Traditionally, large businesses have chosen their directions and planned their future strategies based on insights derived from limited structured data created by or stored in large enterprise systems, such as enterprise resource planning (ERP) or CRM systems. But, today, vast majority of data is being generated by the Web, smartphones, and the Internet of Things that is available to both large and growing enterprises without any bias. Thinly staffed IT organizations are unable to cope with the demands being placed by analytics organizations. The traditional approach to analytics from IT is neither feasible nor desirable! A more flexible and agile approach is absolutely required to deliver on analytical innovations for large and growing enterprises.
This is where cloud based Big Data Analytics technologies come into play. There are vast sources of untapped data such as data from distribution channels, social media, client surveys, contracts, emails, white papers published by research firms, government studies and customer social media data that might explain gross patterns and root causes. Big Data exploitation and monetization cannot happen through a single technology, technique or initiative. Rather, it is an amalgamation of technologies and initiatives that help in creating, storing, retrieving and analyzing data that is remarkable in terms of volume, velocity, and variety.
As Terence Ngai describes in his blog post, “By storing data and performing analytics in the cloud, you can take advantage of distributed processing to greatly increase the speed of your operations. Because you don’t have to move data over the network, you reduce traffic requirements and lower latency rates. The massive scalability available on an as-needed basis can save you the cost of building your own data centers and provide the flexibility you need to meet changing business conditions. The net result? Faster business decisions.”
Traditional Business Intelligence/ Data Warehousing applications involved high infrastructure requirements, high development and maintenance costs and needed to go through a long route for provisioning and were heavily dependent on internal IT team. On the other hand, cloud based Data Management and Analytics applications can become operational in a few days with negligible initial investment and overhead costs, which is why it becomes a lucrative opportunity for growing businesses to harness the power of Advanced Analytics without having to invest in any on-premise solutions.
The 4 main advantages that cloud delivers for storing, synchronizing and analyzing data include:
- Distributed processing to provide agility
- Cost savings
Agility is about being flexible and responding quickly to change. However, it has been difficult to increase the agility of BI, analytics, and data warehousing systems through traditional development cycles where traditional procurement, budgeting, planning and prioritization act as bottlenecks. Therefore, analytics applications on the cloud provide the much-needed on-demand IT to support internal as well as external projects. Cloud enables businesses — not just IT operations — to add or provision computing resources just at the time they’re needed.
Here is an example of how data analytics solutions on cloud deliver on that dimension. Royal Dutch Shell was working on not only reducing energy costs but also to be more agile in deploying IT services and planning for user demand. To reach those goals, Shell in 2010 began using Amazon Web Services. Shell leverages sensors to find oil in wells formerly thought to have run dry or in places where previous exploration indicated there was no oil. These sensors create massive amounts of geological data. Shell’s IT shop has to figure out how to effectively manage the giant files and to deploy these sensors quickly and profitably. They provision compute capacity themselves, run their models on AWS cloud platform and then return the cloud compute capacity, getting charged only for what they used. Shell says that two to three hundred project teams could be up and running in a day versus the weeks it would take them prior to AWS.
Customers today are more informed, less loyal, and expect to be treated the same way across different channels, and so companies need an effective omni-channel strategy. This has been a trend for a while, but using cloud-based solutions make it much easier and faster to integrate and scale. As Dr. Fern Halper discusses in her article, “Many companies process the external data sources in the public cloud and then bring the reduced (analyzed) data set on-premises to make it part of a bigger analysis. These are specific, targeted horizontal or vertical applications that can be called upon from the cloud when needed. For example, a credit card fraud application might be run in the cloud and then the results are pulled back into the rest of the analysis on premises (say, in a private cloud). Another example: a campaign management system or an analytics service that does retention analysis. One way to think about it is almost as a skills-as-a-service model, given the lack of skills in the advanced analytics space.”
Cloud provides access to infrastructure resources on a pay-as-you-go basis enabling organizations of all sizes to explore and use large volumes of information without making a heavy upfront capital investment in infrastructure. This elasticity helps businesses to efficiently innovate and test-run projects that could not be as easily accommodated by an on-premise deployment. As shared in a the Economist-IBM survey, 31% company executives shared they like the cloud’s “pay-as-you-go” cost structure as it takes away the need to fund the building of hardware, installing software, or paying dedicated software license fees. This was the appeal for Etsy, an online marketplace for handmade goods that brings buyers and sellers together and provides recommendations for buyers. “Using cloud-based capabilities, the company is able to cost-effectively analyze data from the approximately one billion monthly views of its Web site and use the information to create product recommendations,” the report notes. “The cost flexibility afforded through cloud provides Etsy access to tools and computing power that might typically only be affordable for larger retailers.”
Cloud analytics is the key that can unlock the treasure trove of data for businesses of different sizes, in various sectors. Those who are able to drive above-market growth, though, are the ones who can effectively mine that gold.
CoreCompete is a provider of Cloud Analytics. Click here to learn more about our service.