What is a data pipeline?
A data pipeline is a series of steps that are performed on data. These steps can include transforming, cleansing, aggregating, and cleaning the data to make it suitable for analysis or modeling purposes.
Different types of pipelines
Balancing IT users and data analysts with governed analytics and discovery
Benefits of using a data pipeline
Data pipeline components
Data pipelines can be composed of various types of components which have their technical requirements and challenges to overcome when being implemented. A general structure for a typical data pipeline might look something like this:
Data pipeline tools and infrastructure
A data pipeline is a set of tools and components that help you to effectively manage datasets and turn them into actionable insights. The ultimate goal is to use the information found within these datasets to make better decisions about business direction. A successful data pipeline can be divided up into nine main parts:
How Lyftrondata helps to transform your Snowflake journey
Lyftrondata columnar ANSI SQL pipeline for instant data access
Many leading companies have invested millions of dollars building data pipelines manually but unfortunately were unable to reap the ROI. The result has mostly been a complex data-driven ecosystem that requires a lot of people, time, and money to maintain.
Lyftrondata removes all such distractions with the Columnar SQL data pipeline that supplies businesses with a steady stream of integrated, consistent data for exploration, analysis, and decision making. Users can access all the data from different regions in a data hub instantly and migrate from legacy databases to a modern data warehouse without worrying about coding data pipelines manually.
Lyftrondata’s columnar pipeline unifies all data sources to a single format and loads the data to a target data warehouse for the use of analytics and BI tools. Avoid re-inventing the wheel of building pipelines manually, use Lyftrondata’s automated pipeline to make the right data available at the right time.
How it works
Lyftrondata’s columnar pipeline allows users to process and load events from multiple sources to target data warehouses via simple commands. All data pipelines in Lyftrondata are defined in SQL. This concept enables scripting all data pipelines, and therefore there’s no need to build them manually. Data pipelines could be automatically scripted instead of building them manually in a visual designer. Get ensured that you can sync and access your real-time data in sub-seconds using any BI tool you like.