Cloud Analytics: Real-World Insight for Fruitful Outcomes
Discover motivations and use cases for cloud-based delivery of analytics
Recent IBM Data magazine features introduced the serendipitous union of cloud computing and big data analytics technologies as an alternative to on-premises infrastructure,1 and presented a basic taxonomy of cloud analytics offerings.2 Taking a look at some practical use cases can highlight how accessible cloud-based delivery of analytics can be for organizations and how it is designed to deliver immediate, beneficial business outcomes.
There are many cloud analytics offerings available today. However, each organization is likely to have a single or perhaps a handful of reasons for getting started with cloud analytics. The following reasons are among some that typically motivate many organizations to adopt cloud analytics:
- Cost-effectiveness: Many organizations start to use cloud analytics to help avoid the spending necessary for the on-premises hardware and software for infrastructure set up to run analytics efficiently.
- Limited skill sets: Limited or lack of in-house analytical skills compels some organizations to adopt analytics-as-a-service offerings that include platform and technical resources to develop models and implement a solution.
- Access to cloud-based data: When the target data of an analytics solution is generated or stored on the cloud, it makes sense to locate the processing components near this data. Cloud-based location near the data tends to be the case with a growing number of solutions that access social networks and data from the Internet of Things sensor data, such as data generated by cars and mobile phones.
- Collaboration: When a number of organizations need to collaborate around solutions that include analytics, using cloud analytics to combine data and models for them makes sense to enable access by all the organizations involved.
The use cases offered here demonstrate how cloud analytics help organizations deploy cloud-based analytics for deriving the insight necessary to fulfill business strategy goals and strive for successful outcomes.
Using digital analytics to help reduce customer churn enabled Boston, Massachusetts–headquartered Carbonite to save USD4 million annually.3 The organization provides cloud-based, Health Insurance Portability and Accountability Act (HIPAA)–compliant data backup and recovery services for businesses and individuals.
“How we deliver actionable insights to business users was science fiction 10 years ago,” says Matthew DiAntonio, vice president, business analytics, at Carbonite. “Now it’s fact.” To win and retain customers, Carbonite strives to maximize the impact of its marketing spend and understand every step of a long and complex customer journey through online and offline touch points. A data-driven, lifecycle-measurement strategy, backed by cloud-based IBM® Digital Analytics software, helps deliver key metrics on customer acquisition and retention directly to decision makers on mobile devices.
Business-to-business integration and analytics
Hirschvogel Inc. makes metal components for the automotive industry.4 The company needed translation services between electronic data interchange (EDI) X.12 documents and SAP Intermediate Documents (IDocs) to enable automatic processing of e-commerce with its US customers. By providing cloud-based integration with the Hirschvogel Inc. enterprise resource planning (ERP) system, the solution is designed to improve visibility into the company's supply chain, which enabled the organization to plan production processes based on the needs of its customers.
In addition, the increased visibility enabled the company to capture customer orders quickly so it could plan production accordingly. As a result, customer satisfaction can be enhanced and costs can be reduced. “The decision to outsource our B2B was simple because we knew the return on investment would occur instantly,” says Nico Schuetz, lead IT technician at Hirschvogel Inc. “The IBM Sterling Commerce® solution was 90 percent less expensive than our in-house option.”
Cloud network diagnostics
The Network Operations Center staff at Consolidated Communications Holdings, Inc. know that minor network problems can often turn into major problems that disrupt service.5 As a result, proactively detecting unusual network behavior is of paramount importance. However, manually setting thresholds and alerts required considerable time and effort, and did not provide enough early warning for staff to prevent operational problems.
Consolidated found that setting thresholds to identify network problems required extensive time and effort, and often identified problems only when they occurred, which was too late to prevent business impact. By implementing IBM SmartCloud Analytics software, Consolidated expects to avoid business disruptions and help eliminate manual thresholds, which can result in an annual savings of USD300,000.
Scalable cloud analytics
Miami-Dade, one of the largest counties in Florida, has a population of three million citizens and includes the city of Miami, a major tourist destination that welcomes more than 38 million visitors each year.6 The county’s administration provides a wide range of public services, including police and fire departments, dive rescue, water and sewer systems, garbage collection, parks, libraries, hospitals, and many others.
Miami-Dade County saw an opportunity to open up government with a large-scale analytics platform that would allow both internal end users and citizens to access a wealth of public information through the web. The county deployed IBM Cognos® Business Intelligence software in a Linux environment on its existing IBM System z® mainframe platform. Employees and citizens can access reports using a standard web browser. The solution provides 24/7 access to analytics for key services such as courts, jails, and the fire department. Its scalable platform offers insight into government for the county’s citizens.
Public sentiment analysis
The University of Southern California (USC) Annenberg Innovation Lab wanted to uncover insights buried in millions of daily online conversations.7 Through a sentiment-analytics project using IBM big data solutions, USC scholars captured and analyzed millions of Twitter tweets, Facebook posts, and other social media conversations to help uncover trends almost immediately. They were able to demonstrate the impact of a television ad within a day of its airing, helped show in near-real time the sentiment of debate viewers, and expected to enable nations to gain early notice of emerging health crises or civil unrest.
The capability of implementing cloud-delivered analytics of big data repositories without requiring an up-front investment in on-premises infrastructure can open an array of opportunities for organizations across a wide swath of industries. Look for an upcoming feature that focuses on integration patterns for cloud analytics.
Please share any thoughts or questions in the comments.
1 “Cloud Analytics: Derive Insight Without On-Premises Infrastructure,” by Ahmed Fattah, IBM Data magazine, August 2014.
2 “Cloud Analytics: A Taxonomy for Service Offerings,” by Ahmed Fattah, IBM Data magazine, August 2014.
3 Carbonite, IBM case study, March 2014.
4 Hirschvogel Inc., IBM case study, October 2013.
5 Consolidated Communications Holdings, Inc., IBM case study, October 2013.
6 Miami-Dade County Builds a Highly Scalable Private Cloud Analytics Platform, IBM case study, August 2012.
7 University of Southern California Annenberg Innovations Lab, IBM case study, February 2013.