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ETL 2.0 is about to redefine the way organizations perform data integration - empowering you to leverage Big Data for competitive advantage and achieve strategic business objectives…while lowering the total cost of owning and maintaining your data integration environment.
The “T” Has Disappeared From Today’s ETL.
Data Integration and ETL tools have historically focused on expanding functionality, neglecting two critical success factors: ease-of-use and high performance at scale. As IT organizations confront the accelerating volume, variety and velocity of data – aka “Big Data” -- they are forced to turn to costly and inefficient workarounds to overcome their performance challenges:
- Tuning requires significant IT staff hours and highly-skilled resources
- Adding hardware involves significant capital as well as operational costs to deliver marginal performance improvements
- Pushing transformations to the database and hand-coding SQL scripts increase complexity, jeopardize data lineage, and reduce business agility while increasing database costs
The “T” has disappeared from today’s ETL. In fact, less than one-third of IT professionals say they process any transformations inside their ETL tools. What is left is a complex web of transformations happening all over the place – a nightmare to maintain, extend and govern.
ETL 2.0: Everything you need for fast, efficient, simple, cost-effective Data Integration. Not more. Not less.
ETL 2.0 delivers everything you need to significantly lower the cost and complexity of today’s data integration environments. ETL 2.0 is a new approach to data integration that brings all data transformations into a high-performance, in-memory ETL engine, minimizing the need for staging data and/or manually pushing transformations down to the database.
- Eliminate staging and off-load database capacity. Read, transform and load data at maximum I/O rates. Transformations are processed in-memory on commodity hardware, accelerating performance while eliminating the need for extra database capacity.
- Deliver maximum performance and efficiency with no tuning required. Traditional data integration is manual and static and, therefore, uses resources sub-optimally. ETL 2.0 delivers maximum performance through a dynamic ETL engine that adapts in real time to changing system conditions. It even provides automatic pipelining and parallelism.
- Connect business users with their data. ETL 2.0 uses collaboration and agile development frameworks to bring the business user closer to their data. Ease-of-use and automatic fine-tuning also mean IT can focus more time addressing the growing business demands for information and less time on ongoing maintenance.
- Accelerate Hadoop deployments. ETL 2.0 leverages and extends Big Data frameworks such as Hadoop, facilitating development and accelerating performance of MapReduce jobs.
- Reduce TCO. Up to 10x faster performance, 75% less CPU utilization and 10x less storage translates into significant savings while still exceeding SLAs. Automatic tuning engines mean fewer IT staff hours to maintain existing DI environment.
In the end - ETL 2.0 is about re-defining the way organizations perform data integration - allowing them to leverage Big Data for competitive advantage. ETL 2.0 is about enabling companies to achieve their strategic business objectives while lowering the total cost of owning and maintaining their data integration environments.