Data integration is the process of combining data from different sources into a single database or system. This process is carried out using various techniques and tools to ensure data accuracy and consistency. For example, if a company’s customer information is kept separately in the CRM (Customer Relationship Management) system, ERP (Enterprise Resource Planning) system and e-commerce platform, data integration makes it possible to collect and analyze this data in a single center. Thus, businesses can make more comprehensive and accurate analyzes and rely on more reliable data when making strategic decisions. By speeding up the process of accessing information, data integration increases the operational efficiency of businesses and provides competitive advantage.
How Does Data Integration work?
Data integration basically works by taking data from various sources, converting it into a common format, and then transferring it to a target system. This process helps businesses make informed decisions based on real-time information by keeping data consistent, up-to-date and accurate. This process consists of six steps:
1. Data Extraction
Data is extracted from various sources, e.g. databases, applications, files and other storage.
2. Data Transformation
The extracted data is converted into a common format to ensure compatibility and consistency. In this step, data is cleaned, filtered, merged and transformed.
3. Data Loading
The transformed data is imported into a target system, such as a database or data warehouse. This phase involves indexing and organizing the data for efficient storage and retrieval.
4. Data Synchronization
Data is synchronized between the source and target systems to ensure that the integration between the data is up-to-date.
5. Data Quality Assurance
Measures are taken to improve data quality and assurance, such as data validation, data duplication prevention and error management.
6. Data Delivery
Integrated data is presented to users through various tools such as dashboards, dashboards, APIs, dashboards, etc., directing them to applications.
What Does Data Integration Do?
The use of different systems in different departments leads to a variety of data. This creates data silos, and data silos significantly increase the risk of errors in handling customer data.
Data integration ensures that information is kept and managed in a centralized, organized and accessible format. This improves data consistency and accuracy, enabling teams to run operational processes more efficiently and analyze data more thoroughly.
Who is Data Integration Important for?
Data integration ensures that data is always up-to-date and consistent. It minimizes the margin of error as it eliminates manual data entry. Because of these benefits, data integration is important for almost every sector. Especially companies in the finance, healthcare, retail and manufacturing sectors can work more efficiently and effectively by integrating customer data, supply chain information and operational data.
To give an example;
Health Industry: By integrating patient data from different hospitals, clinics and laboratories, a healthcare system can provide access to patient history from a single point. This integration allows doctors to see patients’ previous treatments, test results, and prescriptions, and thus provide more accurate diagnosis and treatment.
Finance Industry: Integrating customer data collected from various channels (branches, ATMs, mobile applications, internet banking) enables a bank to better understand customer behavior and needs.
What are the Benefits of Data Integration?
- Reducing manual data entry errors and ensuring harmony between systems makes operational processes more efficient.
- Integrating systems such as CRM, sales and inventory provides a 360-degree view of customer data. This gives teams the opportunity to provide personalized services to customers and increase customer satisfaction.
- Integrated data can be analyzed more easily and quickly, helping to make better decisions.
- Gathering data from different sources in one place ensures that data is consistent and accurate.