Data integration is the systematic harmonization of institutional data sets. The process seeks to unify multiple source data to provide cohesion for organizational use. Entities in various sectors, including health care, financing and accounting, legal, agricultural and industrial or mining fields, benefit from the coherent structure data integration procedures offer.
Data integration is an overarching process that encompasses data from various sources, such as digital platforms and apps, cloud systems, warehouses, lakes and other databases. Data integration aims to store this multi-source information in a common format, making it easier to use.
The extract, load, transform (ELT) system is a popular integration approach. This involves extracting data from the source, uploading it to your database and transforming or processing it into a suitable format.
ELT approaches enable automated transformation or processing, a critical data integration phase. Other data integration techniques include:
You can utilize these and other data integration techniques to:
Manual integration can result in various internal challenges in managing large amounts of multi-source data. It can result in data latency and outdated inputs, security vulnerabilities, processing inconsistencies and data inaccuracies. To reap the benefits of data integration and enhance your business operations, you can follow these integration best practices.
Integration technologies can help you address manual integration challenges and make the process seamless. Automated tools like our data governance software can manage your data integration phases, formatting and storing information in cohesive structures for convenient use.
Creating frameworks that make data more usable and accessible for all users and departments is important. Establish formatting constraints like range, data type, source and more to help with organization. Integration tools like Anomalo’s observability tool can help you streamline your data formatting and automate data organization, notifying you if inconsistencies arise.
Ensure your selected data integration tools and ecosystem components, like your data warehouse or lake, have advanced security to keep large-volume and private data safe. This is particularly important for industries like health care or legal firms that work with intimate customer data and source data from customer relationship management (CRM) platforms.
Deciding on who can access what integrated data is another key best practice for your integration implementation and overall data governance.
Choose flexible and versatile methods and tools that can support the growth of your business and industry. You need integrated data techniques and cloud systems that can expand and evolve with developing trends.
Scalability also involves staying current on relevant technologies. A platform like Anomalo capitalizes on artificial intelligence (AI) and machine learning (ML) to elevate data integration.
Include integration steps like data cleansing, validation, governance, analysis and quality assurance to ensure reliable data for your organization. Anomalo’s diverse capabilities help organizations generate and maintain quality data by identifying anomalies, errors and other data issues.
Learn how to design cohesive, unified data collection and maintenance with Anomalo. Our systems are perfect for nurturing an excellent and interconnected data network for your organization. See how you can partner with us when you request a demo.