How Businesses Are Learning from the Mistakes of Early Cloud Adopters to Optimize New Deployments

Is the Cloud Ready for Business Analytics?

IntroductionIn The Art of War, Sun Tzu wrote, “If you wait by the river long enough, the bodies of your enemies will float by.” The same could be said for the early failures of cloud computing. Business and technology leaders who took a wait-and-see approach avoided these early failures.

They watched as cloud scope creep, security failures, performance loss, and poor bandwidth planning – among other problems – floated by.

Today, we’ve entered the Second Phase of the Cloud Movement. Organizations have learned from the mistakes of the First Cloud Movement and are ready to fundamentally change their approach to business by harnessing the power of cloud computing.

Savvy business leaders are looking to a new kind of cloud computing in this Second Phase. This cloud computing movement is ready to enable organizations with the power of big data analytics. It’s ready to seamlessly weave together both on-premise and off-premise data with third party data and applications. Analytics capabilities that were previously off-limits to corporations because of steep barriers to entry will now be accessible to many.

The companies that make the move now and adopt early won’t be talking as much of a risk as early cloud pioneers did. The lessons learned from the First Phase of cloud computing will allow for a more seamless transition into cloud-powered analytics.

The First Wave of the Cloud MovementTo understand the Second Phase of Cloud Computing, we have to tell the story of theFirst Phase’s early adopters. In the early days of the First Phase of Cloud Computing, the cloud was seen primarily as a new way to deliver software and hardware to end-users without the physical requirements of removable media and servers.

Organizations slowly became comfortable with the idea of their CRMs or other non-critical applications living in the cloud. A movement started to build that viewed the cloud as a place where your data would live. The cloud would treat data like a utility.

The hype surrounding this early cloud utopia said that businesses would see great cost savings. It promised that the high upfront costs associated with new infrastructure could be avoided through cloud computing. However, the early hype hit major speedbumps as companies experienced higher than expected costs, security failures, planning failures, outages, and performance issues.

In this First Phase, people were figuring out what the cloud could do – and what it couldn’t do. In the Second Phase, companies are learning from the mistakes of the past and are ready to use advances in computing to do even more with the cloud.

Lessons Learned from the Early Failures of Cloud Computing Lesson 1: Cost Savings

The promises of cost savings from cloud technologies were an early key selling point and value proposition. But many of the promised savings didn’t match with reality. Companies saw themselves paying similar amounts for the hardware, data, and applications that they paid for their on-premise technology. Today, organizations understand that the cost advantage of a cloud migration is found in the ability to move from a capital expenditure model for IT to an operational expenditure model.

Lesson Learned: Cloud may not save you in the long run, but it comes with more predictable pricing.

Lesson 2: Migrations Are Not Easy

As we move into the Second Phase of Cloud Computing, one of the big lessons that has been learned is that companies need to harness the experience of cloud professionals to avoid a failed migration or reimplementation. Applications that may operate in the data center may not operate the same way in the cloud. These complexities and incompatibilities must be considered when building a cloud strategy.

Lesson Learned: Working with experienced cloud migration specialists and testing in target architecture environments before a migration or reimplementation begins can help you avoid potential performance issues. In a migration scenario, a cloud migration specialist can work with your organization to prioritize the data and applications that can be moved to the cloud. In a reimplementation phase, specialists can help you avoid some of the implementation mistakes that were made in other iterations.

Lesson 3: Cloud Security Strategy Is a Must

If businesses don’t align their corporate data security requirements with their cloud deployment strategy, they could be putting themselves at risk of a crippling data breach. Cloud companies and major retailers that didn’t have a sound upfront cloud security strategy learned this lesson the hard way. The downtime, stolen data, and lost revenue from cloud technologies have been well documented.

Lesson Learned: Just as any in-house data is at risk to hackers or disgruntled employees, data on the Internet is at risk. Proactive data protection strategies must be part of every cloud deployment. Identify your most valuable data and make sure it has the highest levels of redundancy and service level agreements (SLAs).

A 2014 Capgemini Consulting report1 stated that only 8% of executives calledtheir big data projects “very successful.”

Lesson 4: Cloud Is NOT All or Nothing

Many cloud deployments failed as companies tried to pull off full-scale migrations of their data. Applications performance suffered and unhappy employees’ complaints of downtime and high latency increased. Cloud providers and solutions that were not fully vetted often failed.

Lesson Learned: As we step into the Second Phase of Cloud Computing, we see that hybrid cloud deployments allow for more control, greater flexibility, and increased functionality of databases and applications. Hybrid cloud is here and is an option for companies that want to maintain more control.

Lesson 5: Data Analytics and Application Failures

Early analytics projects failed for a number of reasons. The biggest lesson learned is that most cloud deployments weren’t ready to handle big data analytics or complex business applications. There was a false conflation of cloud with analytics and business functionality. Businesses did not take into account that cloud is an alternative platform that brings many exciting advantages to improve operational efficiencies. The cloud itself, though, does not meet more functional business requirements than any other platform. In that regard, the cloud wasn’t designed just for big data – it was designed to handle a wide spectrum of functions, from application development to software testing and other initiatives. The tools weren’t ready, the plans were vague, and companies didn’t have the people in place who understood the intricacies of a cloud deployment – let alone a big data analytics strategy.

Lesson Learned: The failures here fall into two broad categories: technology and culture. The technology wasn’t ready to do what the business demanded. Businesses themselves failed to completely grasp what the technology could and couldn’t do. For data analytics projects to be successful, clear goals must be put into place, the raw data must be organized, and the right technologies must be utilized.

The New Path to Business AnalyticsThe First Phase: The structured databases of many corporations were not suited to process big data. In addition, the costs of storing and processing big data were not economical.

The Second Phase: The structured databases of many companies are still in need of more structure and organization. Companies are building from the failures of early big data projects and employing database experts to help them build smarter databases that allow for better extraction of business intelligence.

Organizations are making sure that they have clear plans and are working with data analytics experts to build a path forward to collecting new insights from their data.

Cloud computing has evolved. Its technological capabilities have increased. The cloud and its emerging capabilities are bringing not just a Second Phase of cloud, but a new age of information technology.

The cloud has come of age and big data is going to be an enormous part of the growth of cloud computing. CompTIA’s 2011 2rd Annual Trends in Cloud Computing cites a report from

IDC saying that public cloud IT spending was $21.5 billion in 2010.2 Current predictions for 2015 by MarketsandMarkets estimate that by 2020, the cloud analytics market alone will be a $23.1 billion dollar industry.3

Cloud Computing Has Lowered the Barriers to Entry for Analytics…But You Still Have a Few Decisions to Make

For companies that want to make the most of the power and economics of cloud-based applications, the time is now. By properly structuring their databases, they can start to process data workloads without needing in-house super-computing.

Companies who are already doing in-house analytics are at an advantage. Even they will start to see the benefits of leveraging powerful cloud technologies to quickly scale their ability to store and process their data. The cloud also offers flexibility for in-house deployment, so organizations can continue running their in-house analytics while taking advantage of the on-premise capabilities that cloud technologies have to offer.

Structured Versus Unstructured Data

Businesses will still need to make an investment in someone who can help you make sense of the company data. Many companies will try to avoid this step and will be lured into the “data lake” myth – or the idea that they can take their pools of unstructured data and still see the same benefits.

The variety and velocity of your data may mean more than how “big” your big data is. Unless you have teams of analysts who are very adept at data analysis and data manipulation, the “data lake” concept may fail your organization. This is the one barrier that will still be tough for many companies to overcome, which is why they buy into the dream of the data lake. It offers them an illusion of an accessible path without going through the due diligence that is required for discovery, provenance, and data security. At the end of the day, the effort is a waste of time if the data are not verifiable and trustworthy.

Organizations will still need to leverage experts with the skills to organize their data in a logical way.

Choosing a Path Forward

Companies that haven’t started to build a plan for their unstructured data are already seeing that the barriers to entry have been eroded. They now must choose a path forward and decide on which hosting environment, software, data format, and technology providers will propel them onward.

What Will Cloud Enabled Business Analytics Do for You?The competitive advantages of the business insights that can be gained from data analytics is now available without significant investment in additional computers and storage required to process larger, denser volumes of data.

Combining the power of big data analytics and the cloud allows organizations to:

• Have on-demand access to unlimited computing and analytics power.• Inexpensively and rapidly develop “what if” ideas around new products and services.• Avoid purchasing or maintaining software licenses or expensive servers.• Collaborate with business partners, networks, and customers regardless of

physical location.• Avoid unexpected cost overruns.• Scale up or down as needed.• Rely on the cloud solution provider for troubleshooting and service.

Given these advantages, expect that the Second Phase of Cloud Computing will allow entry into cloud analytics for companies who were previously locked out because of concerns of project failures and high costs. Early cloud pioneers forged the road, and now, many more organizations will join to gain a competitive advantage and grow their businesses.

ConclusionThe Second Phase of Cloud Computing is ready to start serving the needs of organizations looking to tap into the power of big data analytics.

This cloud computing movement is faster, smarter, and more secure. The Second Phase of Cloud Computing is ready to help organizations make better decisions, get answers to questions faster, and process predictive business modeling in ways that would have been unheard of just a few years ago.

This Second Wave will allow organizations to easily manage enterprise applications, offload infrastructure management tasks, and derive more value from their technology investments.

Are you ready for enterprise cloud computing—one that does more than just store data? Let us help you understand how the cloud is relevant to your business model. Reach out to QueBIT today, and we’ll help you evaluate the options and develop a business plan that meets your requirements.

About QueBIT: As an IBM Premier Business Partner and multi-year winner of IBM’s Business Analytics Partner of the Year award, QueBIT has leveraged its close relationship with IBM to keep abreast of developments of its cloud offerings as they were being formulated. QueBIT also assists customers with public cloud deployments of IBM platforms like TM1 and developing QueBIT’s own cloud SaaS (“Software as a Service”) planning and reporting solution, CloudWORQ.

Sources1 Capgemini Consulting | https://www.capgemini-consulting.com/resource-file-access/resource/pdf/big_data_pov_03-02-15.pdf2 CompTIA | https://www.comptia.org/resources/2nd-annual-trends-in-cloud-computing3 MarketsandMarkets | http://www.marketwatch.com/story/cloud-analytics-market-worth-231-billion-by-2020-2015-07-15-1120312

Please contact us at info@quebit.com if you are ready to leverage the cloud.