Four Reasons Why Big Data Analytics in the Cloud Makes Sense Now
Business Intelligence (BI) and analytics have, perhaps rightfully, been slower to take off in the cloud than other software categories. Customer Relationship Manager (CRM) was an early mover, driven by Salesforce, and since then we’ve seen other applications like payroll and expense reporting go heavily toward the cloud. But now, all signs point to “go” for analytics in the cloud. Why?
1) More spending shifting from the IT department to line-of-business functions
Gartner notably predicted that by next year (2017), more than 50% of technology spending would occur outside of the IT department. Cloud providers are both a huge enabler, and huge beneficiary of this trend. Cloud solutions made it possible for executives in sales, marketing, HR, and elsewhere to make their own decisions about applications. In general, those deployments have had a high success rate, higher than the enterprise deployments of the past, making both individuals and companies more aggressive about choosing cloud-based alternatives for new application needs.
2) Increasing organizational comfort with the cloud
Historically, two of the most cited concerns slowing BI adoption in the cloud have been data integration and data security though they are becoming less of a conversation starter. Forrester has predicted that by mid-2016, nearly three quarters of companies will use cloud-based BI.
BI is nearly always predicated on integration of data, usually from multiple sources. Data from Enterprise Resource Planning (ERP), CRM, and other operational systems provides the foundation for BI, and many organizations decided, rightly or wrongly, that it would be easier to manage all of that plumbing in-house with an on-premises system, especially going back a few years before cloud-based apps for ERP, CRM, and other functions became popular in the mainstream. Now that apps are being built natively in the cloud, it only makes sense that companies are starting to feel more comfortable analyzing their data their too.
In terms of data security – the conversation is also shifting. The high-profile breaches of the last few years at companies like Anthem, Sony, and Target have nearly all been tied to on-premises systems. Industry analysts are telling many organizations that the security of a top-tier cloud provider may be superior to what that organization can (at least economically) deliver internally.
Of course, that doesn’t mean large organizations that are mostly standardized on traditional on-premises BI tools will throw them all out and go “all in” on the cloud. But they’ll deploy departmentally, and they’ll expand if they’re successful.
3) More pressure to deliver insights quickly in fast-moving, competitive markets
Today’s market is as fast moving and competitive as ever. It has only accelerated in the five years since Harvard Business Review described “Adaptability As The New Competitive Advantage,” suggesting that companies need to develop better frameworks for detecting changes in market conditions, and better processes for adjusting quickly, informed by the data. The cloud makes it easier for organizations to deploy solutions quickly. With cloud-based applications, many organizations can deliver full production deployments in less than the time that it would take them to procure hardware for an on-premises deployment.
4) The skills shortages are real
Beyond the above three items and the other “motherhood and apple pie” drivers of cloud adoption (faster deployment, lower TCO, lower switching costs), there is one issue that is unique to big data analytics compared with traditional BI. Right now, big data skill sets are scarce, and premium-priced as a result.
Traditional business intelligence relies on technologies that have been around for decades. There are far more SQL and relational database experts out there than MapReduce or Spark programmers. While the problem is getting better, it’s hard to find Hadoop experts. But if I can use a big data solution where Hadoop is fully managed behind-the-scenes, then I don’t need Hadoop experts.
While on-premises analytics deployments will continue for the foreseeable future, the fact remains that tides are changing when it comes to organizational comfort with moving business-critical functions like BI and analytics to the cloud. Whether making the decision to move to the cloud is instigated by economics or the ever-increasing speed of business, organizations need to get data-driven faster, and turning to the Cloud sooner rather than later may just be the answer.
This post taken from http://dataversity.net
Kalyan Banga203 Posts
I am Kalyan Banga, a Post Graduate in Business Analytics from Indian Institute of Management (IIM) Calcutta, a premier management institute, ranked best B-School in Asia in FT Masters management global rankings. I have spent 6 years in field of Analytics.