AI & DATA ANALYTICS
THE TREND NO CODE / LOW CODE
It ’ s an appealing prospect , but no code / low code ( NCLC ) is big business , particularly when it comes to the swathes of middleranking companies who can ’ t invest in expensive integrations that require teams of engineers writing bespoke code . The theory is simple : NCLC is less customisable than custom development , but it can be tuned by the relative layman to produce comparable results to the more costly solutions available to those with deeper pockets and more complicated needs . Perversely for something that manages to work almost magically , it ’ s also prized for its lack of smoke-and-mirrors coding which appeals to technologically naive managers .
THE SOFTWARE BUBBLE
When it comes to NCLC , Bubble has it locked . An intuitive drag-and-drop interface , twinned with basic logic patterns makes producing HTML more like a computer game than a development task . For the doubters , Bubble has a tool on its website allowing the casual browser to edit the company ’ s own homepage . There ’ s a huge amount of customisation available and Bubble will also host and deploy , eliminating the need for further partners .
THE TREND DATA STREAMING
Stop thinking about Netflix . We ’ re talking about data streaming which … okay , Netflix is , but in a limited way . Data streaming is becoming – and is about to become even more – important , with data gathering in businesses a core part of the DX strategy . But streamed data isn ’ t easy . There ’ s bounded data , which exists in totality and should only be computed once it has all been gathered , and unbounded data , which continues to collect in a theoretically endless stream . Those two entities need to be managed alongside each other , as well as balancing computational capacity in a sensible manner .
THE SOFTWARE APACHE FLINK
Flink is difficult to describe , either as an application , or as a runtime or as an architecture . But its massive computational brain will take multiple data streams and organise them into workable data snapshots – easier said than done , hence the complexity . Its functionality is also critical for automation of event-driven applications , where activity is triggered by a certain data state . The Apache Foundation ’ s Spark should also get an honourable mention in large-scale data processing .
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