Data Engineering
Data Engineering helps you in collecting and validating your data
Data engineering focuses on practical applications of data collection and analysis. For all the work that data scientists do to answer questions using large sets of information, there have to be mechanisms for collecting and validating that information.
Data Engineers are there where the rubber meets the road, focusing on the applications and collecting of Big Data. Through data engineering, mechanisms are put in place to apply Big Data into real-world operations.
How can data engineering help you?
distributed processing
Set up a distributed processing framework with Apache Spark enabling you to split processes and run them in parallel
stream processing
Build a continuous processing framework with Apache Kafka for the processing of real-time data as it is produced and received.
job processing
Execute processing jobs by orchestrating them between nodes and executors to complete complicated analytical workloads
Scheduling & orchestration
Schedule jobs in your data pipeline and manage dependencies and errors with Apache NiFi as a wider dataflow solution
data governance
Build a data governance program to focus on data definitions and standards, quality, security, privacy, architecture and integration
cloud data platforms
Leverage the flexibility of AWS and Azure Cloud to build fully interoperable, cost-effective and expansive data platforms
hybrid cloud solutions
Keep your on-premise data infrastructure and mix it with the computing and storage services of AWS and Azure Cloud
etl pipelines
Build ETL pipelines to extract data from an input source, transform the data and load it into an output destination
Test automation
Build automated tests in your data pipelines to validate data flows and catch costly prodcution errors
This is just a grasp out of many possible fields where Data Engineering can offer tremendous value.
Curious what possibilities lie in your organization?
data engineering technology stack
Over the past few years, many new technologies have made their advances in the data processing world. At Infofarm, we use these technologies to build highly performant and scalable data platforms for our partners.
