We use various programming languages in our solutions at data processing, real-time data ingestion, developing front-end and back-end applications along with data tools and techs.
We design relational database models for Web and Mobile applications with 3rd NF and BCNF. We also design data warehouse layered structure in 3rd NF, Star or Snowflake schema using Kimball Model ( Dimensional Model ) with Change Data Capture (CDC) and Slowly Change Dimension ( SCD ) types implementation using popular Data Modeller tools. In data warehousing architectural perspective, we may apply Enterprise Data Warehouse ( EDW ) or Data Vault approach in database design depending on the requirements and data sources.
We use different type of databases in our solutions regarding nature of the requirements and decide how to store, process and retrieve of data in effective and efficient way.
Basically, we categorise databases in 3 classes.
We deliver comprehensive dashboards using the most recent and popular Data Visualisation tools We have extensive experience on how to present data for business users via BI tool and visualise data on dashboards in the best manner.
We effectively configure and execute the most recent and popular DevOps tools in our projects to reduce costs drastically using Continuous Improvement and Continues Delivery ( CI/CD ) methodologies. We use containerization approaches as a most efficient way to build servers and scale them up and down when needed.
Ingest and unify data from multiple sources, then pipeline it to target systems, always ensuring data integrity. Control data movement and data transformation, from source to target systems, code-free. Our Data Engineers can develop Data Pipelines using any of the ETL or ELT tool depending on tech stack in our customers’ projects.
We focus on real time data replication, ingestion and processing in the leader platforms and techs. Basically, we design data streams with batch processing as a backbone of the real time decision support and monitoring systems. We deliver End to End Data Streaming along with IoT ( Internet of Things ) solutions.
We define data patterns, extract business value, train & deploy ML models. We have extensive experience on ML algorithms as well as AI services on cloud platforms. We mostly use Spark and Python Machine Learning libraries in our project.
We have a great deal of experience on the latest Big Data techs. Basically, Ingestion of unstructured, semi-structured and structured data from different type of source systems in various forms and frequencies, storing them in the distributed and fault-tolerant file systems. Curation, Exploitation of data on Big Data Platforms.
Data Management
Data Science
Platform Engineering
Technologies
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