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JackBe's Presto: A Self-Service, On-Demand Data Integration, Mashup-Based, Dashboard-Oriented, Business Intelligence Tool

Originally published March 10, 2011

Earlier this month, Maryland-based JackBe released version 3.1 of Presto. JackBe calls their product a real-time intelligence solution. But what does that mean? A quick glance at the product tells us that with Presto different types of reporting and dashboard applications can be developed, and data can be visualized in different ways. So far, nothing new. Many tools available on the market today can do that.

So, what's so special about Presto? What is its unique selling point? It's not easy to summarize Presto with one or two words. It supports reporting and dashboarding capabilities, but the way data is moved from the data sources to the reports is different from most other products. It supports extensive federation capabilities, but it's not a data federation or data virtualization product. The easy-to-use development environment makes it a self-service business intelligence (BI) tool. Business analysts with some technical background should have no problem grasping this interface. But it's not a typical self-service tool that loads data into a big cube kept in memory before the data can be deployed. It can mashup internal and external applications, but it's not your average mashup tool because it's focused on developing BI applications.

So again, what is it? In a way, Presto is a little bit of all that is mentioned above. Maybe we should call it a self-service, on-demand data integration, mashup-based, dashboard-oriented BI tool. And the fact that it combines all those features makes it a unique product.

Let me explain these terms.

Self-service: From the business analyst perspective, Presto is a tool that allows someone with limited technical background (experience with Excel is probably enough) to easily create dashboards and link them together. In Presto, a dashboard is simply called an App. JackBe offers an App Store from which the analysts can pick the ideal App for the job. This can be a simple graph, a gauge, or map, for example. Multiple Apps can be linked together to form a bigger dashboard, as seen in Figure 1.

Figure 1: An Example of a Dashboard Created with Presto
(mouseover image to enlarge)

With this straightforward technology, Presto offers a self-service environment to the users. If more complex Apps are required than are available in the App Store, professional developers can develop and add them to the App Store.

Integration of external and internal data: The background of JackBe as a company is in mashup technology. With their earlier generation of products, they excelled at integrating data from all kinds of sources. Besides being able to integrate data stored in databases and services, they could also extract data from websites, even if those websites were HTML-based. Structured interfaces could be developed on top of those external non-structured websites. This makes it easy for a new application to access the data "hidden" in those websites. As an example, Figure 2 shows a typical mashup application running on a mobile App.

Figure 2: An Example of a Mashup Application

All that data integration technology is available in Presto. This allows for data stored in internal and structured data warehouses, production databases, spreadsheets, enterprise resource planning (ERP), customer relationship management (CRM), and business activity management (BAM) to be easily integrated with data available via external websites. For example, internal transportation data can be integrated with public weather data, internal customer data can be integrated with general business data available through certain websites, and a retailer can analyze pricing information of the competition, which is freely available on the web. Nowadays, the web contains mountains of useful external data, including social media posts and news feeds.

On-demand data integration: This means that if users ask for a report, data from the different sources is accessed and integrated and "pushed" live to the report (App). No temporary data stores, such as cubes, are created and/or kept in memory. This means that users will see the most current version of the data. In this respect, Presto is like most data federation/data virtualization products such as those from Composite, Denodo, and Informatica. For particular dashboards, refresh rates can be set and will change the content of a report periodically. This is a powerful feature, especially for dashboards. Note that if accessing the underlying data sources is too slow or inefficient, caches can be defined.

Interactive development: A declarative flow language called EMML (Enterprise Mashup Markup Language), which can be found at www.openmashup.org, is used to define how data should be “mashed” and transformed (Figure 3). In this diagram, the boxes represent integration and transformation steps. This flow language resembles the languages used by most extract, transform and load (ETL) products. The difference with ETL, however, is that in Presto those flows are executed periodically (for example, to refresh dashboards) or they are executed on demand (when users ask for the reports).

Figure 3: An Example of a Wire Diagram with which Data is Pushed from the Data Sources to the Apps
(mouseover image to enlarge)

In Presto, these flow diagrams can be created through a visual browser tool called Wires that creates the wire diagrams. As such a diagram is created, the developers and business analysts can look at the real content of each step (a box in the diagram) in the flow. If they want to check whether the box really returns the right result, they can look at its content. This allows for a very interactive way of development.


Why Presto? There are two main reasons why organizations might be interested in Presto. The first reason is that Presto allows users to look at live data. This is a powerful feature especially for dashboard-based Apps, which should show the state of particular business processes. The second reason could be that users want to enrich the data available within their organization with external data. Presto offers the right technical features for bringing all those data sources together in an integrated fashion. To summarize, the combination of features makes Presto a product worthwhile of studying.

SOURCE: JackBe's Presto: A Self-Service, On-Demand Data Integration, Mashup-Based, Dashboard-Oriented, Business Intelligence Tool

  • Rick van der LansRick van der Lans

    Rick is an independent consultant, speaker and author, specializing in data warehousing, business intelligence, database technology and data virtualization. He is managing director and founder of R20/Consultancy. An internationally acclaimed speaker who has lectured worldwide for the last 25 years, he is the chairman of the successful annual European Enterprise Data and Business Intelligence Conference held annually in London. In the summer of 2012 he published his new book Data Virtualization for Business Intelligence Systems. He is also the author of one of the most successful books on SQL, the popular Introduction to SQL, which is available in English, Chinese, Dutch, Italian and German. He has written many white papers for various software vendors. Rick can be contacted by sending an email to rick@r20.nl.

    Editor's Note: Rick's blog and more articles can be accessed through his BeyeNETWORK Expert Channel.

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