We hold strong partnerships with Amazon, Google, Microsoft, and other other leaders to keep pace with the technological advancements and the evolution of the big data analytics landscape.
Our developers are rigorously trained and certified by international organizations before joining client projects.
We designed and implemented big data solutions for various industries IOT, clean energy, retail, healthcare, and manufacturing.
We are able to master technologies of the whole development cycle of a Big Data project from distributed storage (Hadoop, S3, Azure Blob), database management (mongoDB, Amazon DynamoDB, Amazon Redshift, Hive), data flow (Airflow), big data processing (Kafka, Spark, MapReduce), to machine learning (Keras, PyTorch, Caffe, TesorFlow)
Big data implementation strategies, recommendations on data quality management, big data solution architecture + a suggestion of an optimal technology stack, and POC
Big data needs analysis, Big data solution development (a data lake, DWH, ETL/ELT setup, data analysis (SQL and NoSQL), big data reporting and dashboarding), Setup of big data governance procedures (big data quality, security, etc.), and ML models development
Big data solution administration, Big data cleaning, Big data backup and recovery, Big data solution health checks, Big data solution performance monitoring and troubleshooting
Big data solution infrastructure setup and support, Big data extraction and management, ML model development and tuning, and Predefined and ad hoc reports
Success is no easy accomplishment, but with a trusted partner and an effective collaboration, success comes to you without harsh tries. With us!
Veritone uses massive real-time weather, demand, and device data to predict and optimize energy supply mix for maximum profitability and ideal grid utilization, which power next generation smart grids by continuously collecting and synthesizing overwhelming amounts of data to make timely decisions on how best to allocate new and old energy resources.View more
Aeris manages more than two millions of devices, which generate huge amounts of data that need to be analyzed to optimize cost and energy. Google Cloud, Apache Airflow and BigQuery are employed to process and provide insights for device usage and optimization. For example, unused devices will be turned off to save energy and cost.View more