Slideshow Top 5 Roadblocks to Using a Data Platform

Published
  • October 13 2016, 6:30am EDT
8 Images Total

Top 5 Roadblocks to Using a Data Platform

Organizations are increasingly looking to simplify their data architecture and decrease the time to value from data. But there are a number of challenges in selecting the right data management platform to manage multiple data streams. Here are the top 5 roadblocks.

Challenges and Opportunities

“Increasingly, enterprises are exploring ways to simplify their data management architecture while optimizing decision-making processes in real-time,” explains Julie Lockner, of the Data Platforms division at InterSystems. “This requires bringing analytics from multiple data sources to the point of when transactions and trades are made at scale. But current data architectures unnecessarily separate analytics from transaction processing and structured from unstructured analytics. This introduces delays, prevents business agility and increases infrastructure complexity – to name a few. The bottom line is that businesses need insight at the moment of the transaction in order to remain competitive. But choosing a data platform to help manage different streams can be challenging.” Following are the top five roadblocks facing enterprises looking to use a data platform.

Content Continues Below


Reason #1 – Demands of New Functionality

Each new project requires new functionality, which means yet another database or open source project, further complicating their data management architecture.

Reason #2 – Data Integration and Interoperability

Each new database requires additional data integration spaghetti code.

Reason #3 – Skills Gap

In the ever-evolving world of technology, each new platform (and shiny penny) requires yet another new skillset, and finding people with relevant, up-to-date skills is becoming increasingly challenging.

Content Continues Below


Reason #4 – Updates

Each new data requirement means massive code changes, updates to that spaghetti integration code and overhauls to change management and project management – not to mention lack of control and timing with open source data management projects.

Reason #5 – Keeping Up With Standards

Enterprises need to keep up with the latest database standards, which only compound the challenges further.

So, what do you look for in a data platform?

Lessons learned say that in order to avoid these challenges, when it comes time to actually select a data platform, what should you look for? A few considerations: •Interoperability with existing data silos – avoid custom coding to make data sets work together•High-performance transaction processing, both simple and complex•Inline analytics at the point of the transaction•Inherent scalability, this is a given•Proven and reliable – this goes for both the company and the technology•Simple, since architecture shouldn’t be more complex than it has to be•Flexible, in order to prevent future data islands and allow for multiple use cases on the same platform, multi-model data platforms are well suited here• Enterprise grade: HA, security, sophisticated administration and system management•High-quality customer support: the experience makes a difference