Challenges of cloud analytics: Trends and Technology

The need for quick and easy access to the successful analytics has never been at it best than it is today. Luckily, the cloud processing tends to hold promise to make analytics somehow more transparent and omnipresent than ever before. However, a huge number of challenges still also exist that prevents the growth and widespread adoption of the cloud analytics by various organizations like IBM I Cloud and many more.

Broadly speaking, the modern cloud deployments do not suffer from factors like lack of hardware or the availability of resources, but in fact, these are compromised due to the poor architecture of the software and design management. Several companies who have adopted cloud analytics have experienced themselves locked into poorly functioning in terms of cloud environments, this is due to the reason that they did not ask the right type of question that is directly related to the software architectures and connected dependencies.

Below are the most important issues that the cloud analytics processing systems must address in order to build a highly-successful platform are:

  • Creating a safe and secure platform.
  • Optimizing work output through the support of other available processing paradigms.
  • Making sure of high availability despite regular maintenance.
  • Track and chargeback employees for units of work.
  • A transparent TCO or total cost of ownership- what is generally a concern as hidden costs.

Indirectly the above-mentioned challenges speak for the maturity in terms of any software or application systems and tend to reflect the amount of design effort that has been executed by a specific vendor. therefore, when talking about data processing systems, IBM I Cloud analytics allows thinking about the long-term adoption and the related potential liabilities. Talking about security systems, since the cloud supporters do not want any private information to get into any kind of limelight or data theft, the cloud-based software must try to support the built-in flexibilities that enable it to work very easily. Also, the last and the final hurdle for the cloud analytics is being able to assess the total ownership costs. Several vendors available online offer services that appear cheap at the beginning until you really want to use your outcomes.  Cloud analytics must be able to compartmentalize the costs involved in the process so that no problems are generated later on. By following these potential cloud users require understanding whether the use of the technology is cheaper than using any other software on a specific network or on a server.





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