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The Cloud Analytics market globally has been projected to grow by $39.1 billion, with a compound growth rate of 7.6%. While many companies view these services as economical, they also choose cloud analytics because it makes it easier for them to handle and process massive volumes of data from different sources. It offers real-time information while providing excellent security. So, it comes as no surprise when we read that 91% of the industry say that analytics should be moved to the cloud at a faster rate.

While many analytics companies look to adopt cloud and search for the cheapest cloud platform or a way to optimize their network costs, they still battle a lot of problems:

Security is a significant factor when it comes to cloud analytics and computing challenges. Security has been the most significant concern because it involves a lot of data. Analytics deals with a lot of private data, so the cloud-based software that is used should have built-in flexibilities that allow it to work efficiently with popular security tools. Security is such a big concern that software vendors and organizations have to always be on the lookout for the latest trends and new designs for their software to work with different security protocols.

Finding an application which can be efficiently implemented and functions properly is one of the most important challenges when it comes to cloud analytics. The software has to run on almost all the operating systems or hardware configurations.

Ideally, the analytics software should not be operating under a predefined processing strategy, and it should be capable enough to distinguish between different processing scenarios and dynamically choose how the analytics should be executed without moving a lot of data around. This is not something that is achieved easily, and a lot of organizations struggle to find an appropriate software solution.

IT departments in an organization generally advise business users not to install software they cannot control or support. Also, most apps which are critical to the process, need 100% uptime, which gives no scope for the server that is being shut down to replace or upgrade it. Maintenance can be made more accessible by building redundancies into the software so that duplication of control and processing exists.

Companies nowadays struggle with controlling their cloud spending. In fact, controlling spending is as important to them as cloud security. Nowadays, the mistake of cloud spending is committed not only by beginners, but also by companies who have been using cloud services for a long time. It was estimated in a report that in the year 2020, wasted cloud spending could exceed $17.6 billion. As cloud computing grows, companies are still struggling to manage their cloud spending.

Many online vendors offer services which appear cheap at first, but when it comes to using the analytics results, the costs do not seem reasonable anymore. What is presented as a low-cost solution at the front end represents accumulated costs for data storage, bandwidth, database access, numbers of users, memory allocations, row-level scoring, and many tasks along with other resources.

To assess the profitability, the entire lifecycle of the analytics has to be quantified and evaluated, so that hidden costs can be avoided. This will allow cloud users to know whether the technology they are using is cheaper than using software on a server.

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Link:
Five Of The Biggest Challenges Faced By Cloud Analytics In 2020 - Analytics India Magazine