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The market for big data continues to grow as organizations try to extract business value from their own masses of data and other sources. Earlier this year I outlined the dynamics of the business opportunity for big data and information optimization. We continue to see advances as big data and associated information technologies deliver more value, but the range of innovation also has created fragmentation among existing systems including databases that are managed onpremises or in cloud computing environments. In this changing environment organizations encounter new challenges not only in adapting to technology that is more efficient in automating data processing but also in integrating it into their enterprise architecture. I’ve already explained how big data can be ineffective without integration, and we conducted more in-depth research into the market, resulting in our benchmark research on big data integration, which reveals the state of how organizations are adopting this technology in their processes.
The research shows that use of big data techniques has become widespread: Almost half (48%) of all organizations participating in this research and two-thirds of the very large ones use it for storage, and 45 percent intend to use big data in the next year or sometime in the future. This is a significant change in that most organizations have used relational database management systems (RDBMSs) for nearly everything. We find that RDBMSs (76%) are still the most widely used big data technology, followed by flat files (61%) and data warehouse appliances (46%). But this is not the direction many companies are planning to take in the future: Hadoop (44%), in-memory database (46%), specialized databases (43%) and NoSQL (42%) are the tools most often planned to be used by 2016 or being evaluated. Clearly there is a revolution in approaches to storing and using data, and that introduces both opportunities and challenges.
Establishing a big data environment requires integrating data through proper preparation and potentially continuous updates of data, whether in real time or batch processing. A further complication is that many organizations will not have only one but several big data environments to be integrated into the overall enterprise architecture; that requires data and systems integration. Our research finds that some organizations are aware of this issue: Automating big data integration is very important to 45 percent and important to more than one-third. Automation can not only bring efficiency to big data but also remove many risks of errors or inaccurate and inconsistent data.
Data integration technologies have evolved over the past decade, but advances to support big data are more recent. Our research shows a disparity in how well organizations handle big data integration tasks. Those that are mostly or completely adequate are accessing (for 63%), loading (60%), extracting (59%), archiving (55%) and copying (52%) data while the areas most in need of improvement are virtualizing (39%), profiling (37%), blending (34%), master data management (33%) and masking for privacy (33%). At the system level, the research finds that conventional enterprise capabilities are most often needed: load balancing (cited by 51%), cross-platform support (47%), a development and testing environment (42%), systems management (40%) and scalable execution of tasks (39%). To test the range of big data integration capabilities before it is applied to production projects, the “sandbox” has become the standard approach. For their development and testing environment, the largest percentage (36%) said they will use an internal sandbox with specialized big data. This group of findings reveals that big data integration has enterprise-level requirements that go beyond just loading data to build on advances in data integration.
Big data must not be a separate store of data but part of the overall enterprise and data architecture; that is necessary to ensure full integration and use of the data. Organizations that see data integration as critical to big data are embarking on sophisticated efforts to achieve it. The data integration capabilities most critical to their big data efforts are to develop and manage metadata that can be shared across BI systems (cited by 58%), to join disparate data sources during transformation (56%) and to establish rules for processing and routing data (56%).
Other organizations are still examining how to automate integration tasks. The most common barriers to improving big data integration are cost of the software or license (for 44%), lack of resources to use on improvement (37%) and the sense that big data technologies are too complicated to integrate (35%). These findings demonstrate that many organizations need to better understand the efficiency and cost savings that can be realized by using purpose-built technology instead of manual approaches using tools not designed for big data. Along with identifying solid business benefits, establishing savings of time and money are essential pieces of a convincing rationale for investment in big data integration technology. The most time spent in big data integration today is on basic tasks: reviewing data for quality and consistency (52%), preparing data for integration (46%) and connecting to data sources for integration (39%). The first two are related to ensuring that data is ready to load into big data environments. Data preparation is a key part of big data and overall information optimization. More vendors are developing dedicated technology to help with it.
For a process as complex as big data integration, choosing the right technology tool can be difficult. More than half (55%) of organizations are planning to change the way they assess and select such technology. Evaluations of big data integration tools should include considerations of how to deploy it and what sort of vendors can provide it. Almost half (46%) of organizations prefer to integrate big data on-premises while 28 percent opt for cloud-based software as a service and 17 percent have no preference. Half of organizations plan to use cloud computing for managing big data; another one-third (32%) don’t know whether they will. The research shows that the most important technology and vendor criteria used to evaluate big data integration technology are usability (very important for 53%), reliability (52%) and functionality (49%). These top three evaluation criteria are followed by manageability, TCO/ROI, adaptability and validation of vendors. Organizations are most concerned to have technology that is easy to use and can scale to meet their needs.
Big data cannot be used effectively without integration; we observe that the big data industry has not paid as much attention to information management as it should – after all, this is what enables automating the flow of data. Organizations trying to use big data without a focus on information management will have difficulty in optimizing the use of their data assets for business needs. Our research into big data integration finds that the proper technology is critical to meet these needs. We also learned from our benchmark research into big data analytics that data preparation is the largest and most time-consuming set of tasks that needs to be streamlined for best use of the analytics that reveal actionable insights. Organizations that are initiating or expanding their big data deployments whether onpremises or within cloud computing environments should have integration at the top of their priority list to ensure they do not create silos of data that they can’t fully exploit.
CEO and Chief Research Officer
At its Oracle OpenWorld the multibillion technology provider showcased the breadth and depth of its cloud computing applications and platform. Chairman Larry Ellison proclaimed it the only unified and open approach in the industry. He criticized other large application vendors that use multiple platforms to support their applications, use a proprietary layer that is not fully extensible, provide only a portion of applications needed to run the business or run on Oracle’s database technology. These technical merits may not be relevant to the decision-making processes of business but can be critical for CIO and IT. But the strength of the Oracle Cloud Computing portfolio, which includes infrastructure, platform, tools and applications, is so impressive that our firm awarded Oracle the Technology Innovation Award in Cloud Computing for 2014. This builds from my analysis earlier in the year on the overall efforts of Oracle for cloud computing.
Oracle’s cloud application portfolio spans many areas of business, including human capital management, which my colleague Stephan Millard has analyzed. Its sales application portfolio also has reached a high level of maturity. Its efforts for sales organizations go beyond sales force automation (SFA) for sales reps and managers to other applications for those roles and sales operations and executives as well. In the years since its acquisition of Siebel Systems, Oracle’s position in this market slipped as nemesis salesforce.com became a major player. Now it not only has climbed back into a competitive position but has a more complete sales portfolio than salesforce at a more affordable price.
At Oracle OpenWorld it announced highlights of its advancements in sales. Oracle Sales Cloud version 9 advances sales force automation, partner relationship management and sales performance management along with adding support for mobile and social collaboration technology and sales analytics for roles from executives to front-line sales teams. The greatest changes as I see it are in the sophistication and usability of the sales applications and the embedding of analytics and collaboration that make them faster and easier to use. Oracle has ensured that the new versions are backward-compatible with previous iterations and integrated them with on-premises legacy systems such as Siebel and its own Oracle E-Business Suite to help customers that have mixed environments operate now and will migrate in the future.
Oracle has redesigned its approach to sales to focus on productivity enhancements in tasks related to meeting customers and updating information in more user-centric ways than most SFA systems have. For example, a new mobile application yet to be released, Oracle Sales Cloud Call Report App, enables smartphone users to review and update sales opportunities quickly and easily and to immediately see the impact of changes to forecasts and quotas. In a second area, collaborative selling, Oracle Sales Cloud Mobile is easy to use on smartphones and tablets, but still could improve in being more task and workflow based and be more optimized for touch gestures. In another area, however, Oracle has advanced beyond others: Oracle Voice users can interact verbally with the application to engage in sales at any time and place, even while driving. To reach this unique position Oracle partners with Nuance, as was announced earlier this year. It works on Apple iOS platform to enable a range of tasks to be conducted through voice operations.
Oracle knows that sales prospecting requires robust information that often exists outside the enterprise and across the Internet. To make it easier to get data from partners such as Dun & Bradstreet, the company announced Oracle Data as a Service (DaaS) for Sales, which enriches data with more than 150 attributes about organizations and 100 attributes about individuals. This product takes advantage of Oracle’s acquisition of BlueKai, which provides a marketplace for organizations to share and license data for use within their business. Oracle Data as a Service is a significant component of Oracle’s cloud computing platform and will be valuable for sales organizations.
In recent years sales organizations have become able to automate configuring products and quoting prices by adopting configure price quote (CPQ) software and integrating it with SFA to support interactions with customer prospects. Oracle’s acquisition of Big Machines complements the Oracle Sales Cloud by eliminating the need for a separate application that might not be integrated into the sales process. The company does market Oracle CPQ Cloud as a separate offering, but it is clearly part of the sales portfolio. The next step for Oracle in this area should be to enhance its portfolio for contract automation, which is a challenge that causes sales people and operations to spend significant time in creating a process and workflow of documents that legally define purchases, deliveries and invoicing.
Another key component is Oracle Sales Cloud Sales Performance Management. It uses analytics to manage and improve sales performance with applications designed for coaching and territory optimization. It also has a new mobile application for monitoring sales contests among teams in which progress toward quotas and goals can easily be seen and reviewed. Our firm takes a broad view of sales performance management to include operations, tasks and all sales processes; Oracle’s application is limited to gaining knowledge from analytics on sales activities. For other users seeking to manage sales compensation in general and the unique elements of incentive compensation the vendor has advanced from Oracle E-Business Suite Talent Management to Oracle Workforce Rewards, which includes compensation, benefits and payroll management as part of the Oracle Human Capital Management Cloud. Our benchmark research finds that the process of sales compensation continues to be an issue for almost two-thirds (65%) of organizations; it affects sales operations and executives along with individual sales reps, and for many it is a priority to improve.
Oracle has also expanded its analytics offerings for business. A relevant one here is Oracle Transactional BI Enterprise (OTBIE) for CRM, which provides a portfolio of analytics for forecasts, the pipeline and accounts and helps users understand past performance and predict the future. Analytics of the sales forecast and pipeline is another priority for sales; our research shows that scattered and inconsistent information are the top two impediments that drive about half of organizations to invest further in sales management systems. Oracle’s analytics build on its experience in providing operational reporting capabilities in Oracle Transactional BI Standard, which can present a range of metrics for insights on activities. New advances in sales analytics are evident in Oracle Mobilytics, which provides a sophisticated view of sales activities that can become interactive through visualization. There is also Oracle Sales Cloud Sales Predictor, which helps guide sales people on which products are most likely to be purchased. Overall Oracle has advanced the analytics in its cloud platform significantly this year. Recently it announced Oracle Analytics Cloud, which enhances its tools and the ability to access and embed them in Oracle applications.
As Oracle continues to advance its Sales Cloud, the products are less of a challenge than recognition of the company by customers as a leader in these sales applications. To be competitive in the market will require further investments in marketing and sales to gain momentum and customer adoption but also to continue to expanding the application portfolio. For the Sales Cloud Oracle currently charges $100 per user per month and considering the breadth of applications and analytics, this could be seen as very competitive; salesforce.com starts at $65 per user per month for the basic SFA, but the recently announced Salesforce Analytics Cloud will cost $125 per user per month of which both are significantly more costly. Others major application providers like SAP are also advancing similarly to Oracle for SFA and sales performance management but still have not been able to fulfill on the larger portfolio of application needs for sales operations and executives.
Oracle is a serious player in the market for sales applications and very price advantageous and innovative in its portfolio; we advise organizations to evaluate the company as one of the few that offers more than just SFA and operates in the cloud and mobile technology environment. If you are looking for an integrated suite of sales applications that can help everyone involved in sales, Oracle should be on your list for optimizing operations and maximizing sales performance.
CEO and Chief Research Officer,