Cloud-based BI, the pros and cons

Transcription

1 Cloud-based BI, the pros and cons

2 IDC's most recent survey of the market found that half of businesses were considering BI in the cloud -- a far higher level of potential take-up than for cloud computing technologies overall. In this expert E-Guide, get insight into the factors driving interest in cloud analytics and the inherent advantages of cloud BI over on-premises BI systems, as well as the potential disadvantages to be aware of. By: Stephen Pritchard, Contributor As businesses struggle to process ever-larger volumes of data, the uptake of cloud-based business intelligence (BI) is expected to grow rapidly. Figures from market research firm IDC suggest that cloud analytics and BI deployments, though still a small part of the business intelligence market as a whole, will grow at three times the rate of conventional, on-premises BI systems through IDC's most recent survey of the market found that half of businesses were considering BI in the cloud -- a far higher level of potential take-up than for cloud computing technologies overall. Interest in cloud analytics is being driven by two main factors. First, companies are gathering and storing more data and want to make that data - - and BI reports -- available to more people in their organisations. Cloud analytics extends access to staff working on mobile devices, and potentially to suppliers and customers. It is also more "elastic" than conventional IT systems and can more readily offer more, or less, storage and processing capacity as required. That helps businesses deal not only with larger volumes of data overall, but also with data analytics tasks that have significant peaks in demand. Page 2 of 10

3 The cloud analytics cost advantage The second factor is the way that cloud-based analytics is reducing the cost of using business intelligence systems overall -- and thus bringing BI within reach of smaller businesses and startups. Using BI on demand, or through a cloud-based Software as a Service offering, reduces the up-front cost and possibly the total cost of ownership for an analytics system. Cloud systems also make financial sense for one-off analytics projects, as there is no ongoing cost of hardware or software once the work is complete. As a result, conventional BI and enterprise software vendors, as well as a number of startups, are offering business intelligence in the cloud. In addition, some technological developments, including Google's MapReduce framework for distributed data processing and the open source Apache Hadoop technology, are making it easier for vendors to build large-scale data analytics engines that take advantage of the scalability of the cloud. Systems such as Hadoop also make it easier to process and analyse unstructured data, such as information from documents or multimedia content; such content accounts for anywhere up to 80% of typical enterprise data, according to analyst estimates. The cloud BI challenge IT leaders, however, have to balance the advantages and potential of cloudbased analytics with the relative immaturity of the marketplace and some of the practical. Given the right skills, a business starting with a blank slate could well build analytics capabilities in the cloud. For a business looking to drive greater efficiencies and effectiveness from an existing installation of analytics tools, transferring workloads to the cloud will be less straightforward. "One immediate barrier is the complexity of the analytical models," said Greg Todd, an executive director in Accenture s analytics practice. Although cloudbased BI tools might have comparable capabilities to on-premises software, there will be sufficient differences at the technical level to require models to be rewritten, he suggested. Page 3 of 10

4 Nor can the cloud always match the performance of an on-premises system: businesses are increasingly using data warehouse and analytics appliances to help boost throughput, but few cloud services currently offer these. Businesses also need to consider data security and privacy and whether there is sufficient bandwidth and time to transfer significant quantities of data to the cloud provider for processing. That will depend as much on the workload, and the urgency of the analytical reporting, as the technology itself -- something chief information officerss and BI managers will have to assess in the context of their own businesses. Nonetheless, a "maturation of the market is underway," Todd said. "We are starting with basic information management and moving to predictive analytics and full-blown decision processes." Cloud analytics for social welfare provision Public sector IT provider Cipal -- which is run for a consortium of local authorities and government agencies in the Flemish portion of Belgium -- is using cloud-based analytics to help officials analyse and benchmark social welfare provision. The analytics service runs from a central data warehouse and is part of Cipal s strategy to offer all of its applications in the cloud. For data analytics, using the cloud is a practical solution for public sector organisations that lack the scale, expertise or budgets to deploy relatively complex technology on their own, according to Sven Meermans, Cipal's business development manager for business intelligence. "Many of our customers, especially the smaller municipalities and social welfare bodies, do not have the know-how, the budget or the infrastructure to set up their own BI solution," Meermans said. "We set up a centralised data warehouse at Cipal that enables all of our customers, not only the big organisations, to benefit from a complete BI suite." Deploying BI through a private cloud overcame both the skills and resources problems for government agencies, as well as making it easier for their users Page 4 of 10

5 to access BI data and reporting through a Web browser, he added. Cipal also chose open source BI technology, to allow for more flexible future development. A further benefit from using a cloud-based infrastructure is that Cipal can help local authorities to benchmark their services. By holding information in a central data warehouse and using standardised key performance indicators for services, it enables users to compare their performance with other municipalities. Local authorities, though, have historically not been heavy users of business intelligence, not least because of the cost. With Cipal's cloud-based system, Meermans expects that to change. "We realise that BI for most local government, for the moment, is a nice to have, but we are convinced this will evolve to be a need to have, and we want to be ready," he said. Private cloud for data analytics Mindshare UK, a media planning and buying subsidiary of advertising and marketing services firm WPP, also operates data analytics using a private cloud. The company takes a range of information, including planning data such as an advertising outlet's pricing and reach, as well as audience evaluation and emerging social media feeds, and makes them available to clients through a Web browser. Using a general-purpose BI tool -- as well as a cloud delivery model -- has a number of advantages for both Mindshare and its clients, said Andrew Corroll, head of data integration at the company. For example, it removes the need for clients to purchase and install specific media monitoring software packages, and it simplifies the security issues around allowing third-party access to data. "We can communicate [our data] with people without them having to download software to a machine, and they can access our reports from anywhere, via the Web," Corroll said. Page 5 of 10

6 Planned upgrades include bolstering the in-built analytics capability of the BI and adding shared third-party data to the system, so clients can compare their advertising campaigns with industry-standard metrics, without the need to leave the Mindshare application. By: Beth Stackpole, Contributor With traditional business intelligence initiatives sometimes taking up to 18 months to complete at costs that can run into the hundreds of thousands of dollars -- if they don t end up failing altogether -- it s no surprise that a stillsmall but growing number of organizations are eyeing cloud BI tools as a more cost-effective, fast-track approach. However, Software as a Service (SaaS) BI technology also has potential downsides or complicating factors that would-be users should factor into their thinking before committing to a deployment. First, the plus side: BI in the cloud, like other applications delivered via the SaaS model, promises a number of inherent advantages over on-premises systems. For starters, the cost of entry for SaaS business intelligence typically is much less expensive because companies trade the need to purchase software licenses and stock their data centers with new hardware for a pay-as-you-go monthly subscription model. In much the same vein, SaaS BI tools also hold out the promise of a lower total cost of ownership (TCO) over time because there are no systems to set up and manage internally, thus reducing demands on IT resources. Furthermore, industry analysts say that organizations usually can get up and running with cloud-based BI applications much more quickly than they can with on-premises systems -- often within three to four months, or even less time for small workgroup applications. Page 6 of 10

7 The economic downturn and continued tight IT budgets have also opened doors to SaaS BI that otherwise might have remained shut. The fact that there are lower up-front costs, that it s simpler to get started and that it s all operational expenses, so there s no need to capitalize anything, are big advantages right now and are not to be overlooked when evaluating the cloud, said William McKnight, president of McKnight Consulting Group LLC in Plano, Texas. Potential red flags for cloud BI tools On the flip side, cloud BI tools do have some drawbacks, particularly for organizations in industries that are highly regulated. For example, businesses in the health care or financial services industries, where there are strict rules governing privacy and how and where data is stored, might not be good candidates for SaaS BI, according to McKnight and other analysts. In addition, analysts caution that costs aren t always lower with SaaS BI. Factors such as hidden fees charged by vendors and the number of data sources that need to be integrated to feed the BI system can have a big impact on the final bill for a SaaS deployment, they said. There s a misnomer put out there that SaaS is always cheaper, and it s not, said Shawn Rogers, an analyst at Enterprise Management Associates Inc., a consulting and market research firm in Boulder, Colo. Companies have to do a TCO analysis to ensure that their particular project makes sense given the number of users and data integration issues. PSA Insurance & Financial Services Inc. didn t start with SaaS BI, but business intelligence in the cloud ended up being a better fit for its reporting needs than on-premises software was, according to Andrew Bartels, IT director at the Hunt Valley, Md.-based company. PSA initially deployed a traditional BI application but found it was expensive and difficult to manage, particularly when trying to integrate data across different information silos. Moreover, business users had to wait for IT to design and generate reports, creating a lag time in delivery that reduced the usefulness of the reports. Page 7 of 10

8 From my perspective, BI is slicing and dicing data on demand to better understand how the business is performing and to look at how it s performing in different ways, Bartels said. The time between reports was too long to be effective. By the time a business person got the report, the data was old, it could be wrong or it was missing fields. intelligence to the rescue The cloud BI tools, which PSA switched to two years ago, mitigated that by enabling business users to build their own reports. In addition, the SaaS application provided increased flexibility compared with the on-premises software: It can absorb any data I throw at it, and it allows me to create relationships between data so it s meaningful to the business, Bartels said. While data security was an initial hurdle given that PSA is in the financial industry, Bartels said a check on the SaaS BI vendor s security practices and consultation with PSA s compliance group eased his concerns. Security needs to be there, but the important thing is to do due diligence, he advised. When something is physically stored in the data center behind your firewalls and monitored by your own people, you have a sense of security. Whether it s a false sense, that s another question. The Association for Manufacturing Technology (AMT) is another SaaS BI user. The technology enables the AMT to deliver BI data and reporting services to its member organizations in a timely and scalable fashion, said Pat McGibbon, vice president of strategic information and research for the McLean, Va.-based trade group. Prior to its SaaS BI implementation earlier this year, the AMT served up monthly reports to members via the Web in PDFs or a comma-delimited file format. But now, McGibbon said, end users at member companies can create their own reports and dashboards, giving them much quicker access to data for analysis purposes. In addition, user upgrades at the member level are automatically handled without the need for any intervention by the AMT s IT workers, and the SaaS BI system can scale up to support more users without requiring the trade Page 8 of 10

9 group to invest in additional hardware or staffing. The ability to have a scalable product was a really positive thing, McGibbon said of the decision to go with SaaS BI. We could build this out for one person or a million people without making a $6 million investment in a data center. Beth Stackpole is a freelance writer who has been covering the intersection of technology and business for 25-plus years for a variety of trade and business publications and websites. Page 9 of 10

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