The World Back Then
Think about where we’ve come in the last twenty years. When data integration software was just emerging on the scene in the early-to-mid nineties, the sources for data were limited. Most of the data came from mainframes, operational systems that were built on relational databases, and data service providers. The targets were primarily data warehouses and data marts, with an occasional loop back to operational systems for closed loop Business Intelligence. It is no surprise that most of the prevailing data integration software we use today were created in a vastly different world with very different demands.Download PDF
The Paradigm Shift
There is a major paradigm shift taking place in the field of data and information management. Every day, there are massive amounts of new data being created. Unlike ever before, this data is moving fluidly in many directions; from on-premises to the cloud, cloud to on premises, and people are accessing data from all over the place. The old paradigms of data integration have become unsuitable in this new data landscape. It is time for a paradigm shift. Now is the time to make the move to modern data integration.
New Challenges Require New Approaches
Many of the legacy integration tools have been re-engineered to handle new kinds of data, but there are only so many add-ons you can try to attach to old technology. Multiple connectors and modules bring even more complexity into an already complex problem. Trying to bring an “old world” tool into this new landscape requires massive amounts of effort for the growing mix of data types, sources, and API’s.
Hadoop has become a part of our data ecosystem and it has to live within the existing corporate and internet environment. As a result, some of the greatest challenges involve moving data into and out of Hadoop. Hadoop is both a landing spot for massive data coming in and a provisioning platform for processed data coming out.
Look Beyond Modernization
Technology is changing, however the business requirements are not. With Diyotta, design your data movement, blending and transforming with complete transparency and unlimited reusability. Accelerate the execution of your ongoing data enrichment and analysis by deploying agents that deliver instructions and optimize actions. Let Diyotta help you adapt your environments to meet the ever-changing business and technical demands; migrating data from platform to platform effortlessly.
Five Principles Modern Data Integration
Fully Leverage All Platforms Based On What They Do Well
Get better leverage of your investment in platforms
Move data point-to-point, at the right time
Move less data and avoid single server and network bottlenecks
Manage all of the business rules and data logic centrally
Maximize reuse and drive both transparency and governance