Here at Smarty, we often see companies aggregating address data from multiple sources. Data consolidation improves data quality, speeds up process execution, and simplifies day-to-day information access. Having all your critical data in one place provides a 360-degree view of your business, allowing you to efficiently plan and execute business strategies and solutions. While the merge process may sound painful, the result of data consolidation is worth it. Why Is Data Center Consolidation Important? This lack of transparency can increase your risks of inaccurate data, poor resource utilization, and decreased revenue. The result is a lack of transparency, efficiency, and trust among departments. Siloed data is often stored in a standalone system and may be incompatible with other data sets, making it hard for other departments to access or use the siloed data. What's a Data Silo?Ī data silo is a repository of raw data that s controlled by one department or business unit and isolated from the rest of an organization. Unfortunately, big data can also lead to big problems, namely, duplicate entries, outdated information, data entry error, and last but not least, the dreaded data silos. The answers to those questions lie in data gathered from many different sources. Is there room in the market for your organization to expand to another geographic area? Are your customers advocates or detractors of your product? Was that pricey billboard on Main Street worth it? Without the right information, it's hard to know what the right decision is. What are the Merge Process Steps of Address Data Consolidation?.Address Database Consolidation Challenges. Why You Should Consolidate Data Based on Street Address and Not Other Field Values.Type of Merge 1: ETL (extract, Transform, Load).Why is Data Center Consolidation Important?.Click the "TRY IT NOW" buttons to check them out and read on, to see how address standardization will help you in your dataset merging adventure! Bulk Address Validation You can try some of our address standardization and validation tools here. We’ll discuss the pros and cons of different unique identifiers and show how a standardized, validated mailing address could be the best for you. Standard unique identifiers can be phone numbers, email addresses, or mailing addresses. Merging data from multiple datasets requires one or more unique identifiers to indicate which records are candidates for merging. Handling the high volume data can slow down your company down without useful resources and tools. As time goes on, and technology progresses, data collection only seems to grow and expand. You may be wondering why are we even talking about data consolidation? Because if there's one thing every business does, it's gather data. Merging Datasets is the process of taking multiple original files, cleaning them up, and combining them into one master dataset of addresses and related data. In order to do this, you'll need to merge your datasets. Consolidating your entire organization's data requires taking data from multiple source files, cleaning and verifying it by removing errors, and storing it in a single integrated location. Data Consolidation & Merging Datasets Using Addressesĭata Consolidation is the process of combining an organization's data into a single dataset.
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