Data Engineering Services
Our team of data engineering experts can help you design, build, and implement modern data systems that enable data-driven insights and advanced AI/machine learning capabilities.
We leverage our deep expertise and innovative approach to help you ingest, transform, and consume your data with speed, accuracy, and flexibility. We do this by taking a different, principled approach to building your data systems.
Iterative Approach
We take an iterative approach to deliver MVP every cycle. We incorporate constant feedback loops to improve subsequent versions.
Automate Processes
We automate processes optimally to replicate consistently, reduce errors, and increase speed.
Identify Cases
We identify outlier corner cases upfront and address them expertly.
Modern Cloud Data Architecture Buildout
The Modern Cloud Data Architecture is Armeta‘s diagnostic model to build on-premises-to-cloud journeys for our clients to fully realize cloud capability. Using this model, we can pinpoint exactly where you are in the process and help design and build your enterprise’s secure, flexible data cloud architectures that promote the use of high-quality and accessible data that supports your business intelligence, data science, AI, and machine learning applications.
To learn more about how Armeta can design and build a scalable Modern Cloud Data Architecture for your enterprise, check out this white paper.
Modern Cloud Data Architecture
Data Ingestion & Pipelines Transformation
Data Ingestion Pipelines
We design and implement data pipelines to automate, standardize, and accelerate data ingestion from internal and external sources using modern tools, real-time or batch. We develop data pipeline architectures, workflows, and processes to ensure the optimization of value and use of our client’s data.
Data Transformation
Raw data from disparate, siloed sources must be cleansed, normalized, enhanced, and modeled for optimal usability. We help you transform raw data into actionable, decision-ready data for consumption by different data users and applications.