Data Engineering
Data engineering is the complex task of making raw data usable to data scientists and groups within an organization. Data engineering encompasses numerous specialties of data science. At FuturisTech, in addition to making data accessible, our data engineers create raw data analyses to provide predictive models and show trends for the short- and long-term.
Apache Airflow
Apache Airflow is used for the scheduling and orchestration of data pipelines or workflows. Our team uses Apache Airflow for sequencing, coordination, scheduling, and managing complex data pipelines from diverse sources.
Pyspark
PySpark is an open source, distributed computing framework and set of libraries for real-time, large-scale data processing. Our experts use PySpark which brings robust and cost-effective ways to run machine learning applications on billions and trillions of data on distributed clusters 100 times faster than the traditional python applications.
Pyspark
PySpark is an open source, distributed computing framework and set of libraries for real-time, large-scale data processing. Our experts use PySpark which brings robust and cost-effective ways to run machine learning applications on billions and trillions of data on distributed clusters 100 times faster than the traditional python applications.
Databricks
Our team at Futuristech is expert in using Databricks for building, testing, and deploying machine learning and analytics applications to help achieve better business outcomes.