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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.


Ventana Research

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 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.


Tony Cosentino

VP and Research Director

SiSense gained a lot of traction last week at the Strata conference vr_ngbi_br_importance_of_bi_technology_considerationsin San Jose as it broke records in the so-called 10x10x10 Challenge – analyzing 10 terabytes of data in 10 seconds on a $10,000 commodity machine – and earned the company’s Prism product the Audience Choice Award. The Israel-based company, founded in 2005, has venture capital backing and is currently running at a profit with customers in more than 50 countries and marquee customers such as Target and Merck. Prism, its primary product, provides the entire business analytics stack, from ETL capabilities through data analysis and visualization. From the demonstrations I’ve seen, the toolset appears relatively user-friendly, which is important because customers say usability is the top criterion in 63 percent of organizations according to our next-generation business intelligence.

Prism comprises three main components: ElastiCube Manager, Prism BI Studio and Prism Web. ElastiCube Manager provides a visual environment with which users can ingest data from multiple sources, define relationship between data and do transforms via SQL functions. Prism Studio provides a visual environment that lets customers build visual dashboards that link data and provide users with dynamic charts and interactivity. Finally, Prism Web provides web-based functionality for interacting, sharing dashboards and managing user profiles and accounts.

At the heart of Prism is the ElasticCube technology, which can query large volumes of data quickly. ElasticCube uses a columnar approach, which allows for fast compression. With SiSense, queries are optimized by the CPU itself. That is, the system decides in an ad hoc manner the most efficient way to use both disk and memory. Most other approaches on the market lean either to a pure-play in-memory system or toward a columnar approach.

The company’s approach to big data analytics reveals the chasm that exists in big data analytics understanding between descriptive analytics and more advanced analytics such as we see with R, SAS and SPSS. When SiSense speaks of big data analytics, it is speaking of the ability to consume and explore very large data sets without predefining schemas. By doing away with schemas, the software does away with the  need for a statistician, a data mining engineer or an IT person for that matter. Instead, organizations need analysts with a good understanding of the business, the data sources with which they are working and the basic characteristics of those data sets. SiSense does not do sophisticated predictive modeling or data mining, but rather root-cause and contextual analysis across diverse and potentially very large data sets.

SiSense today has a relatively small footprint, and is facing an uphill battle against entrenched BI and analytics players for enterprise deployments but it’s easy to download and try approach will help it get traction with analysts who are less loyal to the BI that IT departments have purchased. SiSense Vice President of Marketing Bruno Aziza, formerly with Microsoft’s Business Intelligence group, and CEO Amit Bendov have been in the industry for a fair amount of time and understand this challenge. Their platform’s road into the organization is more likely through business groups rather than IT. For this reason, SiSense’s competitors are Tableau and QlikView on the discovery side and products likes SAP HANA and Actuate’s BIRT Analytics in-memory plus columnar approaches are likely the closest competitors in terms of the technological approach to accessing and visualizing large data sets. This ability to access large data sets in a timely manner without the need for data scientists can help overcome the top challenges BI users have in the areas of staffing and real-time access, which we uncovered in our recent business technology innovation research.

vr_bigdata_obstacles_to_big_data_analyticsSiSense has impressive technology, and is getting some good traction. It bears consideration by departmental and mid-market organizations that need to perform analytics across growing volumes of data without the need for an IT department to support their needs.


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.


Tony Cosentino – VP & Research Director

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