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Oracle is one of the world’s largest business intelligence and analytics software companies. Its products range from middleware, back-end databases and ETL tools to business intelligence applications and cloud platforms, and it is well established in many corporate and government accounts. A key to Oracle’s ongoing success is in transitioning its business intelligence and analytics portfolio to self-service, big data and cloud deployments. To that end, three areas in which the company has innovated are fast, scalable access for transaction data; exploratory data access for less structured data; and cloud-based business intelligence.

 Providing users with access to structured data in an expedient and governed fashion continues to be a necessity for companies. Our benchmark research into information optimization finds drilling into information within applications (37%) and search (36%) to be the capabilities most needed for end users in business.

To provide them, Oracle enhanced its database in version Oracle 12c, which was  released in 2013 . The key innovation is to enable both transaction processing and analytic processing workloads on the same system.MostImportantEndUseCapUsing in-memory instruction sets on the processor, the system can run calculations quickly without changing the application data. The result is that end users can explore large amounts of information in the context of all data and applications running on the 12c platform. These applications include Oracle’s growing cadre of cloud based applications. The value of this is evident in our big data analytics benchmark research , which finds that the number-one source of big data is transactional data from applications, mentioned by 60 percent of participants.

 Search and interactive analysis of structured data are addressed by Oracle Business Intelligence Enterprise Edition (OBIEE) through a new visualization interface that applies assets Oracle acquired from Endeca in 2011. (Currently, this approach is available in Business Intelligence Cloud Service, which I discuss below.) To run fast queries of large data sets, columnar compression can be implemented by small code changes in the Oracle SQL Developer interface. These changes use the innovation in 12c discussed above and would be implemented by users familiar with SQL. Previously, IT professionals would have to spend significant time to construct aggregate data and tune the database so users could quickly access data. Otherwise transactional databases take a long time to query since they are row-oriented and the query literally must go through every row of data to return analytic results. With columnar compression, end users can explore and interact with data in a much faster, less limited fashion. With the new approach, users no longer need to walk down each hierarchy but can drag and drop or right-click to see the hierarchy definition. Drag-and-drop and brushing features enable exploration and uniform updates across all visualizations on the screen. Under the covers,

 DefiningBDAnalyticsthe database is doing some heavy lifting, often joining five to 10 tables to compute the query in near real time. The ability to do correlations on large data sets in near real time is a critical enabler of data exploration since it allows questions to be asked and answered one after another rather than asking users to predefine what those questions might be. This type of analytic discovery enables much faster time to value especially when providing root-cause analysis for decision-making.

 Oracle also  provides Big Data SQL , a query approach that enables analysis of unstructured data analysis on systems such as Hadoop. The model uses what Oracle calls query franchising rather than query federation in which, processing is done in a native SQL dialect and the various dialects must be translated and combined into one. With franchising, Oracle SQL runs natively inside of each of the systems. This approach applies Oracle SQL to big data systems and offloads queries to the compute nodes or storage servers of the big data system. It also maintains the security and speed needed to do exploration on less structured data sources such as JSON, which the 12c database supports natively. In this way Oracle provides security and manageability within the big data environment. Looking beyond structured data is key for organizations today. Our research shows that analyzing data from all sources is how three-fourths (76%) of organizations define big data analytics.

 To visualize and explore big data, Oracle  offers Big Data Discovery , which browses Hadoop and NoSQL stores, and samples and profiles data automatically to create catalogs. Users can explore important attributes through visualization as well as using common search techniques. The system currently supports capabilities such as string transformations, variable grouping, geotagging and text enrichment that assist in data preparation. This is a good start to address exploration on big data sources, but to better compete in this space, Oracle should offer more usable interfaces and more capabilities for both data preparation and visualization. For example, visualizations such as decision trees and correlation matrices are important to help end users to make sense of big data and do not appear to be included in the tool.

 The third analytic focus, and the catalyst of the innovations discussed above, is Oracle’s move to the cloud. In September 2014,  Oracle released BI Cloud Service  (BICS), which helps business users access Oracle BI systems in a self-service manner with limited help from IT. Cloud computing has been a major priority for Oracle in the past few years with not just its applications but also for its entire stack of technology. With BICS, Oracle offers a stand-alone product with which a departmental workgroup can insert analytics directly into its cloud applications. When BICS is coupled with the Data-as-a-Service (DaaS) offering, which accesses internal data as well as third-party data sources in the cloud, Oracle is able to deliver cross-channel analysis and identity-as-data. Cross-channel analysis and identity management are important in cloud analytics from both business and a privacy and security perspectives.

 CustomerAnalyticsIn particular, such tools can help tie together and thus simplify the complex task of managing multichannel marketing. Availability and simplicity in analytics tools are priorities for marketing organizations.  Our research into next-generation customer analytics  shows that for most organizations data not being readily available (63%) and difficulty in maintaining customer analytics systems (56%) are top challenges.

 Oracle is not the first vendor to offer self-service discovery and flexible data preparation, but BICS begins its movement from the previous generation of BI technology to the next. BICS puts Oracle Transactional Business Intelligence (OTBI) in the cloud as a first step toward integration with vertical applications in the lines of business. It lays the groundwork for cross-functional analysis in the cloud.

 We don’t expect BICS to compete immediately with more user-friendly analytic tools designed for business and analytics or with well-established cloud computing BI players. Designers still must be trained in Oracle tools, and for this reason, it appears that the tool, at least in its first iteration, is targeted only at Oracle’s OBIEE customers seeking a departmental solution that limits IT involvement. Oracle should continue to address usability for both end users and designers. BICS also should connect to more data sources including Oracle Essbase. It currently comes bundled with  Oracle Database Schema Service  which acts as the sole data source but does not directly connect with any other database. Furthermore, data movement is not streamlined in the first iteration, and replication of data is often necessary.

 Overall, Oracle’s moves in business intelligence and analytics make sense because they use the same semantic models in the cloud as those analytic applications that many very large companies use today and won’t abandon soon. Furthermore, given Oracle’s growing portfolio of cloud applications and the integration of analytics into these transactional applications through OTBI, Oracle can leverage cloud application differentiation for companies not using Oracle. If Oracle can align its self-service discovery and big data tools with its current portfolio in reasonably timely fashion, current customers will not turn away from their Oracle investments. In particular, those with an Oracle centric cloud roadmap will have no reason to switch. We note that cloud-based business intelligence and analytics applications is still a developing market. Our previous research showed that business intelligence had been a laggard in the cloud in comparison to genres such as human capital management, marketing, sales and customer service. We are examining trends in our forthcoming  data and analytics in the cloud benchmark research, which will evaluate both the current state of such software and where the industry likely is heading in 2015 and beyond. For organizations shifting to cloud platforms, Oracle has a very progressive cloud computing portfolio that  my colleague has assessed  and they have created a path by investing in its Platform-as-a-Service (PaaS) and DaaS offerings. Its goal is to provide uniform capabilities across mobility, collaboration, big data and analytics so that all Oracle applications are consistent for users and can be extended easily by developers. However, Oracle competes against many cloud computing heavyweights like Amazon Web Services, IBM and Microsoft, so achieving success through significant growth has some challenges. Oracle customers generally and OBIEE customers especially should investigate the new innovations in the context of their own roadmaps for big data analytics, cloud computing and self-service access to analytics.

 Regards,

Ventana Research

Oracle is one of the world’s largest business intelligence and analytics software companies. Its products range from middleware, back-end databases and ETL tools to business intelligence applications and cloud platforms, and it is well established in many corporate and government accounts. A key to Oracle’s ongoing success is in transitioning its business intelligence and analytics portfolio to self-service, big data and cloud deployments. To that end, three areas in which the company has innovated are fast, scalable access for transaction data; exploratory data access for less structured data; and cloud-based business intelligence.

 Providing users with access to structured data in an expedient and governed fashion continues to be a necessity for companies. Our benchmark research into information optimization finds drilling into information within applications (37%) and search (36%) to be the capabilities most needed for end users in business.

To provide them, Oracle enhanced its database in version Oracle 12c, which was  released in 2013 . The key innovation is to enable both transaction processing and analytic processing workloads on the same system.MostImportantEndUseCapUsing in-memory instruction sets on the processor, the system can run calculations quickly without changing the application data. The result is that end users can explore large amounts of information in the context of all data and applications running on the 12c platform. These applications include Oracle’s growing cadre of cloud based applications. The value of this is evident in our big data analytics benchmark research , which finds that the number-one source of big data is transactional data from applications, mentioned by 60 percent of participants.

 Search and interactive analysis of structured data are addressed by Oracle Business Intelligence Enterprise Edition (OBIEE) through a new visualization interface that applies assets Oracle acquired from Endeca in 2011. (Currently, this approach is available in Business Intelligence Cloud Service, which I discuss below.) To run fast queries of large data sets, columnar compression can be implemented by small code changes in the Oracle SQL Developer interface. These changes use the innovation in 12c discussed above and would be implemented by users familiar with SQL. Previously, IT professionals would have to spend significant time to construct aggregate data and tune the database so users could quickly access data. Otherwise transactional databases take a long time to query since they are row-oriented and the query literally must go through every row of data to return analytic results. With columnar compression, end users can explore and interact with data in a much faster, less limited fashion. With the new approach, users no longer need to walk down each hierarchy but can drag and drop or right-click to see the hierarchy definition. Drag-and-drop and brushing features enable exploration and uniform updates across all visualizations on the screen. Under the covers,

 DefiningBDAnalyticsthe database is doing some heavy lifting, often joining five to 10 tables to compute the query in near real time. The ability to do correlations on large data sets in near real time is a critical enabler of data exploration since it allows questions to be asked and answered one after another rather than asking users to predefine what those questions might be. This type of analytic discovery enables much faster time to value especially when providing root-cause analysis for decision-making.

 Oracle also  provides Big Data SQL , a query approach that enables analysis of unstructured data analysis on systems such as Hadoop. The model uses what Oracle calls query franchising rather than query federation in which, processing is done in a native SQL dialect and the various dialects must be translated and combined into one. With franchising, Oracle SQL runs natively inside of each of the systems. This approach applies Oracle SQL to big data systems and offloads queries to the compute nodes or storage servers of the big data system. It also maintains the security and speed needed to do exploration on less structured data sources such as JSON, which the 12c database supports natively. In this way Oracle provides security and manageability within the big data environment. Looking beyond structured data is key for organizations today. Our research shows that analyzing data from all sources is how three-fourths (76%) of organizations define big data analytics.

 To visualize and explore big data, Oracle  offers Big Data Discovery , which browses Hadoop and NoSQL stores, and samples and profiles data automatically to create catalogs. Users can explore important attributes through visualization as well as using common search techniques. The system currently supports capabilities such as string transformations, variable grouping, geotagging and text enrichment that assist in data preparation. This is a good start to address exploration on big data sources, but to better compete in this space, Oracle should offer more usable interfaces and more capabilities for both data preparation and visualization. For example, visualizations such as decision trees and correlation matrices are important to help end users to make sense of big data and do not appear to be included in the tool.

 The third analytic focus, and the catalyst of the innovations discussed above, is Oracle’s move to the cloud. In September 2014,  Oracle released BI Cloud Service  (BICS), which helps business users access Oracle BI systems in a self-service manner with limited help from IT. Cloud computing has been a major priority for Oracle in the past few years with not just its applications but also for its entire stack of technology. With BICS, Oracle offers a stand-alone product with which a departmental workgroup can insert analytics directly into its cloud applications. When BICS is coupled with the Data-as-a-Service (DaaS) offering, which accesses internal data as well as third-party data sources in the cloud, Oracle is able to deliver cross-channel analysis and identity-as-data. Cross-channel analysis and identity management are important in cloud analytics from both business and a privacy and security perspectives.

 CustomerAnalyticsIn particular, such tools can help tie together and thus simplify the complex task of managing multichannel marketing. Availability and simplicity in analytics tools are priorities for marketing organizations.  Our research into next-generation customer analytics  shows that for most organizations data not being readily available (63%) and difficulty in maintaining customer analytics systems (56%) are top challenges.

 Oracle is not the first vendor to offer self-service discovery and flexible data preparation, but BICS begins its movement from the previous generation of BI technology to the next. BICS puts Oracle Transactional Business Intelligence (OTBI) in the cloud as a first step toward integration with vertical applications in the lines of business. It lays the groundwork for cross-functional analysis in the cloud.

 We don’t expect BICS to compete immediately with more user-friendly analytic tools designed for business and analytics or with well-established cloud computing BI players. Designers still must be trained in Oracle tools, and for this reason, it appears that the tool, at least in its first iteration, is targeted only at Oracle’s OBIEE customers seeking a departmental solution that limits IT involvement. Oracle should continue to address usability for both end users and designers. BICS also should connect to more data sources including Oracle Essbase. It currently comes bundled with  Oracle Database Schema Service  which acts as the sole data source but does not directly connect with any other database. Furthermore, data movement is not streamlined in the first iteration, and replication of data is often necessary.

 Overall, Oracle’s moves in business intelligence and analytics make sense because they use the same semantic models in the cloud as those analytic applications that many very large companies use today and won’t abandon soon. Furthermore, given Oracle’s growing portfolio of cloud applications and the integration of analytics into these transactional applications through OTBI, Oracle can leverage cloud application differentiation for companies not using Oracle. If Oracle can align its self-service discovery and big data tools with its current portfolio in reasonably timely fashion, current customers will not turn away from their Oracle investments. In particular, those with an Oracle centric cloud roadmap will have no reason to switch. We note that cloud-based business intelligence and analytics applications is still a developing market. Our previous research showed that business intelligence had been a laggard in the cloud in comparison to genres such as human capital management, marketing, sales and customer service. We are examining trends in our forthcoming  data and analytics in the cloud benchmark research, which will evaluate both the current state of such software and where the industry likely is heading in 2015 and beyond. For organizations shifting to cloud platforms, Oracle has a very progressive cloud computing portfolio that  my colleague has assessed  and they have created a path by investing in its Platform-as-a-Service (PaaS) and DaaS offerings. Its goal is to provide uniform capabilities across mobility, collaboration, big data and analytics so that all Oracle applications are consistent for users and can be extended easily by developers. However, Oracle competes against many cloud computing heavyweights like Amazon Web Services, IBM and Microsoft, so achieving success through significant growth has some challenges. Oracle customers generally and OBIEE customers especially should investigate the new innovations in the context of their own roadmaps for big data analytics, cloud computing and self-service access to analytics.

 Regards,

Ventana Research

Responding to the trend that businesses now ask less sophisticated users to perform analysis and rely on software to help them, Oracle recently announced a new release  of its flagship Oracle BI Foundational Suite (OBIFS 11.1.1.7) as well as updates to Endeca, the discovery platform that Oracle bought in 2011. Endeca is part of a new class of tools that bring new capabilities in information discovery, self-service access and interactivity. Such approaches represent an important part of the evolution of business intelligence to business analytics as I have noted in my agenda for 2013.

Oracle Business Intelligence Foundational Suite includes many components not limited to Oracle Business Intelligence Enterprise Edition (OBIEE), Oracle Essbase and a scorecard and strategy application. OBIEE is the enabling foundation that federates queries across data sources and enables reporting across multiple platforms. Oracle Essbase is an in-memory OLAP tool that enables forecasting and planning, including what-if scenarios embedded in a range of Oracle BI Applications, which are sold separately. The suite, along with the Endeca software, is integrated with Exalytics, Oracle’s appliance for BI and analytics. Oracle’s appliance strategy, which I wrote about after Oracle World last year invests heavily in the Sun Microsystems hardware acquired in 2010.

These updates are far-ranging and numerous (including more than 200 changes to the software). I’d like to point out some important pieces that advance Oracle’s position in the BI market. A visualization recommendations engine offers guidance on the type of visualization that may be appropriate for a user’s particular data. This feature, already sold by others in the market, may be considered a subset of the broader capability of guided analysis. Advanced visualization techniques have become more important for companies as they make it easier for users to understand data and is critical to compete with the likes of  Tableau, a player in this space which I wrote about last year.

Another user-focused update related to visualization is performance tiles, which enable important KPIs to be displayed prominently within the context of the screen surface area. Performance tiles are a great way to start improving the static dashboards that my colleague Mark Smith has critiqued. From what I have seen it is unclear to what degree the business user can define and change Oracle’s performance tile KPIs (for example, the red-flagged metrics assignedvr_bigdata_big_data_capabilities_not_available to the particular business user that appear within the scorecard function of the software) and how much the system can provide in a prescriptive analytic fashion. Other visualizations that have been added include waterfall charts, which enable dependency analysis; these are especially helpful for pricing analysis by showing users how changes in one dimension impact pricing on the whole. Another is MapViews for manipulation and design to support location analytics that our next generation BI research finds the capability to deploy geographic maps are most important to BI in 47 percent of organizations, and then visualize metrics associated with locations in 41 percent of organizations. Stack charts now provide auto-weighting for 100-percent sum analysis that can be helpful for analytics such as attribution models. Breadcrumbs empower users to understand and drill back through their navigation process, which helps them understand how a person came to a particular analytical conclusion. Finally Trellis View actions provides contextual functionality to help turn data into action in an operational environment. The advancements of these visualizations are critical for Oracle big data efforts as visualization is a top three big data capability not available in 37 percent of organizations according to our big data research and our latest technology innovation research on business analytics found presenting data visually as the second most important capability for organizations according to 48 percent of organizations.

vr_ngbi_br_collaboration_tool_access_preferencesThe update to Oracle Smart View for Office also puts more capability in the hands of users. It natively integrates Excel and other Microsoft Office applications with operational BI dashboards so users can perform analysis and prepare ad-hoc reports directly within these desktop environments. This is an important advance for Oracle since our benchmark research in the use of spreadsheets across the enterprise found that the combination of BI and spreadsheets happens all the time or frequently in 74 percent of organization. Additionally the importance of collaborating with business intelligence is essential and having tighter integration is a critical use case as found in our next generation business intelligence research that found using Microsoft Office for collaboration with business intelligence is important to 36 percent of organizations.

Oracle efforts to evolve its social collaboration efforts through what they call Oracle Social Network have advanced significantly but do not appear to be in the short term plan to integrate and make available through its business intelligence offering. Our research finds more than two-thirds (67%) rank this as important and then embedding it within BI is a top need in 38 percent of organizations. Much of what Oracle already provides could be easily integrated and meet business demand for a range of people-based interactions that most are still struggling to manage through e-mail.

Oracle has extended its existing capabilities in its OBIEE with Hadoop integration via a HIVE connector that allows Oracle to pull data into OBIEE from big data sources, while an MDX search function enabled by integration with the Endeca discovery tool allows OBIEE to do full text search and data discovery. Connections to new data sources are critically important in today’s environment; our research shows that retaining and analyzing more data is the number-one ranked use for big data in 29 percent of organizations according to our technology innovation research. Federated data discovery is particularly important as most companies are often unaware of their information assets and therefore unknowingly limit their analysis.

Beyond the core BI product, Oracle made significant advances with Endeca 3.0. Users can now analyze Excel files. This is an existing capability for other vendors, so it was important for Oracle to gain parity here. Beyond that, Endeca now comes with a native JavaScript Object Notation (JSON) reader and support for authorization standards. This furthers its ability to do contextual analysis and sentiment analysis on data in text and social media. Endeca also now can pull data from the Oracle BI server to marry with the analysis. Overall the new version of Endeca enables new business-driven information discovery that is essential to relieve the stress on analysts and IT to create and publish information and insights to business.

Oracle’s continued investments into BI applications that supply prebuilt analytics and these packaged analytics applications span from the front office (sales and marketing), to operations (procurement and supply chain) to the back office (finance and HR). Given the enterprise-wide support, Oracle’s BI can perform cross-functional analytics and deliver fast time to value since users do not have to spend time building the dashboards. Through interoperation with the company’s enterprise applications, customers can execute action directly into applications such as PeopleSoft, JD Edwards or Oracle Business Suite. Oracle has begun to leverage more of its score-carding function that enables KPI relationships to be mapped and information aggregated and trended. Scorecards are important for analytic cultures because they are a common communication platform for executive decision-makers and allow ownership assignment of metrics.

I was surprised to not find much advancement in Oracle business intelligence efforts that operate on smartphones and tablets. Our research finds mobile business intelligence is important to 69 percent of organizations and that 78 percent of organizations reveal that no or some BI capabilities are available in their current deployment of BI. For those that are using mobile business intelligence, only 28 percent are satisfied. For years, IT has not placed a priority on mobile support of BI while business has been clamoring for it and now more readily leading the efforts with 52 percent planning new or expanded deployments on tablets and 32 percent on smartphones. In this highly competitive market to capture more opportunity, Oracle will need to significantly advance its efforts and make its capabilities freely available without passwords as other BI providers have already done. It also will need to recognize that business is more interested in alerts and events through notifications to mobile technology than trying to make the entire suite of BI capabilities replicated on these technologies.

Oracle has foundational positions in enterprise applications and database technology and has used these positions to drive significant vr_ngbi_br_importance_of_bi_technology_considerationssuccess in BI. The company’s proprietary “walled garden” approach worked well for years, but now technology changes, including movements toward open source and cloud computing, threaten that entrenched position. Surprisingly, the company has moved slowly off of its traditional messaging stance targeted at the CIO, IT and the data center. That position seems to focus the company too much on the technology-driven 3 V’s of big data and analytics, and not enough on the business driven 3 W’s that I advocate. As the industry moves into the age of analytics, where information is looked upon as a critical commodity and usability is the key to adoption (our research finds usability to be the top evaluation consideration in 63 percent of organizations), CIOs will need to further move beyond its IT approach for BI as I have noted and get more engaged into the requirements of business. Oracle’s business intelligence strategy and how it addresses these business outcomes and the use across all business users is key to the company’s future and organizations should examine these critical advancements to its BI offering very closely to determine if you can improve the value of information and big data in an organization.

Regards,

Tony Cosentino

VP and Research Director

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