2012: Year of Cloud BI
By Jeff Bamba, Database Architect, Blue Mountain Labs
This will be the year for rapid growth of cloud business intelligence (BI). Cloud computing was a big subject for customers and vendors to discuss in the early part 2010. More organizations --on the vendor side and their customers -- developed strategies to leverage cloud computing in 2011. In 2012, customers will focus on leveraging cloud computing solutions in data and information management; specifically BI and analytics.
Some vendors have already instantiated cloud BI solutions, quenching the appetite of customers to move their traditional "in-house" BI solutions into the cloud with the promise of reducing total cost of ownership (TCO) and increasing analytical capabilities. Small to mid-size (SMB) organizations made the move to cloud BI in 2011 in hopes of gaining a competitive advantage. This transition from “in-house” BI to the cloud was, for the most part, enabled by vendors focusing on data marts in support of specific functional information domains (i.e., sales, inventory, etc). With a strong customer appetite for cloud solutions, cloud BI adoption will continue in 2012.
Traditionally many organizations design, create, and maintain their BI capabilities in-house in order to leverage their information assets for competitive advantage. This requires customers to have resources, software licenses, and hardware to implement the technology, not to mention the ongoing operation and maintenance (O&M) expenses to support the BI capabilities lifecycle.
In the age of cost cutting in business, information technology (IT) costs are often seen as the first to be cut when companies need to reduce expenses. This does not mean that IT does not add value; however, IT is seen as an easy target. Thus, moving BI capabilities to the cloud will continue in 2012 because it is seen as an easy way to reduce IT costs.
Customers will continue there shift to the cloud helped in part by big vendors enabling their traditional BI solutions as a cloud offering in an attempt to capture more of the mid-size market. Additionally, the early adopters of cloud BI will realize the value of their investment and thus migrate more of their traditional BI solutions to the cloud.
Vendors will continue to crank out more features of their cloud BI offerings and refine the migration approach for customers to adopt cloud BI more efficiently. This will enable new customers to take advantage of cloud BI capabilities while building confidence with existing customers.
How Vendors Will Respond to Customer Demand
The increase in the number of customers moving to cloud BI will require a strong response from vendors to meet customer demands, which will focus on performance, functionality, mobility, ease of use, and ease of adoption. Some vendors will offer cloud BI products and services that target specific industries and vertical markets. These vendors will focus on specific cloud data marts and analytics that support vertical markets such as health care providers and retailers. Other vendors will focus their solutions on functional domains such as sales, human resources, and inventory management that cover multiple markets.
The big vendors will also respond to growing demand for cloud BI by enabling their current commercial, off-the-shelf (COTS) packages as a cloud solutions. The key to attracting SMB customers will be cost of entry and ease of adoption. Big vendors will need to streamline their products with pre-packaged solutions for specific vertical markets and functional information domains in order for SMB to quickly adopt the tools as cloud BI solutions.
Vendors will also need to argument their cloud BI solutions with professional services, minimizing the need for enterprises to have resources “in-house” for cloud migration projects and ongoing support. In general, all vendors of cloud BI must offer professional services as part of their model and offer ways to educate and transition customers to the cloud.
Key Success Areas for Customers
The mass influx of customers leveraging cloud BI will result in failure for some. Customers that succeed are those with information management principles in place before making the switch to cloud BI. These foundational principles include logical definition of information assets, identification of key performance indicators of organizational processes, identification and catalog of source systems for reporting, definition of data synchronization rules (with the cloud), and clearly defined user requirements. Customers should focus their efforts in the aforementioned areas before considering a cloud BI vendor and follow these best practices:
- Having these pieces in place ensures successful transition and acceptance of cloud BI by internal users. A clearly defined logical data model (LDM) allows customers to vet cloud BI solutions for available functionality and ease of mapping internal source systems data for reporting as well as data synchronization. It is the basis for your evaluation criteria -- logical data models (LDMs) cover the business rules and relationship of data needed for reporting and analytics.
- Key performance measures and metrics for determining performance of business processes should be established before embarking on cloud BI projects. This foundation information allows a customer to evaluate a cloud BI solution based on the business needs and questions expected from the end users.
- Advance identification and a catalog of source systems also ensure that analysis and transition of “in-house” BI capabilities to the cloud is targeted and focused. This information is critical in the data synchronization implementation exercise driven by source system data mapping to the cloud.
- As published by numerous research articles, a successful BI implementation is always dependent on user adoption of the system. As a result, time spent identifying a clear user requirement as the basis for evaluating a cloud BI solution is a must. Without such efforts, the adoption or transition to a cloud BI platform is not worth the money.
Limitations of Cloud BI Offerings
Enterprises must be cautious when transitioning to cloud BI. Customers need to understand the current limitations of cloud BI before taking the plunge. Customers need to understand the security topology of the cloud BI offering. They need to be aware of the BI integration challenges with existing systems and most importantly, customizations of the cloud BI solutions.
The biggest limitation of cloud BI offering is lack of data quality components in the cloud technology stack. It is the responsibility of customers to ensure that data quality issues are address before transitioning from “in-house” BI platform to a cloud BI solution. As with every system, the “junk in, junk out” principles apply. Customers should not expect the cloud BI platform to automatically address data quality; it should be a partnership between the customer and the cloud BI vendor to address the data quality challenges.
Cloud Data Mining
As more customers adopt cloud BI solutions, the evolutionary step is cloud BI analytics in the form of cloud data mining. This is one of the capabilities that early adaptors of cloud BI will be requesting from vendors in 2012. Cloud data mining in the form of SaaS (software-as-a-service) is already out by some vendors in beta form while other vendors have it in initial release.
Come 2012, more data mining models will be provided by vendors to enable cloud mining as customer data can easily transition from reporting in the cloud to analytics in the cloud. This is the frontier of cloud BI where vendors will help customers answer operation performance questions through reports and predict future operational performance based on past operational data in the cloud.
A Final Word
Cloud BI in 2012 is the area in cloud computing to watch. Organizations will flock to cloud BI to use the technology to improve performance, remediate risk and compliance reporting, and enable business analytics. Vendors will respond with a hybrid of options and choices to address customer needs. As more customers move their BI needs in to the cloud, cloud data mining will eventually be the must have capability by customers in 2012.
Jeff Bamba is a database architect at Blue Mountain Labs, a consultancy created to lead enterprises to the promises of cloud computing, including how to integrate existing enterprise systems with the cloud. Jeff can be reached at email@example.com