4 Benefits of Investing in Cloud Analytics
Author: Tom Hoblitzell | 7 min read | June 30, 2022
Organizations of all stripes are increasingly demanding cutting-edge, data-driven business insights—so how can you stay ahead of the curve? As part of an overarching digital transformation strategy, more and more companies are moving their on-premises data analytics into the cloud.
Adoption of cloud analytics is skyrocketing: in 2020, 47 percent of enterprises reported having an analytics platform fully in the cloud, while another 42 percent used a hybrid solution spanning both cloud and on-premises. What’s more, this figure of 47 percent increased sharply by 8 percent from just the previous year.
But what are the factors that motivate businesses to invest in a cloud analytics migration? In this article, we’ll go over 4 advantages that make the move to a cloud analytics platform worth every bit of effort.
1. Scalability and flexibility
In general, one of the greatest benefits of the cloud is the increased capacity to scale: adding or subtracting compute or storage resources as necessary in order to fit changing levels of demand.
For businesses still wedded to on-premises analytics, scalability can be a touchy subject. Because you don’t know ahead of time what level of demand you’ll face, companies often purchase on-premises computing resources in excess of what they’ll use on a day-to-day basis. This means that much of your analytics capacity will sit idle, only being used during times of peak activity.
By contrast, moving to the cloud allows you to rapidly and flexibly scale your analytics consumption (either horizontally or vertically) on the fly. This ensures that business intelligence and analytics users can continue to uncover hidden trends and nuggets of wisdom, no matter how much strain your platform is facing.
2. Cost-effectiveness
As a corollary to the above point, using cloud analytics frequently results in cost savings compared with on-premises analytics. This is because cloud computing typically uses a “pay as you go” model, in which customers pay only for those resources that they actually consume. On-premises IT, on the other hand, is a capital expenditure that must be paid upfront, requiring businesses to (over)estimate the resources that they’ll require over the next several years.
In addition, cloud analytics (and cloud computing in general) is often more cost-effective because customers are freed from support and maintenance expenses. Rather, fixing technical issues is the sole responsibility of the cloud provider, who also offers guarantees about the level of uptime that users can expect (e.g. 99.9 or 99.99 percent uptime).
3. Advanced features
Cloud analytics providers such as Oracle have stated their commitment to being a “cloud-first” company: new features and functionality are rolled out to cloud software users before reaching the on-premises version. This means that customers of cloud analytics enjoy a competitive advantage over their business rivals that remain on-premises.
For example, a major game-changer for business intelligence has been the rise of self-service analytics in the cloud. This feature empowers non-technical users to run their own queries and interpret the results, without the assistance of BI and analytics experts. No-code database queries and data visualization tools such as dashboards, charts, graphs, and heatmaps have now brought the power of self-service data analytics to the masses.
4. Total visibility
Much has been said about large enterprises’ need for a “single version of the truth”: a centralized, easily accessible repository that stores your most recent and accurate information. This results in a data resource that everyone can agree is the most “trusted” up-to-date version, preventing confusion and conflicts.
With cloud analytics, it’s much easier for organizations to create and maintain a single version of the truth for their business intelligence needs. For example, many companies seek to establish a “customer 360,” end-to-end view of their audience. This incorporates all of a customer’s interactions with your business across multiple channels and touchpoints, from social media “likes” to support inquiries and refunds. Cloud analytics makes it much easier to pull all the data from the relevant sources and applications, such as your CRM (customer relationship management) software and your ticket management system.
Conclusion
From scalability to visibility, this article has just scratched the surface of what’s possible with cloud analytics. In order to fully enjoy these benefits, many businesses choose to work with a knowledgeable and trustworthy analytics partner such as Datavail.
Datavail is a skilled, experienced IT managed services partner that has helped thousands of clients with their database, analytics, business intelligence, and application development needs.
Our list of cloud analytics certifications includes:
- Microsoft Gold Partner (with 17+ years as a trusted Microsoft Partner)
- AWS Advanced Tier Consulting Partner for Analytics
- Oracle Specialized Partner for Business Intelligence
With an average partnership length of more than 7 years, Datavail has an extensive track record of satisfied long-term clients. Below is just an overview of our cloud data analytics services:
- Cloud readiness assessments of your IT hardware, software, and integrations
- Roadmaps and strategic planning for minimal downtime
- Total cost of ownership (TCO) analyses for the most cost-effective solution
- Migrations and upgrades for your data warehouse or data lake
- Integrations and connections for your on-premises and third-party data sources
- Real-time dashboards and reporting for up-to-the-minute insights
- Ongoing long-term support and maintenance
Are you considering a migration from on-premises analytics to the cloud? Our team of business intelligence and data analytics experts is ready for a chat about your business needs and objectives. To learn more about how cloud analytics can benefit your organization, read our white paper “Journey to Cloud Analytics: Using the Cloud to Solve Your Analytics Challenges.”