lastname@example.org.
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