Data Integration

Smarter InformaticsData integration software solutions merge fragmented data from multiple sources, and provide accurate and reliable information, valuable to your business. This is particularly useful for merging data systems from different companies or integrating structures from within the same organisation.

Data integration will benefit organisations of all sizes, and involves the detection, cleansing, converting and delivery of your company’s data. The most widely recognised application of data integration is building a data warehouse. A data warehouse enables companies to combine different data sources into one central repository that can be used for data analysis and reporting.

An extract, transform, load (ETL) process is often used in conjunction with a data warehouse. Data is frequently extracted from multiple operational systems, cleansed and converted to meet business requirements, and then uploaded into the company's data storage, usually a data warehouse. Data extraction, conversion and consolidation of this type is achieved quickly and efficiently through the implementation of an ETL solution.

For large companies or enterprises that have merged, a master data management (MDM) approach may be required. This is the process of linking all crucial data to a master file that offers a single point of reference for all employees and divisions. An MDM solution will increase productivity and enhance operations by having one main data storage location that supplies your business with consistent and reliable data.

The key benefits for employing an integration strategy to your data resources include:

  • Diminish unreliable and inconsistent data through the merging of data formats, specifications and customer profiles, making information more accessible and easier to use.
  • Increase the number of business prospects by storing quality customer-centric data, enabling businesses to provide reliable information tailored to individual needs and requirements.
  • Reduce the possibility of risk exposure by gathering and sustaining consistent, quality and current data that can inform accurate business decisions.
  • Enhance productivity whilst minimising costs and reducing waste by merging information from different data sources, retaining up-to-date data, removing duplications, and using fewer resources.
  • Increase the reliability of data with cleanse and validation processes that reduce errors, inconsistencies and duplications.

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