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Cloud computing took seed when a quintillion bytes of data required secure storage. This is referred to as simply Big Data. Big Data and Cloud computing logically complement each other. However, enterprises are still sceptical in migrating their data analytics to the cloud, also known as Cloud Analytics.

What is Cloud Analytics?

This term refers to technological and analytical tools and methods specifically designed to analyze information from massive data. Data analysis and related services are performed on a public or a private cloud.

A recent survey of senior technology leaders suggests that there are some major barriers which conflict with the idea of deploying Cloud Analytics. It can be troublesome to manage and secure the essence of the data rather than just stacking it.

Here are 5 major barriers to Cloud Analytics

Security: As highlighted in the survey result, the security of data analytics in the public cloud is a major concern. Approx. 50% technology leaders consider security as the prime reason for not choosing public cloud for analytics. Interestingly, 46% leaders say that data analytics in the public cloud ensures higher levels of security. This remains a topic of debate among analysts and business owners.

Technological disconnect: Organizations are not ready to completely trust technological advancements. While people who are actually using Cloud Analytics suggest that public cloud makes it easier to use innovative analytics technology. 49% of technology leaders said that technological disconnect and low performance was preventing them from deploying cloud analytics.

Regulatory Compliance: With the advent of EU GDPR, there are strict laws for storing data in the public cloud. The strong data privacy laws are making cloud analytics tougher and this is a big reason for enterprises to not go this way. Interestingly, research firm IDC has predicted, “By the end of 2019, 15 percent of small and midsize banks will have implemented cloud-based compliance analytics platforms and data solutions to improve KYC [Know Your Customer], CDD [Customer Due Diligence] and AML [Anti-Money Laundering] compliance.”

Lack of Trust in Cloud: 32% survey respondents have a lack of trust in the Cloud for moving analytics to a public cloud environment. Traditional IT professionals did not have experience of migrating data to the cloud as they are used to work with physical infrastructure. Also, Cloud security breach cases have strengthened their reluctance to use Cloud analytics.

Integration of Legacy systems and Cloud Applications: According to 30% technology, it can be very complicated to connect cloud analytics to legacy data centre systems, such as in-house SAN and NAS storage. While it is extremely easy to connect analytics to cloud storage. Hence, integration can be seen as a significant challenge.

These technical and cultural hindrances are challenges that organizations are working to overcome in order to make cloud analytics viable.

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