FEATURE : ANALYTICS
• Company culture can be a barrier because companies get trapped into just doing things the way they always have been , and they are reluctant to try new approaches
• An organization may lack a flexible architecture to experiment with
• Or they may lack vision or support from the business to identify areas of possible improvement
What are the dangers of IT leaders deprioritizing data analytics initiatives ?
IT leaders often think of analytics as a ‘ nice-to-have ’ technology and frequently put it on the back burner while they focus on other mission-critical objectives and making sure the lights stay on . But in today ’ s competitive landscape , the use of forward-looking analytics is now mission-critical .
If you aren ’ t getting more from your data , you are falling behind your competition , and you may find your company obsolete in the near future .
How can companies break down data silos to deliver a greater degree of visibility ?
Data lakes have proven to be the go-to strategy for eliminating data silos . They provide a central location for all disparate data where you can easily provide the appropriate security and governance protocols in place .
Then , that data can be easily combined and transformed into structures that can be consumed via a myriad of analytics services – as well as traditional business intelligence consumption .
Are there any tools and systems available that successfully take the burden of data management off busy IT teams ?
Cloud analytics technologies , in general , can help remove the burden from IT in multiple ways , including :
• Not having to worry about managing the infrastructure of physical servers
• Serverless analytics technology can remove on-going administration of operating systems and applications
• Having data in a data lake can ease security and governance controls of the data , putting the control in one place rather than maintaining from all the separate systems
• Data in a lake allows for more self-service and consumption of the data itself
• Many ML and AI services have been greatly simplified so that you don ’ t require specialists or data scientists to obtain the insights
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