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Actuate, a company known for powering BIRT, the open source business intelligence technology, has been delivering large-scale consumer and industrial applications for more than 20 years. In December the company announced it would be acquired by OpenText of Ontario, Canada. OpenText is Canada’s largest software vendor with more than 8,000 employees and a portfolio of enterprise information management products. It serves VR2014_Leadership_AwardWinnerprimarily large companies. The attraction of Actuate for such a company can be seen in a number of its legacy assets as well as more current acquisitions and developments but also its existing customer base. It was also awarded a 2014 Ventana Research Business Leadership Award.

Actuate’s foundational asset is BIRT (Business Intelligence and Reporting Tools) and its developer community. With more than 3.5 million developers and 13.5 million downloads, the BIRT developer environment is used in a variety of companies on a global basis. The BIRT community includes Java developers as well as sophisticated business intelligence design professionals, which I discussed in my outline of analytics personas. BIRT is a key project for the Eclipse Foundation, an open source integrated development environment familiar to many developers. BIRT provides a graphical interface to build reports at a granular level, and being Java-based, it provides ways to grapple with data and build data connections in a virtually limitless fashion. While new programming models and scripting languages, such as Python and Ruby, are gaining favor, Java remains a primary coding language for large-scale applications. One of the critical capabilities for business intelligence tools is to provide information in a visually compelling and easily usable format. BIRT can provide pixel-perfect reporting and granular adjustments to visualization objects. This benefit is coupled with the advantage of the open source approach: availability of skilled technical human resources on a global basis at relatively low cost.

Last year Actuate introduced iHub 3.1, a deployment server that integrates data from multiple sources and distributes content to end users. IHub has connectors to most database systems including modern approaches such as Hadoop. While Actuate provides the most common connectors out of the box, BIRT and the Java framework allow any data from any system to be brought into the fold. This type of approach to big data becomes particularly compelling for the ability to vr_Big_Data_Analytics_04_types_of_big_data_for_analyticsintegrate both large-scale data and diverse data sources. The challenge is that the work sometimes requires customization, but for large-scale enterprise applications, developers often do this to deliver capabilities that would not otherwise be accessible to end users. Our benchmark research into big data analytics shows that organizations need to access many data sources for analysis including transactional data (60%), external data (50%), content (49%) and event-centric data (48%).

In 2014, Actuate introduced iHub F-Type, which enables users to build reports, visualizations and applications and deploy them in the cloud. F-Type mitigates the need to build a separate deployment infrastructure and can act as both a “sandbox” for development and a broader production environment. Using REST-based interfaces, application developers can use F-Type to prototype and scale embedded reports for their custom applications. F-Type is delivered in the cloud, has full enterprise capabilities out of the box, and is free up to a metered output capacity of 50MB. The approach uses output metering rather than input metering used by some technology vendors. This output metering approach encourages scaling of data and focuses organizations on which specific reports they should deployed to their employees and customers.

Also in 2014, Actuate introduced BIRT Analytics 5.0, a self-service discovery platform that includes advanced analytic capabilities. In my review of BIRT Analytics, I noted its vr_predanalytics_benefits_of_predictive_analytics_updatedabilities to handle large data volumes and do intuitive predictive analytics. Organizations in our research said that predictive analytics provides advantages such as achieving competitive advantage (for 68%), new revenue opportunities (55%) and increased profitability (52%). Advances in BIRT Analytics 5.0 include integration with iHub 3.1 so developers can bring self-service discovery into their dashboards and public APIs for use in custom applications.

The combination of iHub, the F-Type freemium model, BIRT Analytics and the granular controls that BIRT provides to developers and users presents a coherent strategy especially in the context of embedded applications. Actuate CEO Pete Cittadini asserts that the company has the most APIs of any business intelligence vendor. The position is a good one especially since embedded technology is becoming important in the context of custom applications and in the so-called Internet-of-Things. The ability to make a call into another application instead of custom-coding the function itself within the workflow of an end-user application cuts developer time significantly. Furthermore, the robustness of the Actuate platform enables applications to scale almost without limit.

OpenText and Actuate have similarities, such as the maturity of the organizations and the types of large clients they vr_Info_Optimization_02_drivers_for_deploying_informationservice. It will be interesting to see how Actuate’s API strategy will impact the next generation of OpenText’s analytic applications and to what degree Actuate remains an independent business unit in marketing to customers. As a company that has been built through acquisitions, OpenText has a mature onboarding process that usually keeps the new business unit operating separately. OpenText CEO Mark Barrenechea outlines his perspective on the acquisition which will bolster its portfolio for information optimization and analytics or what it calls enterprise information management. In fact our benchmark research on information optimization finds that analytics is the top driver for deploying information in two thirds of organizations. The difference this time may be that today’s enterprises are asking for more integrated information which embeds analytics rather than having different interfaces for each of the applications or tools. The acquisition of Actuate by OpenText has now closed and now changes will occur to Actuate that should be watched closely to determine its path forward and it potential higher value for customers within OpenText.

Regards,

Ventana Research

We recently released our benchmark research on big data analytics, and it sheds light on many of the most important discussions occurring in business technology today. The study’s structure was based on the big data analytics framework that I laid out last year as well as the framework that my colleague Mark Smith put forth on the four types of discovery technology available. These frameworks view big data and analytics as part of a major change that includes a movement from designed data to organic data, the bringing together of analytics and data in a single system, and a corresponding move away from the technology-oriented three Vs of big data to the business-oriented three Ws of data. Our big data analytics research confirms these trends but also reveals some important subtleties and new findings with respect to this important emerging market. I want to share three of the most interesting and even surprising results and their implications for the big data analytics market.

First, we note that communication and knowledge sharing is a primary vr_Big_Data_Analytics_06_benefits_realized_from_big_data_analyticsbenefit of big data analytics initiatives, but it is a latent one. Among organizations planning to deploy big data analytics, the benefits most often anticipated are faster response to opportunities and threats (57%), improving efficiency (57%), improving the customer experience (48%) and gaining competitive advantage (43%). However, once a big data analytics system has moved into production, the benefits most often mentioned as achieved are better communication and knowledge sharing (51%), gaining competitive advantage (51%), improved efficiency in business processes (49%) and improved customer experience and satisfaction (46%). (The chart shows rankings of first choices as most important.) Although the last three of these benefits are predictable, it’s noteworthy that the benefit of communication and knowledge sharing, while not a priority before deployment, becomes one of the two most often cited later.

As for the implications, in our view, one reason why communication and knowledge sharing are more often seen as a key benefit after deployment rather than before is that agreement on big data analytics terminology is often lacking within organizations. Participants from fewer than half (44%) of organizations said that the people making business technology decisions mostly agree or completely agree on the meaning of big data analytics, while the same number said there are many different opinions about its meaning. To address this particular challenge, companies should pay more attention to setting up internal communication structures prior to the launch of a big data analytics project, and we expect collaborative technologies to play a larger role in these initiatives going forward.

vr_Big_Data_Analytics_02_defining_big_data_analyticsA second finding of our research is that integration of distributed data is the most important enabler of big data analytics. Asked the meaning of big data analytics in terms of capabilities, the largest percentage (76%) of participants said it involves analyzing data from all sources rather than just one, while for 55 percent it means analyzing all of the data rather than just a sample of it. (We allowed multiple responses.) More than half (56%) told us they view big data as finding patterns in large and diverse data sets in Hadoop, which indicates the continuing influence of this original big data technology. A second tier of percentages emphasizes timeliness as an aspect of big data: doing real-time processing on streams of data (44%), visualizing large structured data sets in seconds (40%) and doing real-time scoring against a database record (36%).

The implications here are that the primary characteristic of big data analytics technology is the ability to analyze data from many data sources. This shows that companies today are focused on bringing together multiple information sources and secondarily being able to process all data rather than just a sample, as well as being able to do machine learning on especially large data sets. Fast processing and the ability to analyze streams of data are relegated to third position in these priorities. That suggests that the so-called three Vs of big data are confusing the discussion by prioritizing volume, velocity and variety all at once. For companies engaged in big data analytics today, sourcing and integration of various data sources in an expedient manner is the top priority, followed by the ideas of size and then speed of arrival of data.

Third, we found that usage is not relegated to particular industries, vr_Big_Data_Analytics_09_use_cases_for_big_data_analyticscertain types of companies or certain functional areas. From among 25 uses for big data analytics those that participants are personally involved with, three of the four most often mentioned involve customers and sales: enabling cross-selling and up-selling (38%), understanding the customer better (32%) and optimizing pricing (28%). Meanwhile, optimizing IT operations ranked fifth (24%) though it was most often chosen by those in IT roles (76%). What is particularly fascinating, however, is that 17 of the 25 use cases were named by more than 10 percent, which indicates many uses for big data analytics.

The primary implication of this finding is that big data analytics is not following the famous technology adoption curves outlined in books such as Geoffrey Moore’s seminal work, “Crossing the Chasm.” That is, companies are not following a narrowly defined path that solves only one particular problem. Instead, they are creatively deploying technological innovations en route to a diverse set of outcomes. And this is occurring across organizational functions and industries, including conservative ones, which conflicts with conventional wisdom. For this reason, companies are more often looking across industries and functional disciplines as part of their due diligence on big data analytics to come up with unique applications that may yield competitive advantage or organizational efficiencies.

In summary, it has been difficult for companies to define what big data analytics actually means and how to prioritize their investments accordingly. Research such as ours can help organizations address this issue. While the above discussion outlines a few of the interesting findings of this research, it also yields many more insights, related to aspects as diverse as big data in the cloud, sandbox environments, embedded predictive analytics, the most important data sources in use, and the challenges of choosing an architecture and deploying big data analytic products. For a copy of the executive summary download it directly from the Ventana Research community.

Regards,

Ventana Research

Ventana Research recently completed the most comprehensiveVRMobileBIVI evaluation of mobile business intelligence products and vendors available anywhere today. The evaluation includes 16 technology vendors’ offerings on smartphones and tablets and use across Apple, Google Android, Microsoft Surface and RIM BlackBerry that were assessed in seven key categories: usability, manageability, reliability, capability, adaptability, vendor validation and TCO and ROI. The result is our Value Index for Mobile Business Intelligence in 2014. The analysis shows that the top supplier is MicroStrategy, which qualifies as a Hot vendor and is followed by 10 other Hot vendors: IBM, SAP, QlikTech, Information Builders, Yellowfin, Tableau Software, Roambi, SAS, Oracle and arcplan.

Our expertise, hands on experience and the buyer research from our benchmark research on next-generation business intelligence and on information optimization informed our product evaluations in this new Value Index. The research examined business intelligence on mobile technology to determine organizations’ current and planned use and the capabilities required for successful deployment.

What we found was wide interest in mobile business intelligence and a desire to improve the use of information in 40 percent of organizations, though adoption is less pervasive than interest. Fewer than half of organizations currently access BI capabilities on mobile devices, but nearly three-quarters (71%) expect their mobile workforce to be able to access BI capabilities in the next 12 months. The research also shows strong executive support: Nearly half of executives said that mobility is very important to their BI processes.

Mobile_BI_Weighted_OverallEase of access and use are an important criteria in this Value Index because the largest percentage of organizations identified usability as an important factor in evaluations of mobile business intelligence applications. This is an emphasis that we find in most of our research, and in this case it also may reflect users’ experience with first-generation business intelligence on mobile devices; not all those applications were optimized for touch-screen interfaces and designed to support gestures. It is clear that today’s mobile workforce requires the ability to access and analyze data simply and in a straightforward manner, using an intuitive interface.

The top five companies’ products in our 2014 Mobile Business Intelligence Value Index all provide strong user experiences and functionality. MicroStrategy stood out across the board, finishing first in five categories and most notably in the areas of user experience, mobile application development and presentation of information. IBM, the second-place finisher, has made significant progress in mobile BI with six releases in the past year, adding support for Android, advanced security features and an extensible visualization library. SAP’s steady support for the mobile access to SAP BusinessObjects platform and support for access to SAP Lumira, and its integrated mobile device management software helped produce high scores in various categories and put it in third place. QlikTech’s flexible offline deployment capabilities for the iPad and its high ranking in assurance-related category of TCO and ROI secured it the fourth spot. Information Builders’ latest release of WebFOCUS renders content directly with HTML5 and its Active Technologies and Mobile Faves, the company delivers strong mobile capabilities and rounds out the top five ranked companies. Other noteworthy innovations in mobile BI include Yellowfin’s collaboration technology, Roambi’s use of storyboarding in its Flow application.

Although there is some commonality in how vendors provide mobile access to data, there are many differences among their offerings that can make one a better fit than another for an organization’s particular needs. For example, companies that want their mobile workforce to be able to engage in root-cause discovery analysis may prefer tools from Tableau and QlikTech. For large companies looking for a custom application approach, MicroStrategy or Roambi may be good choices, while others looking for streamlined collaboration on mobile devices may prefer Yellowfin. Many companies may base the decision on mobile business intelligence on which vendor they currently have installed. Customers with large implementations from IBM, SAP or Information Builders will be reassured to find that these companies have made mobility a critical focus.

To learn more about this research and to download a free executive summary, please visit http://www.ventanaresearch.com/bivalueindex/.

Regards,

Tony Cosentino

Vice President and Research Director

Actuate recently announced BIRT Analytics Version 4.2, part of its portfolio of business intelligence software. The new release includes several techniques used by analytics professionals placed behind a user-friendly interface that does not require advanced knowledge of statistics. Beyond the techniques themselves, release 4.2 focuses on guiding users through processes such as campaign analytics and targeting.

With the release, Actuate is focusing on what I have already assessed in BIRT Analytics and to support more advanced analytics within organizations like marketing. For these users, a handful of analytical techniques cover the majority of uses cases. Our benchmark research into predictive analytics shows that vr_predanalytics_top_predictive_techniques_usedclassification trees (used by 69% of participants), regression techniques (66%), association rules (49%) and k-nearest neighbor algorithms (36%) are the techniques used most often. While BIRT Analytics uses Holt-Winters exponential smoothing for forecasting rather than linear regression and k-means for clustering, the key point is that it addresses the most important uses in the organization through a nontechnical user interface. Using techniques like regression or supervised learning algorithms increases complexity, and such analysis often requires formidable statistical knowledge from the user. In addition to the techniques mentioned above, BIRT Analytics reduces complexity by offering Venn diagram set analysis, a geographic mapping function, and the ability to compare attributes using z-score analysis. A z-score is a standardized unit of measure (relative to the model parameters mu and sigma) that represents how far away from a model’s mean a particular measurement rests. The higher the absolute value of the z-score, the more significant the attribute. This analysis is a simple way of showing things such as the likelihood that a particular email campaign segment will respond to a particular offer; such knowledge helps marketers understand what drives response rates and build lift into a marketing campaign. With this analytical tool set, the marketer or front-line analyst is able to dive directly into cluster analysis, market basket analysis, next-best-offer analysis, campaign analysis, attribution modeling, root-cause analysis and target marketing analysis in order to impact outcome metrics such as new customer acquisition, share-of-wallet, customer loyalty and retention.

Actuate also includes the iWorkflow application in release 4.2. It enables users to set business rules based on constantly calculated measurements and their variance relative to optimal KPI values. If the value falls outside of the critical range, it can start an automated process or send a notification for manual effort to remedy a situation. For instance, if an important customer satisfaction threshold is not being met, the system can notify a customer experience manager to take action that corrects the situation . In the same way, the iWorkflow tool allows users to preprogram distribution of analytical results across the organization based on particular roles or security criteria. As companies work to link market insights with operational objectives, Actuate ought to integrate more tightly with applications from companies such as Eloqua, Marketo and salesforce.com. Today this has to be done manually and prevents the automation of closed-loop workflows in areas such as campaign management and customer experience management. Once this is done, however, the tool becomes more valuable to users. The ability to embed analytics into the workflows of the applications themselves is the next challenge for vendors of tools for visual discovery and data discovery.

Other enhancements to BIRT Analytics address data loading and data preparation. The data loader adds a drag-and-drop capability for mapped fields, can incorporate both corporate data and personal data from the desktop and automates batch loading. New preprocessing techniques include scaling approaches and data mapping. The abilities to load data into the columnar store from different information sources and to manipulate the data in databases are important areas that Actuate should continue to develop. Information sources will always be more important than the tools themselves, and data preprocessing is still where most analysts spend the bulk of their time.

BIRT Analytics has been overlooked by many companies in the United States since the roots of the company are in Spain, but the vr_bti_br_whats_driving_change_to_technology_selectiontechnology offers capabilities on par with many of the leaders in the BI category, and some are even more advanced. According to our business technology innovation benchmark research, companies are instituting new technology because of bottom-line considerations such as improvements in business initiatives (60%) and in processes (57%). Furthermore, usability is the top evaluation criterion for business intelligence tools in almost two-thirds (64%) of companies, according to our research on next-generation business intelligence. These are among the reasons we are seeing mass adoption of discovery tools such as BIRT Analytics. Those looking into discovery tools, and especially marketing departments that want to put a portfolio of analytics directly into the hands of the marketing analyst and the data-savvy marketer, should consider BIRT Analytics 4.2.

Regards,

Tony Cosentino

VP and Research Director

Actuate this week announced BIRT Analytics, and thereby puts itself firmly into supporting a range of business analytics needs from data discovery and visualization to a range of data mining and predictive capabilities that allows itself new avenues of growth. Actuate has long been a staple of large Business Intelligence deployments; in fact the company says that ActuateOne delivers more insights to more people than all other BI applications combined. This is likely true, given that Actuate is embedded in major consumer applications across industries worldwide. This announcement builds and utilizes its advancements into big data that I already assessed last year that can help it further expand its technology value to business and IT.

Tools such as BIRT Analytics can change the organizational culture aroundvr_ngbi_br_importance_of_bi_technology_considerations data and analytics. They put the power of data discovery and data visualization into the hands of tool-savvy managers as well as business analysts.  While Actuate has allowed highly functional and interactive dashboards in the past, BIRT Analytics brings the usability dimension to a different level. Usability is of the highest importance to 63 percent of organizations for business intelligence software, according to our next-generation business intelligence benchmark research, and one where BIRT Analytics and other tools in its class really show their value. The technology allows not just for visual data exploration, but also for new sources of data to be connected and analyzed without a predefined schema. This fits well with the current world of distributed computing, where everything can no longer be nicely modeled in one place. The software can gather data from different sources, including big data sources, flat files and traditional relational databases, and mash these up through visually appealing toolsets, allowing end user analysts to bypass IT and avoid much of the data preparation that has been a hallmark of business intelligence in the past. In fact our recent business technology innovation benchmark research shows that only a little more than half of companies are satisfied with their analytic processes, and 44 percent of organizations indicate the most time-consuming part of the analytics process is data-related tasks that Actuate is addressing with their ability to handle data efficiently.

Some of the advantages of the BIRT Analytics product are its fast in-memory engine,vr_predanalytics_benifits_of_predictive_analytics its ability to handle large amounts of data, and the more advanced analytic capabilities in the system. The company’s web site says it offers the fastest data loading tool in the industry with the FastDB main memory database system and an ability to explore 6 billion records in less than a second. These are impressive numbers, especially as we look at big data analytics, which often runs against terabytes of data. The usability of this tool’s analytics features is particularly impressive. For instance, set analysis, clustering and predictive capabilities are all part of the software, allowing analysts who aren’t necessarily data scientists to conduct advanced data analysis. These capabilities give tools like BIRT Analytics an advantage in the market since they offer simple end-user-driven ways to produce market segmentation and forecasting reports. These advancements help Actuate provide new benefits of its BIRT Analytics that according to our benchmark research on predictive analytics, 68 percent of organizations see predictive analytics as a source of competitive advantage.

Actuate already ranked as a hot vendor in the 2012 Ventana Research Business Intelligence Value Index thanks to its enterprise-level reliability and validation of its deployments which this release will help it even more in its ratings.  In the short term, BIRT Analytics will certainly boost Actuate’s market momentum and allow it to compete in areas where it would not have been seen before and help it expand its value to its existing customers.

Regards,

Tony Cosentino

VP and Research Director

Actuate, the driving force behind the open source Eclipse Business Intelligence and Reporting Tools (BIRT) project, is positioning itself in the center of the big-data world through multiple partnerships with companies such as Cloudera, Hortonworks, KXEN, Pervasive and a number of OEMs. These agreements, following on its acquisition of Xenos a couple of years ago, help Actuate address some big issues in big data, involving enterprise integration and closed-loop operational systems that provide what my colleague Robert Kugel refers to as action-oriented information technology systems. Today, most initiatives in big data and Hadoop are still in the proof-of-concept stages or being implemented in organizational siloes. Actuate, with its enterprise orientation and federated architecture, is in a position to potentially advance these efforts in a variety of ways.

Actuate’s back-to-back announcements with Cloudera and Hortonworks give support to the 1.5 million BIRT developers and begin to solidify the ties between the BIRT and Hadoop open source communities. Actuate first announced support for Hadoop with the release of BIRT 3.7 last year when it gave BIRT developers access to Hadoop through Hive Query Language (HQL). Hive allows BIRT native access to Hadoop as a data source and provides a single interface for analysis and reporting across a variety of multistructured data sources. These steps answer the finding in our benchmark research on Hadoop and Information Management that users require more efficient methods to access Hadoop HDFS. The overall result of the partnerships is out-of-the-box access for the two leading distributions of Hadoop, enabling organizations to integrate big data more easily into their BIRT environments.

In the analytics and visualization space, Actuate signed agreements with Pervasive and KXEN. RushAnalyzer, Pervasive’s predictive analytics tool that runs natively on Hadoop, will be integrated with the ActuateOne product suite. The combination of Rush Analyzer and ActuateOne gives business users the ability to transform and analyze big data, and puts advanced visualization capabilities in the hands of analysts. The KXEN partnership goes further into predictive analytics by integrating with KXEN’s flagship product, InfiniteInsight. This gives users capabilities in key areas of predictive analytics such as cross-selling and up-selling, churn analytics, next-best-offer and market basket analysis. Our benchmark research in big data finds that predictive analytics is a capability not available in 41 percent of organizations.

Actuate’s OnDemand software is delivered via both PaaS and SaaS. Here Actuate has signed deals with a number of companies, including BMC Software, Cisco, Computer Associates, GE Healthcare, Infor and Siemens, and more recently with Access Data, eMeter and Integrated Data Services. In all, Actuate has more than 200 OEM partnerships, which are of particular importance as companies and developers turn toward the cloud for big-data platform development. Our benchmark research in big data shows that while most current deployments are on-premises, hosted and SaaS deployments will grow faster moving forward.

In addition to the multiple partnerships, Actuate is positioned to ride the big-data wave with Xenos, a content management company it acquired in 2010. Integration with Xenos Enterprise Server allows BIRT developers to design a user front end for powerful parsing technology that enables mining of multistructured data buried in legacy documents and archives of statements, forms and records.

Overall, I see a three-pronged big-data strategy emerging from Actuate. On one front, it offers an enterprise business intelligence system that easily builds reports using any source of data. A large and growing developer community provides the company with the ability to explore all types of relationships and adjust quickly and nimbly to competitors. On the second level, Actuate provides OEM application developers the ability to invoke broad BI functionality within their own custom applications. This will likely prove to be more important as companies move to cloud-based technologies and closed-loop operational intelligence systems that can drive immediate action within a single desktop or mobile interface. In these first two areas, Actuate is at home in terms of its targets in the enterprise, being well-known among enterprise application developers.

It’s on the third front where I think things get interesting for the company, Actuate’s Performance Analytics software, which my colleague Mark Smith wrote about earlier this year. This application focuses on the lines of business and competes with some discovery tools in the market that have already gained traction. Given the shifting landscape of the enterprise buying center with respect to big data, this group is very important as our big data benchmark research has found. The key for Actuate will be to link big data and predictive analytics capabilities that they gain through partner relationships back to its growing business analytics environment operating across the Internet to the mobile environment. If the company can do so, it will position itself well in business environments where analytics need to be pushed out to support real-time and interactive decision-making by front-line managers.

Regards,

Tony Cosentino – VP & Research Director

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