Data Intelligence
Almost all innovations and decisions in companies today are data-driven. The digital transformation generates data in organizations and processes in constantly new and larger quantities. This requires intelligent data use, fast processing and timely evaluation to prevent the rapid loss of value of previously collected information.
“Data Intelligence”, in combination with other innovation drivers such as Artificial Intelligence (AI) or the Internet of Things (IoT), is now one of the essential building blocks for the systematic analysis and optimization of processes and value creation in any modern company.
You have big plans - we have the right solutions
We support small and medium-sized enterprises in particular in dealing profitably with the collected information. Even more important to us than the actual analysis and evaluation by appropriate tools of “Data Intelligence” are the systematic collection, the processing-optimized transformation and the demand-oriented distribution.
MORE USE AND VALUE FROM YOUR DATA
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You want to know which data you can use and which steps and tools are required
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Information from different sources should be integrated and made available in a consistent, reliable form so that it can be analyzed and evaluated centrally
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You want to take steps to improve the quality of your data and ensure high data quality on a permanent basis
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IoT sources provide large amounts of data, but you lack a frontend for monitoring and evaluation
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You want to take the first steps with artificial intelligence (AI) to make predictive decisions
Leading technologies and products
As a Microsoft Gold Partner, we use the Azure platform and its services. We supplement our toolbox with suitable tools to make data intelligence easy and efficient to use, especially for small and medium-sized enterprises.
Azure Advanced Analytics Architecture
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Enables you to turn your data into actionable insights using best-in-class machine learning tools. With this solution, you can combine any data at any scale and create and deploy custom machine learning models at any scale.
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Data Flow:
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Bring together all your structured, unstructured, and semi-structured data (logs, files, and media) using Synapse Pipelines in Azure Data Lake Storage.
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Use Apache Spark pools to cleanse and transform the unstructured datasets and combine them with structured data from operational databases or data warehouses.
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Use scalable machine learning/deep learning techniques to derive deeper insights from this data using Python, Scala, or .NET, with Notebook applications in Apache Spark-Pool.
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Leverage Apache Spark-Pool and Synapse pipelines in Azure Synapse Analytics to access and move data at scale.
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Query and report on data in Power BI.
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Transfer insights from Apache Spark pools into Cosmos DB to make them accessible via web and mobile apps.
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