- OLAP analysis (in CE edition JPivot)
- Dashboards (CDF + CDE)
CIO at a wellness & fitness company with 51-200 employees
The initial setup of the tool is very simple and the product is fairly simple.
What is most valuable?
How has it helped my organization?
With the launch of Pentaho the organization has aggregated information about the various functional areas and the ability to generate real-time analysis (OLAP) without the need of IT.
For how long have I used the solution?
It's in production since 2010
What was my experience with deployment of the solution?
None encountered.
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What do I think about the stability of the solution?
It's fairly stable.
How are customer service and support?
Customer Service:
I use the CE without support.
Technical Support:I use the CE without support.
Which solution did I use previously and why did I switch?
Yes. I changed because of costs.
How was the initial setup?
The initial setup of the tool is very simple. In the last version we have a marketplace for installing new features in the product.
What about the implementation team?
In-House.
What's my experience with pricing, setup cost, and licensing?
The cost of initial setup was only for the hours and technical expertise (internal development).
What other advice do I have?
A very important aspect of performance is the choice of the database to house the data warehouse. I recommend investing time in deciding the engine and architecture. We recommend using oriented columns engines.
Disclosure: My company does not have a business relationship with this vendor other than being a customer.
IT Consultant at a computer software company with 51-200 employees
Creating your own plugin is very easy with Pentaho
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IT Manager at a transportation company with 51-200 employees
In terms of functionality, they're not growing as fast as other companies. It's good for showing the need for BI.
Database Analyst at a government with 51-200 employees
Working on poverty alleviation in Indonesia, this tool has improved the ability of policy makers to make good decisions.
Data Warehouse Specialist at a educational organization with 501-1,000 employees
More built-in features could improve the solution, but everything related to ETL is valuable.
Owner with 51-200 employees
Vendor
Feb 4, 2014
Pentaho BI Suite Review: Final Thoughts – Part 6 of 6
Introduction
This is the last of a six-part review of the Pentaho BI suite. In each part of the review, we will take a look at the components that make up the BI suite, according to how they would be used in the real world.
Data Mining
In this sixth part, originally, I'd like to at least touch on the only part of Pentaho BI Suite we have not talked about before: Data Mining. However as I gather my materials, I realized that Data Mining (along with its ilks: Machine Learning, Predictive Analysis, etc.) is too big of a topic to fit in the space that we have here. Even if I try, the usefulness would be limited at best since at the moment, while the result is being used to solve real-world problems, the usage of Data Mining tools is still exclusively within the realm of data scientists.
In addition, as of late I use Python more for working with datasets that requires a lot of munging, preparing, and cleaning. So as an extension to that, I ended using Pandas, SciKit Learning, and other Python-specific Data Mining libraries instead of Weka (which is basically what the Pentaho Data Mining tool is).
So for those who are new to Data Mining with Pentaho, here is a good place to start, an interview with Mark Hall who was one of the author of Weka who now works for Pentaho: https://www.floss4science.com/machine-learning-with-weka-mark-hall
The link above also has some links to where to find more information.
For those who are experienced data scientists, you probably already made up your mind on which tool suits your needs best and just like I went with Python libraries, you may or may not prefer the GUI approach like Weka.
New Release: Pentaho 5.0 CE
For the rest of this review, we will go over the new changes that comes with the highly anticipated release of the 5.0 CE version. Overall, there are a lot of improvements in various parts of the suite such as PDI and PRD, but we will focus on the BI Server itself, where the largest impact of the new release can be seen.
A New Repository System
In this new release, one of the biggest shock for existing users is the switch from file-based repository system to the new JCR-based one. JCR is a database-backed content repository system that was implemented by the Apache Foundation and code-named “Jackrabbit.”
The Good:
- Better metadata management
- No longer need to refresh the repository manually after publishing solutions
- A much better UI for dealing with the solutions
- API to access the solutions via the repository which opens up a lot of opportunities for custom applications
The Bad:
- It's not as familiar or convenient as the old file-based system
- Need to use a synchronizer plugin to version-control the solutions'
It remains to be seen if this switch will pay off for both the developers and the users in the long run. But it is stable and working for the most part, so I can't complain.
The Marketplace
One of the best feature of the Pentaho BI Server is its plugin-friendly architecture. In version 5.0 this architecture has been given a new face called the Marketplace:
This new interface serves two important functions:
- It allows admins to install and update plugins (almost all Pentaho CE tools are written as plugins) effortlessly
- It allows developers to publish their own plugins to the world
There are already several new plugins that is available with this new release, notably Pivot4J Analytics. An alternative to Saiku that shows a lot of promises to become a very useful tool to work with OLAP data. Another one that excites me is Sparkl with which you can create other custom plugins.
The Administration Console
The new version also brings about a new Administration Console where we manage Users and Roles:
No longer do we have to fire-off another server just to do this basic administrator task. In addition, you can manage the Mail server (no more wrangling configuration files).
The New Dashboard Editor
As we discussed in Part V of this review, the CDE is a very powerful dashboard editor. In version 5.0, the list of available Components are further lengthen by new ones. And the overall editor seems to be more responsive in this new release.
Usage experience: The improvements in the Dashboard editor is helping me to create dashboards for my clients that goes beyond the static ones. In fact, the one below (demo purposes only) has the interactivity level that rivals a web application or an electronic form:
NOTE: Nikon and Olympus are trademarks of Nikon Corporation and Olympus Group respectively.
Parting Thoughts
Even though the final product of a Data Warehouse of a BI system is a set of answers and forecasts, or dashboards and reports, it is easy to forget that without the tools that help us to consolidate, clean up, aggregate, and analyze the data, we will never get to the results we are aiming for.
As you can probably tell, I serve my clients with various tools that makes sense given their situation, but time and again, the Pentaho BI Suite (CE version especially) has risen to fulfill the needs. I have created Data Warehouses from scratch using Pentaho BI CE, pulling in data from various sources using the PDI, created OLAP cubes with the PSW, which ends up as the data source for the various dashboards (financial dashboards, inventory dashboards, marketing dashboards, etc.) and published reports created using the PRD.
Of course my familiarity with the tool helps, but I am also familiar with a lot of other BI tools beside Pentaho. And sometimes I do have to use other tools in preference to Pentaho because they suit the needs better.
But as I always mention to my clients, unless you have a good relationship with the vendor to avoid paying hundreds-of-thousands per year just to be able to use tools like IBM Cognos, Oracle BI, or SAP Business Objects, there is a good chance that the Pentaho (either EE or CE version) can do the same for less, even zero license cost in the case of CE.
Given the increased awareness on the value of data analysis in today's companies, these BI tools will continue to become more and more sophisticated and powerful. It is up to us business owners, consultants, and data analysis everywhere to develop the skills to harness the tool and crank out useful, accurate, and yes, easy-on-the-eyes decision-support systems. And I suspect that we will always see Pentaho as one of the viable options. A testament to the quality of the team working on it. The CE team in particular, it would be amiss not to acknowledge their efforts to improve and maintain a tool this complex using the Open Source paradigm.
So here we are, at the end of the sixth part. Writing this six-part review has been a blast. And I would like to give a shout out to the IT Central Station who has graciously hosted this review for all to benefit from. Thanks for reading.
Disclosure: My company does not have a business relationship with this vendor other than being a customer.
Engineer at a marketing services firm with 51-200 employees
Vendor
Dec 26, 2013
It does a lot of what we need but off-the-shelf solutions often can’t do exactly what you need
Owner with 51-200 employees
Vendor
Dec 12, 2013
Pentaho BI Suite Review: Dashboards – Part 5 of 6
Introduction
This is the fifth of a six-part review of the Pentaho BI suite. In each part of the review, we will take a look at the components that make up the BI suite, according to how they would be used in the real world.
In this fifth part, we'll be discussing how to create useful and meaningful dashboards using the tools available to us in the Pentaho BI Suite. As a complete Data Warehouse building tool, Pentaho offers the most important aspect for delivering enterprise-class dashboards, namely Access Control List (ACL). A dashboard-creation tool without this ability to limit dashboards access to a particular group or role within the company is missing a crucial feature, something that we cannot recommend to our clients.
On the Enterprise Edition (EE) version 5.0, dashboard creation has a user-friendly UI that is as simple as drag-and-drop. It looks like this:
Figure 1. The EE version of the Dashboard Designer (CDE in the CE version)
Here the user is guided to choose a type of grid layout that is already prepared by Pentaho. Of course the option to customize the looks and change individual components are available under the hood, but it is clear that this UI is aimed towards end-users looking for quick results. More experienced dashboard designers would feel severely restricted by this.
In the rest of this review, we will go over dashboard creation using the Community Edition (CE) version 4.5. Here we are going to see a more flexible UI which unfortunately also demands familiarity with javacript and chart library customizations to create something more than just basic dashboards.
BI Server Revisited
In the Pentaho BI Suite, dashboards are setup in these two places:
- Using special ETLs we prepare the data to be displayed on the dashboards according to the frequency of update that is required by the user. For example, for daily sales figures, the ETL would be scheduled to run every night. Why do we do this? Because the benefits are two-fold: It increase the performance of the dashboards because it is working with pre-calculated data, and it allows us to apply dashboard-level business rules.
- The BI Server is where we design, edit, assign access permissions to dashboards. Deep URLs could be obtained for a particular dashboard to be displayed on a separate website, but some care has to be taken to go through the Pentaho user authorization; depending on the web server setup, it could be as simple as passing authorization tokens, or as complex as registering and configuring a custom module.
Next, we will discuss each of these steps in creating a dashboard. As usual, the screenshots below are sanitized and there are no real data being represented. Data from a fictitious microbrewery is used to illustrate and relate the concepts.
Ready, Set, Dash!
The first step is to initiate the creation of a dashboard. This is accomplished by selecting File > New > CDE Dashboard. A little background note, CDE (which stands for Ctools Dashboard Editor) is part of the Community Tools (or Ctools) created by the team who maintains and improve Pentaho CE.
After initiating the creation of a new dashboard, this is what we will see:
Figure 2. The Layout screen where we perform the layout step
The first thing to do is to save the newly created (empty) dashboard into somewhere within the Pentaho solution folder (just like what we did when we save an Analytic or Ad-Hoc Reports). To save the currently worked on dashboard, use the familiar New | Save | Save As | Reload | Settings menu. We will not go into details on each of this self-explanatory menus.
Now look at the top-right section. There are three buttons that will toggle the screen mode, this particular one is in the Layout mode.
In this mode, we take care of the layout of the dashboard. On the left panel, we see the Layout Structure. It is basically a grid that is made out of Row entries, which contains Column(s) which itself may contain another set of Row(s). The big difference between Row and Column is that the Column actually contains the Components such as charts, tables, and many other types. We give a name to a Column to tie it to a content. Because of this, the names of the Columns must be unique within a dashboard.
The panel to the right, is a list of properties that we can set the values of, mostly HTML and CSS attributes that tells the browser how to render the layout. It is recommended to create a company-wide CSS to show the company logo, colors, and other visual markings on the dashboard.
So basically all we are doing in this Layout mode is determining where certain contents should appear within the dashboard, and we do that by naming each of the place where we want those contents to be displayed.
NOTE: Even though the contents are placed within a Column, it is a good practice to name the Rows clearly to indicate the sections of the dashboard, so we can go back later and be able to locate the dashboard elements quickly.
Lining-Up Components
After we defined the layout of the dashboard using the Layout mode, we move on to the next step by clicking on the Components button on the top horizontal menu as shown in the screenshot below:
Figure 3. The Components mode where we define the dashboard components
Usage experience: Although more complex, the CDE is well implemented and quite robust. During our usage to build dashboards for our clients, we have never seen it produce inconsistent results.
In this Components mode, there are three sections (going from left to right). The left-most panel contains the selection of components (data presentation unit). Ranging from simple table, to the complex charting options (based on Protovis data visualization library), we can choose how to present the data on the dashboard.
The next section to the right contains the current components already chosen for the dashboard we are building. As we select each of these components, its properties are displayed in the section next to it. The Properties section is where we fill-in the information such as:
- Where the data is coming from
- Where the Component will be displayed in the dashboard. This is done by referring to the previously defined Column from the Layout screen
- Customization such as table column width, the colors of a pie chart, custom scripting that should be run before or after the component is drawn
This clean separation between the Layout and the Components makes it easy for us to create dashboards that are easy to maintain and accommodates different versions of the components.
Where The Data Is Sourced
The last mode is the Data Source mode where we define where the dashboard Components will get their data:
Figure 4. The Data Sources mode where we define where the data is coming from
As seen in the left-most panel, the data source type is quite comprehensive. We typically use either SQL or MDX queries to fetch the data set in the format that is suitable to be presented in the Components we defined earlier.
For instance, a data set to be presented in a five-columns table will look different than one that will be presented in a Pie Chart.
This screen follows the other in terms of sections, we have (from left to right) the Data Source type list, the currently defined data sources, and the Properties section on the right.
Usage experience: There may be some confusion for those who are not familiar with the way Pentaho define a data source. There are two “data source” concepts represented here. One is the Data Source defined in this step for the dashboard, and the other, the “data source” or “data model” where the Data Source connects to and run the query against.
After we define the Data Sources and name them, we go back to the Components mode and specify these names as the value of the Data source property of the defined components.
Voila! A Dashboard
By the time we finished defining the Data Sources, Components, and Layout, we end up with a dashboard. Ours looks like this:
Figure 5. The resulting dashboard
The Title of the dashboard and the date range is contained within one Row. So are the first table and the pie chart. This demonstrates the flexibility of the grid system used in the Layout mode.
The company color and fonts used in this dashboard is controlled via the custom CSS specified as Resource in the Layout mode.
All that is left to do at this point is to give the dashboard some role-based permissions so access to it will be limited to those who are in the specified role.
TIP: Never assign permission at the individual user level. Why? Think about what has to happen when the person change position and is replaced by someone else.
Extreme Customization
Anything from table column width to the rotation-degrees of the x-axis labels can be customized via the properties. Furthermore, for those who are well-versed in Javascript language, there are tons of things that we can do to make the dashboard more than just a static display.
These customizations can actually be useful other than just making things sparkle and easier to read. For example, by using some scripting, we can apply some dashboard-level business rules to the dashboard.
Usage experience:Let's say we wanted to trigger some numbers displayed to be in the red when it fell below a certain threshold, we do this using the post-execution property of the component and the script looks like this:
Figure 6. A sample post-execution script
Summary
The CDE is a good tool for building dashboards, coupled with the ACL feature built into the Pentaho BI Server, they serve as a good platform for planning and delivering your dashboard solutions. Are there other tools out there that can do the same thing with the same degree of flexibility? Sure. But for the cost of only time spent on learning (which can be shortened significantly by hiring a competent BI consultant), it is quite hard to beat free licensing cost.
To squeeze out its potentials, CDE requires a lot of familiarity with programming concepts such as formatting masks, javascript scripting, pre- and post- events, and most of the times, the answer to how-to questions can only be found in random conversations between Pentaho CE developers. So please be duly warned.
But if we can get past those hurdles, it can bring about some of the most useful and clear dashboards. Notice we didn't mention “pretty” (as in “gimicky”) because that is not what makes a dashboard really useful for CEOs and Business Owners in day-to-day decision-making.
Next in the final part (part-six), we will wrap up the review with a peek into the Weka Data Mining facility in Pentaho, and some closing thoughts.
Disclosure: My company does not have a business relationship with this vendor other than being a customer.
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Learn More: Questions:
- Seeking advise on going with Birst, BOARD or Pentaho as an OEM platform solution where we could end up with 1,000's of users over time.
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Have you looked into using Talend?? It's got a great user interface, very similar to kettle, and their paid for version has version control that works very well, and you get the ability to run "joblets" which are basically re-usable pieces of code. Even in the free version there is version control, although it's pretty clumsy, and not joblets in the free, and the free version is difficult to get working with Github.