Structured data are datasets with strong and consistent organization. Structured data is managed with structured query language (SQL), where users can easily search and edit data.
Structured data is organized into rows and columns with known and predictable content. Each column contains a specific type of data, such as date, text, money, or percentage. Data that does not match the data type of this column is rejected as an error.
Relational database tables and spreadsheets typically contain structured data. The high level of semantic structure combines master data and historical data into a data model. Data model subject areas include topics such as customers, inventory, sales transactions, prices, and suppliers. Structured data is easy to use, and data integrity can be strengthened. When large amounts of past phenomena are captured, structured data becomes big data.
Because structured data makes the editing process simple and fast, it can be easily understood by machine learning algorithms. Queries are also made easier by users who can access, understand and interpret the data.
Structured data handles highly organized quantitative data managed with SQL databases, while unstructured data handles qualitative data that does not use predefined databases that are managed in the best NoSQL databases (such as MongoDB). All important business processes and decisions are based on structured data. Data warehouses are the basis of data lakes and applications. When integrated into a data model, structured data provides fast and great business value.
Data anonymization techniques are the modification of data in systems in such a way as to prevent the data from pointing to a specific individual while maintaining the format and consistency of the data.
GPT-4.5 is the latest artificial intelligence language model developed by OpenAI. This model, which comes as a continuation of GPT-4, aims to make the user experience more efficient and intelligent by taking its natural language processing (NLP) capabilities even further.
Disinformation security is a next-generation cybersecurity discipline that provides protection against deliberately false or misleading information campaigns. This security approach uses specialized technologies to detect, verify, and prevent the spread of malicious narratives.
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.
The Self-Service Analytics platform was designed for all Enerjisa employees to benefit from Enerjisa's strong analytics capabilities.
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!
