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Top 6 Barriers to Cloud Analytics

  • Top 6 Barriers to Cloud Analytics

    Top 6 Barriers to Cloud Analytics
    Enterprises want to run their big analytics in the public cloud, but technical, cultural and strategic barriers are standing in their way.
  • 1. Security

    Security 50%

    Since the dawn of cloud computing, security has been the top concern of organizations that are considering the public cloud, and that remains true in this survey. Interestingly, 50 percent of technology leaders said that security concerns are preventing them from deploying cloud analytics, while 46 percent said that moving big data analytics to the cloud would improve security.

    Analysts have noted the same disconnect among their clients. "Security continues to be the most commonly cited reason for avoiding the use of public cloud," Jay Heiser, research vice president at Gartner, stated in a press release. "Yet paradoxically, the organizations already using the public cloud consider security to be one of the primary benefits."

    Perhaps some day the majority of organizations will feel that public cloud environments match or exceed the security of their in-house data centers, but clearly that day hasn't yet arrived. And the steady drumbeat of high-profile companies experiencing data breaches isn't helping to allay security concerns.

  • 2. Immature/low-performing technology

    Immature/low-performing technology 49%

    In the Teradata survey, 49 percent of technology leaders said that low-performing technology was preventing them from deploying cloud analytics. Again, the report highlights a bit of a disconnect as 44 percent of respondents expected better performance from cloud-based analytics, and 35 percent said that the public cloud would give them easier access to analytics technologies.

    Again, this may be an area where people who are actually using cloud analytics have a different opinion than organizations that are still investigating the technology. After all, many analysts say the public cloud makes it much easier to use innovative analytics technology like machine learning and deep learning. It's also possible that the low-performing technology that is preventing some organizations from adopting the cloud is the legacy infrastructure in their data centers that doesn't integrate well with the cloud.

  • 3. Regulatory compliance

    Regulatory compliance 35%

    The upcoming implementation of the European Union's General Data Protection Regulation (GDPR) has refocused attention on compliance, particularly complying with data privacy laws. And storing data in the public cloud can make it particularly tricky to adhere to international laws. That makes it somewhat unsurprising that 35 percent of large organizations said that regulatory compliance was a major barrier to cloud analytics.

    In an interesting twist, some organizations may actually use cloud analytics to help them improve their compliance posture. 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."

  • 4. Lack of trust in the cloud

    Lack of trust 32%

    Thirty-two percent of the respondents to the Teradata survey said that a lack of trust in the cloud has been a barrier to moving big data analytics to a public cloud environment. While some people dismiss those with these concerns as "server huggers," cloud migration represents a very significant cultural shift, particularly for IT professionals who are used to being able to touch infrastructure physically. Stories about cloud outages and security breaches have leant weight to those fears, making this sort of cultural barrier one of the more difficult to overcome when adopting cloud analytics.

  • 5. Connecting legacy systems with cloud applications

    legacy systems 30%

    As 30 percent of the survey respondents noted, connecting cloud analytics to other cloud-based systems, such as cloud storage, is extremely easy. However, connecting cloud analytics to legacy data center systems, such as in-house SAN and NAS storage, can be much more complicated. For 30 percent of the large enterprises surveyed, integration was enough of a challenge that they named it as a barrier.

    Some analysts predict that legacy integration will become less of an issue as organizations move more data storage to the public cloud. "Where the analytics workloads run is based a lot on where the data is generated and stored. Today, most public cloud workloads are new, and we won't see the percentage of cloud use rise until legacy workloads migrate en masse," said Jim Hare, research vice president at Gartner. "This scenario will happen eventually, but given the extent to which modern data and analytics efforts overwhelmingly use traditional data types stored on-premise, this shift will likely take several years to complete."

  • 6. Lack of in-house skills

    in-house skills 29%

    Many organizations also find it difficult to hire professionals with the requisite skills for running big data analytics in the cloud. In fact, 29 percent of those surveyed pointed to a lack of in-house skills as a barrier. Data scientists and developers continue to be among the most highly paid IT professionals, and those with public cloud expertise are in even greater demand.

    Many vendors are responding by increasing the self-service capabilities of their cloud analytics products, allowing regular business users to run the reports they need to do their jobs. In addition, many educational institutions and training providers have added courses in cloud computing and big data analytics.

  • 1 of

Top 6 Barriers to Cloud Analytics

  • 1 of
  • Top 6 Barriers to Cloud Analytics

    Top 6 Barriers to Cloud Analytics

    Enterprises want to run their big analytics in the public cloud, but technical, cultural and strategic barriers are standing in their way.
  • Security 50%

    1. Security

    Since the dawn of cloud computing, security has been the top concern of organizations that are considering the public cloud, and that remains true in this survey. Interestingly, 50 percent of technology leaders said that security concerns are preventing them from deploying cloud analytics, while 46 percent said that moving big data analytics to the cloud would improve security.

    Analysts have noted the same disconnect among their clients. "Security continues to be the most commonly cited reason for avoiding the use of public cloud," Jay Heiser, research vice president at Gartner, stated in a press release. "Yet paradoxically, the organizations already using the public cloud consider security to be one of the primary benefits."

    Perhaps some day the majority of organizations will feel that public cloud environments match or exceed the security of their in-house data centers, but clearly that day hasn't yet arrived. And the steady drumbeat of high-profile companies experiencing data breaches isn't helping to allay security concerns.

  • Immature/low-performing technology 49%

    2. Immature/low-performing technology

    In the Teradata survey, 49 percent of technology leaders said that low-performing technology was preventing them from deploying cloud analytics. Again, the report highlights a bit of a disconnect as 44 percent of respondents expected better performance from cloud-based analytics, and 35 percent said that the public cloud would give them easier access to analytics technologies.

    Again, this may be an area where people who are actually using cloud analytics have a different opinion than organizations that are still investigating the technology. After all, many analysts say the public cloud makes it much easier to use innovative analytics technology like machine learning and deep learning. It's also possible that the low-performing technology that is preventing some organizations from adopting the cloud is the legacy infrastructure in their data centers that doesn't integrate well with the cloud.

  • Regulatory compliance 35%

    3. Regulatory compliance

    The upcoming implementation of the European Union's General Data Protection Regulation (GDPR) has refocused attention on compliance, particularly complying with data privacy laws. And storing data in the public cloud can make it particularly tricky to adhere to international laws. That makes it somewhat unsurprising that 35 percent of large organizations said that regulatory compliance was a major barrier to cloud analytics.

    In an interesting twist, some organizations may actually use cloud analytics to help them improve their compliance posture. 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 32%

    4. Lack of trust in the cloud

    Thirty-two percent of the respondents to the Teradata survey said that a lack of trust in the cloud has been a barrier to moving big data analytics to a public cloud environment. While some people dismiss those with these concerns as "server huggers," cloud migration represents a very significant cultural shift, particularly for IT professionals who are used to being able to touch infrastructure physically. Stories about cloud outages and security breaches have leant weight to those fears, making this sort of cultural barrier one of the more difficult to overcome when adopting cloud analytics.

  • legacy systems 30%

    5. Connecting legacy systems with cloud applications

    As 30 percent of the survey respondents noted, connecting cloud analytics to other cloud-based systems, such as cloud storage, is extremely easy. However, connecting cloud analytics to legacy data center systems, such as in-house SAN and NAS storage, can be much more complicated. For 30 percent of the large enterprises surveyed, integration was enough of a challenge that they named it as a barrier.

    Some analysts predict that legacy integration will become less of an issue as organizations move more data storage to the public cloud. "Where the analytics workloads run is based a lot on where the data is generated and stored. Today, most public cloud workloads are new, and we won't see the percentage of cloud use rise until legacy workloads migrate en masse," said Jim Hare, research vice president at Gartner. "This scenario will happen eventually, but given the extent to which modern data and analytics efforts overwhelmingly use traditional data types stored on-premise, this shift will likely take several years to complete."

  • in-house skills 29%

    6. Lack of in-house skills

    Many organizations also find it difficult to hire professionals with the requisite skills for running big data analytics in the cloud. In fact, 29 percent of those surveyed pointed to a lack of in-house skills as a barrier. Data scientists and developers continue to be among the most highly paid IT professionals, and those with public cloud expertise are in even greater demand.

    Many vendors are responding by increasing the self-service capabilities of their cloud analytics products, allowing regular business users to run the reports they need to do their jobs. In addition, many educational institutions and training providers have added courses in cloud computing and big data analytics.

Everyone seems to believe that big data and cloud computing are a match made in heaven. So why aren’t more enterprises migrating their analytics to the cloud?

A recent Teradata survey of senior technology leaders at 700 large global organizations found that some key barriers are preventing enterprises from deploying cloud analytics. "The State of Analytics in the Cloud" report found that 83 percent of respondents believed that the public cloud is the best place to run big data analytics. And 69 percent of those surveyed said that they want to run all of their analytics on cloud computing services by 2023.

Why do they want their analytics to run in the cloud? When asked about the benefits they hoped to achieve, respondents cited the following (multiple answers were allowed):

  • Faster deployment — 51 percent
  • Improved security — 46 percent
  • Faster insight into data — 44 percent
  • Better performance — 44 percent
  • Easier access by users — 43 percent
  • Cheaper maintenance — 41 percent
  • Easier access to analytics technologies — 35 percent
  • Direct access to cloud data stores — 33 percent
  • Greater integration with other cloud services — 30 percent
  • Faster pace of innovation — 27 percent

Despite all these benefits, organizations aren't migrating analytics to the cloud quickly enough to suit most IT leaders. In fact, nine out of ten respondents (91 percent) said that analytics should be moving to the public cloud faster than it is today.

Gartner data supports that conclusion. It found that pure public cloud deployments of analytics technology are only around 21 to 25 percent of all deployments.

What's standing in the way of moving more analytics to the cloud?

In the Teradata survey, enterprise technology leaders pointed to six technical, strategic and cultural hurdles that organizations need to overcome in order to make cloud analytics viable. And ironically, some of those cloud barriers are very closely related to the benefits that IT hopes to realize with cloud analytics.

Images from Pixabay

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