Analytics In The Cloud: Larger Data Sets, More Insights
Big Data analytics has become a major driving force behind business decisions, especially in large organizations. Instead of investing a massive amount of capital upfront for an infrastructure large enough to handle the amount of data necessary to generate compelling, valuable insights, businesses now have the option of shifting the resource-intensive burden of analytics to the cloud.
Some 70.1 percent of organizations regularly rely on cloud analytics as a key part of their strategy, according to responses to an Enterprise Management Associates (EMA) study, The State of Cloud Analytics 2016, sponsored by the software information company Informatica. Another 21.6 percent revealed that they were (at the time of the survey) adopting cloud analytics.
Because of the continued proliferation of cloud analytics, businesses are in need of well-trained business professionals with degrees in business data analytics.
What Services Fall Under Cloud Analytics?
Analytics as a service (AaaS), an umbrella term that covers several aspects of cloud analytics, provides a number of technical and cost benefits over on-premise analytics solutions.
“The point of analytics as a service is that you can take advantage of analytics platforms without having to deploy everything on-premises and give your IT team even more moving parts to worry about,” according to a 2016 post, “Analytics As A Service,” on the CyberTrend: Technology For Business blog. “In the same way that moving almost any internal system to the cloud will free up some internal resources, adopting cloud-based analytics or other analytics as a service solutions gives you a quicker path to gaining insights.”
Infrastructure as a service (IaaS) can provide the hardware needed to handle larger data sets remotely. Analytics platforms are resource-intensive and require an infrastructure of enough storage space and processing power to be of any use. IaaS takes that burden and shifts it to the cloud.
Some businesses, especially those that offer monthly/annual subscription-based access to web-based software, use the software as a service (SaaS) approach. Not only is the software itself housed on remote servers, the data created by that software can be analyzed at the same location. Data as a service (DaaS) refers to the data generated and packaged in the cloud.
Cloud analytics, in all of its various forms, enhances business processes and allows for better collaboration between different departments and with suppliers/distributors. Also, cloud analytics provides better security options and data governance capabilities than most in-house services.
What Benefits Does The Cloud Offer?
Businesses that utilize cloud analytics services will find that the demands on in-house IT services are lessened, freeing up IT personnel to handle day-to-day, on-premise duties. The money saved on maintaining servers can be redirected to product development, marketing, employee recruitment and hiring, and any number of other functions.
Cloud analytics is primarily used in one of four areas, as described by TechnologyAdvice.com’s “Data Analytics in Cloud Computing”:
- Social Media – By using cloud drives to collect and evaluate social media data from a variety of sites, analysts can quickly deliver organized insights to company decision makers.
- Tracking Products – Organizations that rely on shipping physical products to customers and retailers benefit from cloud analytics through expedited package delivery, efficient stocking of warehouses, and improved overall customer satisfaction.
- Tracking Preference – Cloud analytics is adept at tracking user preferences, analyzing past activity, and making suggestions customized to individual users.
- Keeping Records – Companies can keep track of every sale at every location and process those records immediately through cloud analytics. The process speeds up inventory reports, restock shipments, and analyses of customer shopping behavior.
Companies that begin to use cloud analytics quickly learn just how useful it can be. After beginning with simple collaboration over data insights made possible by cloud analytics services, businesses often increase their use of and reliance on cloud strategies.
The eventual result is usually a robust cloud analytics strategy that uses multiple projects designed to be a self-governed service, meaning that it runs by itself within parameters set by legal regulations, company policy, and ethical considerations.
“The faster an enterprise matures in their use of cloud analytics, the more quickly they progress from collaboration to enhancing business processes and strategies,” says Ingram Cloud’s Global Cloud Product Management Director Louis Columbus in his article “State Of Cloud Analytics In The Enterprise” on Forbes.
“By definition, robust organizations are those who are engaged in five or more analytics projects. Self-service enables enterprises with the most robust adoption of analytics to create data sources and models on the fly and gain greater value from their cloud analytics investments as a result.”
Hybrid Cloud Analytics
Business intelligence (BI) occasionally requires a deeper analysis of customer activity and business data than simple visualizations created by SaaS and AaaS services.
When a company needs an analytical approach beyond what is offered by cloud services, it may need to combine cloud infrastructures (both public and private) with on-premise infrastructures in order to orchestrate seamlessly delivery of useable BI.
“A properly governed (hybrid cloud) solution allows you to define rules around where data and/or the analysis on that data can be stored or run – you can create enforcement rules on where things can and will reside based on the sensitivity and security of that dataset,” writes data & analytics expert Drew Clarke in his post “Hybrid Cloud Analytics: Don’t Be Cloud-Washed By The New Term On The Block” on CloudComputing-News.net.
“A hybrid cloud analytics solution must allow for bi-directional migration to/from one infrastructure environment to another and should be managed as one seamless environment across infrastructure boundaries via a single console.”
As the business world embraces hybrid clouds more, customers will notice that suggestions custom generated specifically for them are much more accurate and personalized than they are now. Marketing departments will also benefit from hybrid cloud analytics because their targeted marketing efforts will be much more precise and therefore much more likely to work.
Maryville University’s MS In Business Data Analytics
The demand for business analytics experts lies at the heart of Maryville University’s online Master’s of Science in Business Data Analytics degree. Cloud analytics and hybrid cloud analytics solutions undertaken by businesses over the next five to ten years will require competent analytics experts well trained in the field.
At Maryville University, students learn how to handle datasets, orchestrate multiple infrastructures, monetize data, and present competitive information to decision-makers. Graduates will have the training and knowledge to combine business operational data with the latest analytical tools, making them invaluable to employers.
The State Of Cloud Analytics 2016 – https://www.informatica.com/lp/the-state-of-cloud-analytics-2016.html#fbid=rgpUgcfCRZt
Analytics As A Service – https://www.cybertrend.com/article/23979/analytics-as-a-service?
Data Analytics in Cloud Computing – http://technologyadvice.com/wp-content/uploads/2013/05/Data-Analytics-in-Cloud-Computing_TechnologyAdvice.pdf
State Of Cloud Analytics In The Enterprise – https://www.forbes.com/sites/louiscolumbus/2017/03/11/state-of-cloud-analytics-in-the-enterprise/#444bb6b03ad6
Hybrid Cloud Analytics: Don’t Be Cloud-Washed By The New Term On The Block – https://www.cloudcomputing-news.net/news/2017/feb/23/hybrid-cloud-analytics-dont-be-cloud-washed-new-term-block/