By John L. Myers and Lyndsay Wise
Cloud implementations have been evolving for many years. Salesforce.com made great strides in how organizations view the cloud as an implementation option for central core activities of an organization, such as sales operations. To many, Amazon Web Services proves that cloud infrastructure is not a one-off or custom environment for large-scale organizations. Cloud infrastructure can be utilized not only by organizations of any size, but smaller segments, such as departments and teams.
For analytics and analytical environments, there is not a “champion” example to look to yet. Data warehouses have traditionally been built as part of “behind the firewall” data center implementations utilizing desktop analytical packages and on premises data integration facilities. However, in the past two to three years, organizations are embracing the opportunities and possibilities of the cloud. They are not letting past deployment strategies become a barrier for current and upcoming cloud-based analytical environments.
In upcoming Enterprise Management Associates (EMA) end-user research, respondents overwhelmingly indicate that cloud-based analytical strategies are part of their organizations.
With nearly six out of ten respondents indicating that cloud-based analytics is either an “essential” or an “important” part of their business, these organizations show that the cloud as an implementation avenue is core to future plans.
Cloud is Superior
The past use of on-premises strategies to implement data warehouses and other analytical environments was mainly based on a “lack of substitutes” for the technical facilities. There was no cloud-based data management platform or analytical environment. However, with offerings such as Dell Boomi, Informatica Cloud, and the SnapLogic Elastic Integration Platform, we have seen a shift—starting with data integration—to implementing analytical environments in the cloud.
EMA research respondents overwhelmingly indicate that cloud platforms provide a better solution than their on premises counterparts. In fact, the highest indication is around the total cost of ownership component of the cloud versus on premises situation. Over five out of ten EMA respondents indicate that cloud-based analytical implementations provide a superior option. Overall, nearly nine out of ten indicate that the cloud is on par with or superior to an on-premises solution.
This momentum has continued from the data integration components into the data management and data visualization areas of analytical environments. Amazon and Snowflake’s “data warehouse as a service” offerings have introduced the ability for organizations to put power and performance into cloud-based data management platforms. Organizations such as MicroStrategy and Tableau have flexed into full-fledged, cloud-based solutions that complement their on premises and desktop offerings.
Strong Benefits from Cloud
Cloud-based analytical environments provide benefits over and above the perceived superior value to on premises solutions. Improved security is the top perceived benefit from the EMA cloud-based research panel. This comes from the heightened focus on security and privacy from recent high-profile breaches of security involving Anthem, Home Depot, and Target. Even though these security breaches were based on on premises data centers and associated infrastructure, the theme of security and privacy runs throughout cloud-based solutions. If an organization has a disjointed set of security policies across multiple locations, cloud-based solutions offer the opportunity to have a single set of security protocols outsourced to an organization with expertise across multiple implementations. While there is the risk of having a breach across multiple organizations with a single cloud-based infrastructure, to date, there have been few high-profile cases of data breaches based on cloud-based architectures managed by established providers.
In addition to the security benefits, EMA respondents indicate that they see great value in cloud-based solutions for lowering their implementation costs, both in terms of effort and in terms of expenses. The numbers two, four, and five benefits, according to panel respondents, were a lower overall administration level of effort, ease of integration, and implementation time frames. All of these contribute to one of the core advantages of cloud-based analytical environments, ease and speed of implementation.
When you consider the amount of administration and implementation time spent on current analytical infrastructures, this advantage becomes a key driver in the implementation of new analytical environments into a cloud infrastructure and/or the transition of existing analytical environments to new, less administration-intensive environments, such as cloud-based infrastructure, and/or managed service environments, such as Teradata Cloud.
Cloud is No Longer “Little Brother”
In EMA end-user research in 2011, 2014, and 2015, the overall value of cloud-based analytical environments has matured to the point where organizations are comfortable with either cloud-based or on premises solutions for their analytical environments from simple data visualization to advanced analytics. This means the decision to choose cloud or not is based more on the strategies and budgets of the implementing organization and less on the technical capabilities of a cloud solution.
Cloud-based analytics are now here to stay. With ease of use and low total cost of ownership, cloud-based solutions provide an easier path to implementation and faster distribution time frames that enable organizations to solve particular analytical issues based on their implementation strategies and budget constraints rather than technology limitations. SW
John Myers is managing research director, business intelligence (BI) data warehousing, EMA. He joined the firm in 2011 as senior analyst of BI. In this role, Myers delivers coverage of the BI and data warehouse industry with a focus on database management, data integration, data visualization, and process management solutions.
Lyndsay Wise joined EMA in 2015 as research director for BI and data warehousing, focusing on data integration, data governance, cloud technologies, data visualization, analytics, and collaboration. She has more than ten years of experience in software research, BI consulting, and strategy development, specializing in software evaluation and best-fit solution selection.
Feb2016, Software Magazine
