Real-Time Data Integration

1. Connecting Databases and Applications Through Data Integration

2. In the present data-driven business environment databases and applications often have to be connected in a way where changes of data in one system are simultaneously and automatically updated in all other linked systems. This is known as real-time data integrationand companies need it to get timely and relevant information based on which key decisions are made. It facilitates business growth and development and helps to expand customer relationships. Data integration helps companies face fiercely competitive business ecosystems, globalization, and customer expectations. Not only do large organizations opt for real-time data integrationbut small and medium enterprises also run various applications and databases on the cloud or in-premises opt for it too.

4. The need for real-time data integration Why do organizations need to link applications and databases between various data platforms? · Transfer of data efficiently and economically – Single records are moved in this type of data integration and not entire batches at a time. This saves time and is cost-efficient too as computing and storage facilities in the cloud are charged according to the quantum of resources used. · Optimized customer engagement – Businesses can use real-time CRM to trigger emails as soon as a purchase is completed thereby increasing customer engagement. Updated customer insights about available stock, account balances, purchase history, and loyalty rewards ensure heightened customer service. · Monitoring key operational areas – Real-time dashboards provide a constantly updated flow of information in key operational areas such as inventory levels, the supply chain, customer purchases, and staff. This helps in better decision-making. Best practices for creating real-time data integration strategies Several aspects have to be considered before developing real-time data integrationstrategies. · Change to faster and more efficient applications – Switch to applications that use the latest cutting-edge technologies. Stop using the older batch-oriented ETL applications that do not sync with the apps required for data integration and affect performance and efficiency. · Parallel processing – When the high volume and high-speed applications are present in the network, parallel processing is required to handle these data streams separately from the older batch apps already existing. Coordinated ingestion engines and multiple parallels that can scale up and down to meet data processing requirements are required in these cases. · Integration stimulation – Increase testing and up-front simulation. It is required more for real-time data integrationthan traditional data integration. · Planning for component failure – Failure of components in sections of the data pipeline is a major challenge for data integration. Inappropriate designing can result in data system outage or data loss. It is therefore essential to decouple all phases of the pipeline to establish resiliency in every phase so that the full system runs without a hitch.

5. Value can be had from real-time data streams only when developers can implement real-time data integration to new applications. Organizations must monitor continually how their devices, systems, and applications are interacting with each other.