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App Maestros assists businesses in overcoming data difficulties, increasing end-user satisfaction, and guiding corporate strategies through intelligent insights. Our data engineering team uses the correct technology, processing tools, and technique to analyze structured, semi-structured, and unstructured data. We also offer complete data lifecycle management services, including upgrading our clients' expensive and siloed in-house data infrastructure and transforming large data pipelines into robust systems ready for agile business analytics.Discuss your project
Removal of structured and unstructured data from streaming and batch sources and refining and cleaning data to make it available to data scientists and business users for exploration and analysis on legacy database systems or cloud systems.
DF, Databricks, Synapse, Informatica, and another legacy, Big Data, and cloud orchestration and data management pipeline tools and methodologies are being used to build production-grade repayable and independent data workflow pipelines manipulating and storing data in batch and real-time.
Expertise in legacy and cloud-based deployment services for developing efficient production build and release pipelines based on infrastructure-as-code artifacts, reference/application data, database objects (schema definitions, functions, stored procedures, and so on), data pipeline definitions, and data validation and transformation logic.
Using operational data to improve efficiency; building machine learning and artificial intelligence use cases to improve sales and operations, improve supply chain visibility, detect gaps, improve replenishment rates, and access distributor data.
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