Your need for data is ever growing, and the traditional methods of data storage and processing are no longer viable. What do you do?
In today’s real-time information world, marketers have a variety of priorities to juggle with customer experience, personalization, digital marketing, customer 360, marketing automation, measuring marketing ROI, and the list goes on.
As you look deeper into the marketer’s world of data and analytics, you see the greater the need for an integrated, scalable, elastic, robust, cost-efficient, and secure data-storing and data-crunching environment. This is where the big data problem is revealed. To leverage a data-driven approach, we need to store and process data from wide variety of sources, in huge volumes, and at high velocity.
What worked in the past, will not work today
Traditionally, IT has relied upon standing up marketing databases and data warehouses using relational databases located on premise or collocated in data centers. But, in today’s digital age, the set up for this model quickly becomes cost prohibitive not only due to the high volume of data needing to be stored, but also due to the amount and high-degree of complex data processing required—just imagine storing and processing social media data on a relational database! Moreover, such a processing environment needs to be elastic to scale or shrink depending on the need.
To further add to the list, these on-premise, hosted databases come with their own challenges such as: long procurement cycles, an upfront capex investment, frequent upgrades (adding storage and compute capacities), performance-tuning, administration and maintenance, and so on. The story becomes even more grave if your IT budget is shrinking.
Don’t give up, there is a silver lining to this bullet. Meet public cloud.
Public cloud is gaining more and more adoption in the enterprise technology world. Since 2009, cloud computing spend is growing at a 4.5X rate of IT spend. From 2015 to 2020, cloud computing is expected to grow more than 6X the rate of IT spending. According to the IDC, worldwide spending on public cloud computing will increase from $67B in 2015 to $162B in 2020 attaining a 19% CAGR.
With increased elasticity, unlimited scale, robust security, and on-demand pricing, public cloud-based computing environments are perfect for big data workloads. Cloud providers such as Amazon Web Services, Google Cloud Platform, and Microsoft Azure provide platform as a service (PaaS)-based SQL and NoSQL services to crunch massive volumes of structured or unstructured data in a matter of minutes, if not seconds. These services are fully “NoOps”, meaning you don’t have to worry about maintaining and managing underlying hardware or software, instead you focus more on data and application.
Is public cloud the right answer for you? Contact us to schedule a meeting with a cloud expert to learn how we help clients successfully to the plunge to the cloud.