As the cloud goes mainstream, the technology will become crucial to executives handling projects powered by analytics. Besides the ongoing issues of scale, speed, and cost squarely addressed by cloud-based big data analytics, their new issues around privacy, latency, and veracity are also things to take into consideration. Let’s get this out of the way: you need to move your data analytics to the cloud. The business case for moving your company's information technology (IT) applications, including data analytics to the cloud, is compelling but it is not as easy as you might expect. Here’s why.
When compared to building or expanding an in-house analytics infrastructure, migrating analytics workloads is relatively fast but unfortunately unquestionably cost-efficient and also carries risks of delays, service interruptions, and project failures.
Firstly, the transfer of data from enterprises to the public cloud is a bigger chore than what you might expect. If you think that it is possible to transfer data to the cloud at a push of a button, then you might have got a mistake. The real story is somewhat of a surprise. The cloud lets you weigh the pros and cons of a system without committing the resources, however, depending on how you use cloud services and the cloud providers themselves, the cloud services might provide great performance or not perform well at all.
Containing not only the database itself but also metadata which defines and describes the data and relationships between tables in the database, a database system is reasonably referred to as self-describing. Do you think that it is easy to go through the processes to move several petabytes of data?
Second, data integration is still an issue in the cloud; moving the data does not magically solve all of your integration challenges. Also, a big question for many chief information officers—and perhaps the biggest barrier to making the move: Can our company’s data be secure in the cloud?
Whilst some public cloud providers are starting to provide customers —your company with more data ownership and control over their data by providing ample tools and guidance to help you secure and manage the data, the information stored in the cloud is often not within an organization’s control. Thus, a lot of IT executives consider moving workloads into the cloud a potential loss of control.
Instead, it is the security practices of third parties that completely control the integrity of your data. Unfortunately, access to cloud storage can also be affected by bouts of unpredictable data throughput over the internet. This is out of your control and impossible to guarantee. The best practices may not always be applied to your organization’s security.
It does not make it inherently secure to move your data to the cloud. In order to protect your data, you must use your existing infrastructure as well as the tools and processes established by the cloud providers. Facilities, infrastructure, and architectures that employ some of the world’s most sophisticated physical and virtual security measures have been built by the top cloud service providers. It cannot be denied that cloud providers are experts at running large-scale data center operations, but it does not mean that they will never suffer equipment failures and other outages.
In addition, with the massive threat of cybercrime, the data breaches becoming more commonplace, and especially the average cost of a breach now a massive $4 million in 2018, who dare to consider public cloud security threats an afterthought?
Last but not least, cloud-native businesses and startups take advantage of the public cloud storage to achieve an incredible amount of data storage capacity and advanced storage management capabilities. But the cloud-based analytics databases themselves - the only solution that brings high-performance SQL analytics to big data - are complex and difficult to configure. Some of that complexity comes from the security subsystems in the database. They are, of course, good at what they do but there are always trade-offs and they should be figured out in the context of the database and data analytics. To launch you on the path that works best for your company, it is advised to understand the qualifications, migration patterns, key decision points, best practices and tools that are essential for success.
While the advantages of the premise-based IT software and tools are popularly recognized, cloud-based applications, which offer more connectivity and functionalities than legacy systems, are the global trend. Different companies might have different needs, but they all have to face common challenges on planning, scoping, and executing an analytics migration to the cloud. Why are data-driven decisions now an essential, daily, and valuable activity for all types of business people — not just marketers, data analysts, and IT architects? It is due to the emergence of cloud, the abundance of data, and the advances in analytics. And as controlling a big data is a complex, tricky thing, propelling the pairing of the cloud with big data requires companies to learn to master some key steps.
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| Reasons to move your data analytics to the cloud |
Firstly, the transfer of data from enterprises to the public cloud is a bigger chore than what you might expect. If you think that it is possible to transfer data to the cloud at a push of a button, then you might have got a mistake. The real story is somewhat of a surprise. The cloud lets you weigh the pros and cons of a system without committing the resources, however, depending on how you use cloud services and the cloud providers themselves, the cloud services might provide great performance or not perform well at all.
Containing not only the database itself but also metadata which defines and describes the data and relationships between tables in the database, a database system is reasonably referred to as self-describing. Do you think that it is easy to go through the processes to move several petabytes of data?
Second, data integration is still an issue in the cloud; moving the data does not magically solve all of your integration challenges. Also, a big question for many chief information officers—and perhaps the biggest barrier to making the move: Can our company’s data be secure in the cloud?
Whilst some public cloud providers are starting to provide customers —your company with more data ownership and control over their data by providing ample tools and guidance to help you secure and manage the data, the information stored in the cloud is often not within an organization’s control. Thus, a lot of IT executives consider moving workloads into the cloud a potential loss of control.
 |
| A lot of IT executives consider moving workloads into the cloud a potential loss of control |
It does not make it inherently secure to move your data to the cloud. In order to protect your data, you must use your existing infrastructure as well as the tools and processes established by the cloud providers. Facilities, infrastructure, and architectures that employ some of the world’s most sophisticated physical and virtual security measures have been built by the top cloud service providers. It cannot be denied that cloud providers are experts at running large-scale data center operations, but it does not mean that they will never suffer equipment failures and other outages.
In addition, with the massive threat of cybercrime, the data breaches becoming more commonplace, and especially the average cost of a breach now a massive $4 million in 2018, who dare to consider public cloud security threats an afterthought?
Last but not least, cloud-native businesses and startups take advantage of the public cloud storage to achieve an incredible amount of data storage capacity and advanced storage management capabilities. But the cloud-based analytics databases themselves - the only solution that brings high-performance SQL analytics to big data - are complex and difficult to configure. Some of that complexity comes from the security subsystems in the database. They are, of course, good at what they do but there are always trade-offs and they should be figured out in the context of the database and data analytics. To launch you on the path that works best for your company, it is advised to understand the qualifications, migration patterns, key decision points, best practices and tools that are essential for success.
While the advantages of the premise-based IT software and tools are popularly recognized, cloud-based applications, which offer more connectivity and functionalities than legacy systems, are the global trend. Different companies might have different needs, but they all have to face common challenges on planning, scoping, and executing an analytics migration to the cloud. Why are data-driven decisions now an essential, daily, and valuable activity for all types of business people — not just marketers, data analysts, and IT architects? It is due to the emergence of cloud, the abundance of data, and the advances in analytics. And as controlling a big data is a complex, tricky thing, propelling the pairing of the cloud with big data requires companies to learn to master some key steps.
Moving your data analytics to the cloud isn’t so easy
Reviewed by thanhcongabc
on
June 20, 2018
Rating:
Reviewed by thanhcongabc
on
June 20, 2018
Rating:
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