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Enabling the Modern Data Stack with the Unified Data Warehouse / Data Lake Architecture
Shyam Srinivasan, Senior Director and Head of Product Marketing, Trifacta
What is the modern data stack?
A modern data stack is an intelligent framework that brings together the essential elements of data ingestion, data warehousing (in the cloud), data engineering, and advanced data insights. Trifacta leads the charge with our recently announced data engineering cloud, where we deliver an intelligent, collaborative, visual solution to transform data, ensure quality, and automate data pipelines.
From ETL to ELT
A critical aspect of the modern data stack is to move from traditional ETL to modern ELT processes. ELT enables flexibility, speed, and scale, along with ease of use. Additionally, cloud warehouses as part of the ELT architecture facilitate higher processing power, autoscale for any size of data, and help achieve a lower total cost of ownership (TCO). With the data engineering cloud, Trifacta caters to the complete ELT architecture, with our foundation of playing a key role in “T” with our innovations in data transformation.
Trifacta’s mission is to enable data democratization with usable, trustworthy, and valuable data. We extend that mission to enable and complement current trends such as the unification of the modern data warehouse (DW) and the data lake (DL). With Trifacta, the key foundational layers of the unified DW/DL evolution such as connectivity to data storage, the move from ETL to ELT, automating data pipelines, and the security aspects of data governance are optimized for any scale, enhanced for high performance, and enabled for ease of use in the cloud. David Menninger, SVP & Research Director at Ventana Research says “By 2022, more than one-half of all organizations will use cloud-based technology as their primary data lake platform making it easier to adopt and scale operations as necessary.” This is in complete alignment with Trifacta as a cloud-based SaaS platform delivering useful data.
The open, intelligent, collaborative, and self-service data engineering cloud from Trifacta caters to a wide range of use cases, including those that are fundamental to the DW/DL architecture such as high-quality data transformation, advanced analytics, and line of business data marts. The blurring of boundaries with the modern DW/DL is a cornerstone of the Trifacta data engineering cloud, helping users discover and evaluate data, validate data quality, accelerate data transformation, and automate robust data pipelines.
Data Profiling and Adaptive Data Quality
The AI-assisted data transformation techniques from Trifacta offer visual guidance towards clean data with adaptive data quality rules. For data users who love to work with code, Trifacta provides flexibility using low code or leveraging custom code using SQL, Python, or a language of your choice. With interactive data exploration, Trifacta helps you understand your data at its most granular level. Outliers in data are automatically identified for follow-up actions, ensuring high-quality data is always delivered for advanced analytics. You can connect to any data source, choose the required transformations, and decide the scale for applications in advanced analytics and machine learning. Trifacta ensures data silos are unified or eliminated, and useful data is delivered with complete visibility and transparency, leading to data-driven decisions for superior business outcomes.
The unified DW/DL construct leverages the strengths of traditional ETL and the modern ELT processes that involve automation and orchestration of large-scale data pipelines. Trifacta caters to these requirements with quick and easy data connectivity, predictive data transformation, data profiling, and easy automation. You can build robust data pipelines with automated scheduling, leading to predictable, high-quality reporting. Trifacta delivers a seamless data engineering cloud providing a scalable solution across single, hybrid, and multi-cloud environments. This accelerates the expansion of the data footprint for useful data and analytics, catering to seasonal business requirements for the right outcomes.