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Data integration is critical for data-driven business management as it harmonises data from different sources. Real-time data integration provides transparency and error detection. Data quality is improved and efficient decisions are enabled. The strategy requires requirements analysis, data assessment, technology selection, architecture and governance. Deletion and archiving concepts are important. Our data intelligence expertise includes products from Qlik, Microsoft and Talend to provide you with the best solutions.
Data-driven business management requires data integration, as it ensures that data from different sources and systems are brought together and harmonised. Only when complete, correct and consistent internal and external information is easily and quickly accessible and can be linked together can it fully develop its benefits as a basis for data-driven decisions:
Data Integration enables companies to bring together data from different internal and external sources. This creates a holistic picture of the company's data that reaches across different departments, systems and processes. Such a comprehensive understanding is critical to identifying connections, patterns and relationships in the data and making informed decisions.
The integration of real-time data offers companies the chance to bring more transparency into their processes, to increase planning reliability or to detect possible sources of error in time. By integrating real-time data such as physical values (temperature, pressure, etc.), production companies can gather information about the effectiveness of their systems. Actual values can be compared with target data using algorithms that trigger reaction scenarios in real time if certain threshold values are exceeded or not reached.
Data integration enables companies to solve data quality problems by automatically cleansing, validating and harmonising data. Inconsistencies, redundancies and errors in the data are detected and corrected to ensure high data quality and consistency.
Data integration supports efficient decision-making processes by facilitating access to relevant and timely data. Managers can access integrated data without having to spend time and resources manually searching and compiling data. This enables faster and more informed decisions by providing up-to-date data for analysing and evaluating options.
Data Integration helps to manage data effectively. Data is easier to organise, store and process. This facilitates access to relevant data and enables more efficient use of data for operational processes, reporting, compliance requirements and other business needs.
A clear data management strategy is important to carry out data integration effectively. Without a solid strategy, difficulties can arise in data identification, prioritisation, mapping and updating.
A requirements analysis should include identification of data sources, data targets, data formats, integration patterns (batch-oriented or real-time), required data quality, data protection requirements, volume of data to be integrated, etc.
Subsequently, existing data must be assessed in terms of their quality, consistency, completeness and relevance. It makes sense to identify data sources that should be prioritised for integration, as well as data that may need to be cleansed, harmonised or transformed.
Based on the company's requirements and goals, suitable data integration technologies can then be identified and selected.
To ensure effective data integration, the next step should be to develop a suitable data architecture and data modelling. It must be determined how the data is to be integrated, transformed and made available. Real-time data is playing an increasingly important role. They offer companies a particularly large potential for value creation, but require special attention and a well-coordinated and well thought-out architecture for data integration.
An important aspect of the data integration strategy is to implement measures for data validation and quality control. This includes testing to ensure that the integrated data is correct as well as consistent and meets the defined quality standards.
In addition, governance policies and compliance requirements related to data integration should be considered. This includes data integrity protection, data security, data protection regulations, data access controls and compliance with legal requirements such as the GDPR.
After defining the data integration strategy, the implementation of the corresponding technologies and processes takes place. In order to ensure efficient data integration, the integration process should be continuously monitored so that errors can be corrected at an early stage and adjustments can be made if necessary.
The concepts of deletion and archiving should be incorporated into the data integration process.
To ensure that data that is no longer needed or has lost its validity is removed from the systems, companies should have deletion concepts in place. This helps to improve data quality and to keep data stocks lean and up-to-date. It must be determined when and how data is to be deleted in order to ensure that any legal and internal company guidelines are adhered to.
For compliance reasons, historical analysis, or other purposes, the archiving of certain data may be necessary. Accordingly, companies should create an archiving concept that specifies which data should be archived, defines the archiving processes and technologies, and ensures data integrity and accessibility over time.
As a data intelligence expert for holistic end-to-end data intelligence with many years of project experience, we support companies in all process steps from requirements analysis to tool selection and solution implementation..
Our product portfolio in the area of data integration includes data integration software from three leading providers:
We maintain close partnerships with all three manufacturers and ensure that we stay up-to-date with the latest technologies through regular training. As a Qlik Elite Solution Provider, Microsoft Partner, and Talend Gold Partner, we are happy to advise you on the selection and implementation of a data integration solution that best suits your requirements - so that you can derive the maximum benefit from your data.