6 Ways to Increase Data Engineering Productivity
Target: Everett, the Data Engineer
What is Data Engineering?
Data engineering is the design, testing, and deployment of data pipelines from acquisition to analysis and action. The work of the data engineer includes finding, capturing, ingesting, cleansing, transforming, integrating, profiling, understanding, analyzing, and communicating data, as well as delivering insight to decision-makers.
What consumes data engineers’ time?
Most data engineers spend far too much time looking for the right data, preparing the data for analysis, and switching back and forth between different tools because there isn’t a single tool that manages the entire data pipeline from end to end.
What is unified data orchestration?
A unified data orchestration platform provides data engineers with everything they need to design, test, automate, and deploy data pipelines all the way from acquisition to analysis and action. Without changing platforms, the data engineer can find, capture, ingest, cleanse, transform, integrate, profile, understand, analyze, and communicate data, as well as deliver insight to decision-makers.
By implementing a unified data orchestration platform, data engineers can increase their productivity in 6 ways.
NUMBER ONE: Make it simple to find data and analytics.
With unified data orchestration, finding data becomes simple because the data and analytics are centralized. Especially with rich, searchable metadata data, engineers quickly find what they need, and they can focus more of their time and effort on understanding and analysis.
NUMBER TWO: Accelerate data pipeline design and deployment with built-in data engineering.
With unified data orchestration, platforms that are designed with built-in data engineering features like no-code or low-code, drag-and-drop interfaces can speed up production and make better use of data engineering resources. When acceleration features are built in from acquisition through debugging, testing, and deployment into production, data engineers can expect maximum acceleration.
NUMBER THREE: Streamline data preparation with automation and recommendations.
With unified data orchestration, a metadata-driven approach allows users to build automation and create recommendation engines for every step of data preparation and yet analysis. Being built-in means that data professionals are far more likely to save the time and effort they normally spend testing their hypotheses to arrive at the right next step.
NUMBER FOUR: Leverage and reuse analytical excellence.
With unified data orchestration, existing code is up to 80% reusable for future migrations, maximizing the reuse of analytics and fueling excellence through continuous improvement. This amounts to a potential 4X increase in productivity for all migrations. This benefit is further multiplied by the ability to push the processing of data to the most suitable platform, all within the same pipeline.
NUMBER FIVE: Tie insight delivery to the end of data pipelines.
With unified data orchestration, data professionals work with business users to make sure that the business utilizes their work. Connecting insight delivery to the data pipeline reduces the time normally spent on last-mile decision enablement by familiarizing data professionals with the business and business professionals with the data.
NUMBER SIX: Unify data pipeline management from acquisition to insight.
With unified data orchestration, typical data handoff times can be reduced to almost nothing. Unification of data management allows the data engineer to select the platform that is best for every action taken against the data and manage it all from one single control plane. By eliminating the time it takes to move data from one platform to another and the effort it takes to work with data in different tools, the data engineer becomes an innovator.
Multiplying Data and Analytics Value
Unified Data Orchestration frees data engineers from wasted time on menial tasks, and organizations benefit from data engineering productivity in three ways: innovation, acceleration, and optimization. PurpleCube AI was designed from the ground up to make the life of the data engineer more productive. To learn more about PurpleCube AI, book a personalized demo, or start your free trial, contact us at contact@purplecube.ai or talk to us on our website at www.purplecube.ai.
