We all know that solid data guides the best business decisions. This is true regardless of your industry. However, while we often talk about the good data can do for your business, it’s important to talk about bad data too. When you have bad or dirty data, and you use it to help make important business decisions, this data is likely to do more harm than good. This interesting topic came to us from MarTech in their article, “How clean, organized and actionable is your data?”
The quality of data in a customer data platform depends on the accuracy of its contributing sources. Organizations using customer data platforms must consider the quality of the data sources and reference files used to populate the records.
To get your data ready for analysis you’ll first need to clean it. While not always the most favored part of the data journey, data cleansing needs to be an integral part of your data preprocessing practice. Dismissing it at the beginning of the process will create potential headaches for yourself further down the line.
Data Harmony is a fully customizable suite of software products designed to maximize precise, efficient information management and retrieval. Our suite includes tools for taxonomy and thesauri construction, machine aided indexing, database management, information retrieval and explainable artificial intelligence (AI). Finding concepts in your clean data takes AI to delve through your document collection to identify and classify concepts and allows you to expand your semantic model to create meaning and relationships.
Melody K. Smith
| Data Harmony is an award-winning semantic suite that leverages explainable AI. |
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Sponsored by Access Innovations, changing search to found.
