Data cleanup, or data rubbing, is the process of detecting and correcting or removing data or records that are incorrect from a database. It also includes correcting or removing unformatted or duplicate data or records. The data removed in this process is often referred to as “dirty data”. Data cleaning is a necessary process to protect data quality. Large businesses with extensive datasets or assets typically use automated tools and algorithms to detect such records and correct common errors (such as missing zip codes in customer records).
The most powerful big data circles have rigorous data cleanup tools and processes to ensure that data quality is protected and trust in datasets is high for all types of users.
It is difficult to make a clear definition of data quality. The truth is that your data quality is good if the data achieves its purpose of using it. For example, showing the right values on a management board to guide the organization ensures that management is also consistent and the process is managed correctly.
As its full name suggests (Structured Query Language), SQL is responsible for querying and modifying information stored in a specific database management system.
Backpropagation is a fundamental algorithm used in the learning process of artificial neural networks. This algorithm allows neural networks to learn how to optimize the weights needed to solve a problem.
We work with leading companies in the field of Turkey by developing more than 200 successful projects with more than 120 leading companies in the sector.
Take your place among our successful business partners.
Fill out the form so that our solution consultants can reach you as quickly as possible.
We were able to increase the data processing speed by 13 times on average and 30 times at maximum with this project.
By combining our 30+ years of experience and experience with the centers of excellence in our ecosystem, we prepare your organization to lead the digital transformation!
