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Hybrid transactional analytical processing

Hybrid transactional analytical processing

Traditionally, operational databases and platforms for data analysis have been two different worlds. This has come to be seen as natural, as after all the requirements for use cases that need immediate results and transactional integrity are very different from those that need complex analysis and long-running processing.

2 hours ago by in Data Management

Insight Platforms as a Service

Insight Platforms as a Service

Remember how we noted data is going the way of the cloud? While there are no signs of this slowing down, there's another interesting trend unraveling, the so-called Insight Platforms as a Service (IPaaS). The thinking behind this is simple: if your data is in the cloud anyway, why not use a platform that's also in the cloud to run analytics on them, and automate as much of the process as possible?

3 hours ago by in Data Management

Streaming becomes mainstream

Streaming becomes mainstream

The endless streams of data generated by applications lends its name to this paradigm, but also brings some hard to deal with requirements to the table: How do you deal with querying semantics and implementation when your data is not finite, what kind of processing can you do on such data, and how do you combine it with data from other sources or feed it to your machine learning pipelines, and do this at production scale?

3 hours ago by in Data Management

Quick glossary: Hybrid cloud

Quick glossary: Hybrid cloud

Hybrid cloud technology is becoming a standard model for many modern enterprises, but the terminology can be difficult to fathom. This glossary of 25 hybrid cloud terms will help you gain an understanding...

from Tech Pro Research

The machine learning feedback loop

The machine learning feedback loop

The pace of change is catalyzed and accelerated at large by data itself, in a self-fulfilling prophecy of sorts: data-driven product -> more data -> better insights -> more profit -> more investment -> better product -> more data. So while some are still struggling to deal with basic issues related to data collection and storage, governance, security, organizational culture, and skillset, others are more concerned with the higher end of the big data hierarchy of needs.

3 hours ago by in Data Management

Moving up the analytics stack

Moving up the analytics stack

As descriptive and diagnostic analytics are getting commoditized, we are moving up the stack towards predictive and prescriptive analytics. Predictive analytics is about being able to forecast what's coming next based on what's happened so far, while prescriptive analytics is about taking the right course of action to make a desirable outcome happen.

3 hours ago by in Data Management

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