Your Analytics Ought to be in the Cloud

Blog - Advanced Analytics, Analytics

Jim picks up yet another interesting topic for discussion in the Analytics Mindset Series 3/5. If you have missed the previous blogs 1/5 & 2/5, of the series, read it here:

Way back in 2010, I was quoted in a Computerworld article ( noting that BI could be the “…next killer SaaS application.” It was a somewhat controversial statement to make in those “early” days of cloud adoption; indeed, even I was not fully convinced that all of the necessary pieces would ever be there to make cloud analytics work properly. At the time, bandwidth, security, cost, processing capacity, and privacy were some of the concerns that came to the forefront for those who had reservations about analytics in the cloud.

In the subsequent years, cloud adoption has taken off in most corners of enterprise technology enablement. Consider, most (if not all) major software companies deliver their wares in cloud-first or cloud-only formats, with the lions-share of R&D dollars following that model. Customers are modernizing their back-office operations by adopting cloud tools at a record pace across all their key systems, such as ERP, Workforce Management, and CRM. In doing so, enterprises are expecting the promise of lower costs, unbounded capacity, and superior innovation to come together to deliver their corporate objectives. Certainly, when you examine the revenue trends of the leading cloud providers today, one could certainly come to the conclusion that customers are seeing these benefits and are hungry for more.

Given what appears to be a mad sprint to the cloud, why has analytics been slow to join the dance? Certainly, it cannot be a lack of interest in the space as BI adoption continues to be high on the list of CIOs “critical application” surveys. Truly, you cannot throw a rock these days and not hit a news article where some C-suite leader is touting the benefits of “AI” and “Machine Learning” within their organization. Given all of this talk around leveraging data to engender digital transformation, you might conclude that the cloud should be the place to plant the “data flag” that powers your enterprise – right?

Yes! Let’s consider the case for analytics in the cloud with these thoughts in mind.

{MSRCosmos Analytics Practice –}

Already there. Without even realizing it, you are probably enjoying cloud analytics today. For example, are you using a leading cloud CRM that has a sophisticated analytics capability bolted onto it (named after some guy who discovered E=mc2)? Or, how about a leading BI dashboarding tool that has power written all over it? Maybe you are familiar with a website toolkit that provides deep analytics on your site traffic (it can make you googly-eyed)? Yup, analytics has been in the cloud for years, powered by the leading enterprise software companies and their platforms, and you were right there with them. Moreover, if you were to take inventory of where your enterprise data resides, I would be willing to wager that more than half is already in some cloud environment today. Thus, it would follow that integrating all of that data on a similar or adjacent cloud architecture could provide synergies.

Getting there. So, you want to develop a custom data warehouse solution in the cloud that serves up analytics to support your business objectives. As with all analytics projects, it starts with the data. Anyone who has delivered successful analytics projects of size knows that sourcing, assembling, and architecting the necessary data is (easily) the most important technical challenge to conquer.

The good news is that modern cloud environments from leading vendors have very sophisticated analytics platforms embedded within that provide an environment approaching smartphone app store convenience. Each has their specific strengths, certainly, but all can provide the basic toolkits to get data in, cleaned, and richly presented to your consumers. Some of these cloud platforms are cousins to their on-premise incarnation – if they exist – and might be slightly behind the capability curve, but vendors are keenly aware of that gap and are mindful to close it.

Power up. Thinking you will have to sacrifice performance in this “fluffy” new world? Think again. There are numerous database/data warehouse tools that have been developed in the past five years in the cloud, and they are native, angry high performing beasts. Seriously. I have spoken to customers and reviewed statistics, and these cloud-native (most built from scratch) have shown they can outperform even purpose-built appliances. Better still, a leading cloud-native data warehouse (let’s call them “flakers”) takes full advantage of the paradigm – independently scalable compute and storage, agile node management, and automated maintenance (DBAs not needed here). This is where I lament that I had to work hard “back in the day” to build stuff, these kids today…

{MSRCosmos Cloud Enablement –}

From my perspective, the move to cloud analytics is a clear mandate. For those free of legacy analytics or starting anew, move with purpose and alacrity to the cloud. If you have “lift and shift” applications to deal with, find a partner that can help you properly scope and plan your migration. When done correctly, the results should be more “move and improve” than just a change of scenery and a fresh coat of paint. Cloud is the foundation of most enterprise digital transformations and analytics ought to be a VIP in that journey.


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