Revolutionize Your Data Analysis with Matching Solutions

Revolutionize Your Data Analysis with Matching Solutions

Ever found yourself frustrated with matching data using Excel? Or worse, having to redo the matching of two data sets because of too many false negatives? You’re not alone. Data analysis is tough, made tougher with ancient practices that can no longer keep up with the complex nature of data today. Yet, most data analysts still spend their days manually coding scripts for data matching. 

Studies have shown that about 40-50% of data analysts are spending a significant amount of their time manually coding matching scripts to match data. This activity can be incredibly tedious and time-consuming, making it difficult for professionals to focus on more valuable data analysis tasks. As a result, many organizations are now turning to automated data-matching solutions in order to reduce the burden of manual coding and streamline their processes.

What are the capabilities of a data matching solution?

Data matching solutions are revolutionizing data analysis in organizations, allowing companies to clean, de-duplicate, and consolidate vast amounts of structured and unstructured data from disparate sources more efficiently, quickly, and accurately than traditional methods. These solutions help businesses to quickly process and derive the value of their data effectively for better & faster decision-making. Data matching using WinPure is one example of such solution that contributes to a company's efficiency and effectiveness by saving time and resources, streamlining processes, and providing valuable insights for informed business decisions. For example, a data matching solution can help a business de-duplicate CRM data from two different sources during a merger and acquisition process within just a few days, allowing teams to spend their time wisely on strategic planning instead of mundane, iterative tasks. 

Other than efficiency and proficiency, some key capabilities of a data matching solution include: 

  • Identifying relationships and discrepancies between two or more sets of data
  • Cleaning, processing, and transforming large sets of data within a single dashboard 
  • Easy-to-use interface for non-technical users 
  • Automatically linking records to identify matches across databases
  • Merging multiple data sources into a single view, without any manual intervention
  • Verifying the accuracy and completeness of information
  • Detecting duplicate records for improved data quality

A data matching solution like WinPure for example, even allows for advanced functions in creating custom rules and standards without needing coding knowledge. 

Why are data matching solutions needed? 

Data matching solutions provide an invaluable way for organizations to streamline their operations and improve outcomes by leveraging automated algorithms to identify patterns among large datasets. 

These solutions enable organizations to quickly identify important correlations between variables within the datasets that may not be immediately obvious or easily understood. By doing so, businesses can accurately detect trends that could inform strategies or decisions related to marketing initiatives or problem-solving processes. More importantly, data-matching solutions allow for greater scalability within an organization by providing a single platform that connects different sources of information, increasing the likelihood of discovering actionable insights from the analyzed data.

Accuracy and efficiency as key benefits

The primary benefit of data matching solutions is improved accuracy when extracting insights from datasets. By relying on automated processes instead of manual ones, errors associated with human input are significantly reduced. This allows organizations to quickly conduct research without having to worry about misidentifying items due to incorrect inputs or other mistakes made during manual analysis processes. 

When it comes to data analysis, teams must be able to focus on what truly matters - deriving meaning from data. They are not supposed to spend 80% of their time cleaning and transforming data, which can now easily be done with advanced data matching solutions that pre-process, prepare, clean, and de-duplicate data within a single interface. 

Lastly, these types of solutions reduce overall processing times due to their ability to rapidly process high volumes of incoming data from disparate sources simultaneously instead of relying on laborious manual efforts. A data analyst can save up to 60% of their work time with the help of a data matching tool. 

Examples of how data matching solutions can revolutionize data analysis

Wondering how data matching solutions can help? Here are a few examples. 

  1. Automatically identify and correct discrepancies between sets of data. An advanced data matching solution like WinPure allows users to see hidden errors that would otherwise be hidden or unknown to the analyst. A key difference between manual and solution-based data matching is the fact that you can only detect errors that you know exist, not those that you don’t know! For example, did you know most analysts can’t catch an accidental “dot” in a name field? It’s a minor problem, often ignored, resulting in data that looks “dirty.”
  1. Improve user experience. Your customers won’t like being sent multiple emails or marketing materials to their home and office addresses. Poor data leads to poor and annoying user experiences. With data matching, you can consolidate your customer’s information and create master records that can then be used to identify relationships between different users (such as family members under a similar last name) and provide them with customized offers. 
  1. Segmentation-based marketing campaigns. Leveraging algorithms such as Machine Learning, data matching solutions can quickly generate highly accurate customer profiles that enable personalized offers based on user behavior and preferences. 
  1. Remove duplicates to ensure data quality. A data matching tool identifies duplicates by comparing records based on specific criteria such as name, address, contact number, and other details. It can also use fuzzy logic to compare similar-sounding names or words. Additionally, the tool can use algorithms that look for duplicate values in the same field or across fields of different records. Duplicates are the biggest cause of concern in databases, especially since they make it difficult for businesses to identify the most valid ID of an entity. This lack of validation can turn into a data privacy nightmare as seen with a medical device manufacturer that failed to accurately match patients with their implanted devices and consequently put nearly 1 million patient records at risk of being accessed by unauthorized individuals.
  1. Create golden records. A data-matching solution can help companies achieve golden records by identifying and removing duplicate records from their databases. The tool uses criteria such as name, address, contact number, and other information to identify and remove duplicates, allowing companies to create a single source of truth stored in “golden” records. This helps improve communication between departments and ensures that accurate information is shared between internal teams and external customers.

Matching solutions are there to make your data analysis job easier, more efficient and effective, especially in a landscape where data is getting more complex and disparate by the day. Businesses are trying hard to keep up with the influx of data and while it’s easy to collect data, trying to make sense out of it is a daunting task that requires the assistance of a powerful matching solution!