Automate Migration of Informatica to Spark on the Cloud with StreamAnalytix
Enterprises extract, transform, and load (ETL) data from multiple sources and applications to create a single data repository, a.k.a. data warehouse. ETL allows enterprises to effectively design and create an environment to mine and analyse data for making informed decisions. It isolates data from transactional systems, which ensures business-as-usual while data is analysed in an optimized environment.
However, traditional ETL tools have many limitations. They are time consuming, expensive and error-prone to use, and lack the scalability, agility, and integration capabilities needed to succeed in today’s fast-paced business landscape.
To address these challenges, data-driven enterprises are increasingly shifting to next-generation ETL tools, which can run workloads on-premise and in the cloud. Unlike traditional ETL tools, these modern tools can extract value from extensive datasets. They also leverage the cloud without compromising security and provide better value for money.
Driving speed and agility with smart ETL tools
While next-generation ETL tools offer many attractive business benefits, the journey of modernization is not easy. A successful migration involves seamlessly porting existing ETL workflows to a new environment within the stipulated budget and time, without impacting business processes. However, ready-to-use, low code tools can help you effortlessly migrate ETL workloads to the cloud, without having to rebuild, thereby saving time, effort, and money. Let’s take a closer look at one of the industry’s most powerful tools for ETL migration.
Impetus’ self-service analytics, ETL, and ML platform, StreamAnalytix enables you to assess your existing ETL workloads and swiftly transform them to visual Spark. With StreamAnalytix’s automatic migration agent, you can preserve your structure, logic, and execution rules, and migrate ETL workflows to a new environment in 3 easy steps:
· Assessment: Existing workloads are assessed for complexity, size, and compatibility operators
· Migration: Traditional ETL workloads are transformed into Spark-based distributed workflows
· Validation: Ensuring successful migration of existing workloads without data loss
The StreamAnalytix advantage
StreamAnalytix’s migration agent drastically reduces the amount of time ETL practitioners spend on performing repetitive tasks across key areas like data cleansing, coding, versioning, workflow orchestration, and others. It provides a far more comprehensive environment for your migration compared to traditional platforms. Users can easily onboard new sources/ targets and seamlessly manage, monitor, and optimize converted workloads. The platform’s power-packed features provide unparalleled scalability and extensibility to drive strategic business benefits:
1. Massively reduce migration efforts: Ensure automated translation with an innovative engine
2. Business continuity: Business-as-usual on existing systems while validating new workflows
3. In-built assessment: Prioritize transformation candidates with an in-built assessment
4. Cost-effective: Reduced costs with significantly higher ROI
5. Visually equivalent modern platform: Get a near-identical visual experience of all your legacy ETL workloads on Spark
6. Future-ready: Build a future-ready competitive enterprise by on-boarding to a cutting-edge platform
StreamAnalytix enables Fortune 500 companies to build and operationalize big data applications faster across industries, data formats, and use cases. As a unified platform for stream and batch processing with an intuitive drag-and-drop visual interface and advanced operators to enrich pipelines, StreamAnalytix is one of the most advanced ETL migration tools available today. To learn more, read this white paper.