Data profiling refers to the systematic analysis of the content of a specified data source. The goal of data profiling is to gain a better understanding of the raw data since you cannot gain insights or find trends without fixing it first.
Data profiling must be completed before processing data with machine learning algorithms and involves determining if the data is complete and accurate enough to solve the problem at hand. This process is necessary to clarify the content, structure, and relationships within the data so that you can build your predictive model.
Some common aspects of data profiling include collecting descriptive statistics and performing quality assessments. These descriptive statistics include information like count, sum, minimum, and maximum – all details that will help managers better understand the dataset they are working for.
Other features of data profiling, including tagging data with keywords and descriptions, discovering metadata and identifying distributions within the information available.
Have you heard the saying, “garbage in, garbage out”? This represents the idea that if you use low-quality data as an input, your outputs will always be inaccurate and faulty.
In other words, the outputs of your machine learning model and predictive AI tools are only as good as the data you use to train them. Failure to profile your data can prevent your business from making accurate decisions. This can translate directly into dollars lost – a study by The Data Warehouse Institute found that problems caused by poor data quality cost businesses over $600 billion a year in the US alone.
Data profiling is essential for businesses to detect data quality issues early on so that they can correct them and move forward with their IT projects. It can also help them uncover new requirements that they had not previously considered, as well as pinpoint the strengths and weaknesses of their data collection processes.
At LogicPlum, we give you access to some of the most sophisticated data models in the industry to help increase the speed and accuracy of data profiling. Our automated data profiling tools eliminate the guesswork in identifying problems with your data and puts your business in control of the dataset.
Our managed services and products have helped organizations in various industries across the globe automate their data profiling so that they can become data-driven businesses.