It can be defined as the combining of data from various sources and bringing them together for a unified view. How it works is, it involves absorbing information from the vast storehouses of data, filtering the acquired information, and mapping it to transform it into a final data that can be used to take further actions.
It combines data by collecting it from different sources. It helps you to derive more value to your business. When you do not have a unified view of the necessary documents, files and stored data, there are higher chances of confusions and loss of data after a period of time. Multiple databases require multiple operators, this is not recommended especially if your business requires data storage on a regular basis. When you integrate data, you would be able to get access to the data you need as a unified view and as a separate view as and when you need.
How data integration works is easy to understand. It operates with an approach that is still evolving among IT experts. Data such as customer information, sale details, important agreements, proposals and other such documents are stored in databases.
A good data integration model offers the ability to process unstructured data from web pages, social media, etc. There are certain tests conducted to ensure that the data conforms to the business rules and regulations. The process also makes sure there are no duplicates during the integration.
Astera Centerprise Data Integrator: A few key factors that should be kept in mind at the time of data integration are; data quality, data profiling, mapping and transformation. The Astera Centerpirse Data Integrator is extensible and scalable and also provides a straightforward interface that is easy to understand and use. The tool can accommodate many data formats and languages.
Denodo: Digital transformation depends upon how flexible and adapting an approach is made. The process is all about the visualization of a unified view of the integrated data. This tool is popularly known to generate global metadata for searching, decovering and browsing data. Security wise it’s a wonderful tool.
IBM Infosphere: There are a number of powerful and flexible tools that IBM offers. The IBM Infosphere is popular among major brands to tackle large and complex problems relating to data integration data mining and more. You can virtually connect to any kind of source with these tools.
Oracle Data Integrator: The tool offers flexibility of platform. It can connect to any data source and also accommodate data format of any kind. The features it offer are extensive and highly customizable and easy to use. ODI is a popular choice.
Salesforce Integration Solution: This is a software solution that manages communication between Salesforce and other systems. It is done by using APIs to interpret messages that the systems exchange during the integration.
Dell Boomi: Dell Boomi offers you connection of applications and data through a low-code graphical interface with pre-built connectors and APIs. Integration is possible with multiple vendors and Boomi manages the integration process and the maintains the quality on a single interface.
Data Integration is one of the most important concepts of information technology. The big data technology is not just an initiative, a technique or a technology, it is a trend now. The technology offers variety and volume that no other can. Its velocity is revolutionizing.
The big data new technology can also we referred to large sets of data that difficult or impossible to process through traditional methods of data processing. There can be structured and unstructured large sets of data in big companies. Upto 80% data around the world is unstructured. There are a number of challenges and obstacles in big data processing.
Big data integration is huge responsibility. At Dreamstel we offer fully managed integration services, Salesforce and solutions for cloud big data technologies. We focus on lowering the overall cost of operation by aiding data governance and manageability. We enable a completely scalable, cost effective and efficient data architecture with iPaaS, BDaaS and SaaS.