The dream of effortless BI deployment has always been sweeter than the reality. Some of the most significant barriers arise during acquisition. Combing through the components to figure out which ones you must buy to get the features you’re looking for can feel like rummaging through a really expensive, very high-tech flea market.
Newly surfaced Tableau Software aims to revolutionize the acquisition and deployment process with its product suite, Tableau Professional and Standard Editions. To a significant degree, it has succeeded, especially on the acquisitions side.
The currently dominant acquisition model, vertical integration, is based on the idea that data distribution and analysis tools should come from the vendors who store, compile, or organize the data. In its own way, vertical integration makes good sense for buyers already committed to a single vendor’s data warehouse or integrated BI suite.
But acquisition through vertical integration is not as simple as it looks. It becomes dicey when the back-end data vendor you’ve standardized on doesn’t have a BI client that matches your analysts’ needs — or doesn’t have one at all. Further, the elegant vertical integration concept tends to be inelegant in execution: Sometimes acquiring a BI client for analysts requires multiple component purchases — such as additional services or connectors — beyond the client. Those components frequently connect easily only to data from their specific vendor. Prices usually are built around site licenses and tend to run in the tens of thousands of dollars to more than US$100,000.
In contrast, Tableau’s three versions are shrink-wrapped, top out at about $1,800, and connect to a wide range of back-end data sources. The client is a what-you-get-is-what-you-get model; there’s no long parts lists or complex interconnected components to pick from. I tested the Standard Edition and, for the most part, found it well-suited to enterprises’ need for better, smarter BI applications.
Making the grade
Late last year, I reviewed Hyperion’s Essbase 7X and focused on the new Hyperion Visual Explorer client. As it turns out, the HVE client I appreciated for its appropriateness and ease of use is actually a licensed version of Tableau’s client, refined to work optimally (and exclusively) with Essbase source data. Now, Tableau is offering that client for use with any source data.
Tableau presents an Excel-like interface that’s designed for a user who’s an analyst with business knowledge; it supports viewing and exploration of data absorbed from data warehouses, databases, and preprocessed data cubes. As with the HVE version, the design gives analysts a method of interacting with a vast selection of possible data “dimensions” without having to know about back-end data’s structure.
I found connection extremely simple for this category, guided by the product’s well-constructed dialog boxes. Installation took less than 15 minutes and configuration on an analyst’s workstation less than 30 minutes to connect to a dozen unitary and linked data sources.
For end-users with some knowledge of data schemas, connection to a single source or the bringing together of multiple sources will be straightforward (as it will be for administrators). Tableau Standard Edition 1.0 connects in a few minutes to data tables from sources including delimited text, Excel, Access, and MySQL; the Professional Edition connects to those three, plus Microsoft SQL Server, Microsoft SQL Server Analytical Services, Hyperion Essbase, and IBM DB2 OLAP server.
The interface is very much as described in the HVE review: Analysts work in a pivot-table-like, but significantly more comprehensible, interface. You drag and drop dimensions and measurements to row and column assignments, and you can just as easily create filters or pick from a narrow, but serviceable, selection of visual display types. I found the interface very fluid for navigating data dimensions and responding to answers with follow-up questions.
Shops willing to throw development resources at Tableau can extend it through the declarative programming interface, VizQL. This “visual query language” is designed for describing visual graph elements and data tables. VizQL statements map database tuples (ordered sets of data) to drawing format specifications; you can also compile it into SQL or MDX (Multidimensional Expressions).
Execution speed and scalability were not a problem. Tableau’s execution in screen response and refresh rendering was as fast as my back-end data permitted, roughly akin to Excel pacing.
Overall scalability, however, is going to be a strongly site-specific variable. Because Tableau provides only the visual presentation layer of an overall BI solution, it neither improves nor degrades the scalability of a solution, which is dictated by database, data mart, or OLAP-components infrastructure deeper in the stack.
The final tally
Tableau strongly deserves the immediate attention of any organization looking to deploy lightweight BI tools that are easy to buy, deploy, and maintain. At $999 for the Standard Edition, Tableau erases a BI entry barrier by designing the most flexible acquisition and deployment standard available in a high-torque BI front end.
There aren’t many drawbacks to Tableau’s products. The flexibility of the Tableau deployment will work perfectly for SMBs because it doesn’t require a total standardization on a single BI vendor’s offerings; at the same time, the suite serves many tactical needs for larger enterprises. I hope in the future they can take their “kinder, gentler” pivot-table UI and come up with something that breaks that model’s stranglehold on the category (pivot-table models can be a choker that limits deployment to those with very particular work styles).
After years of software distribution tending toward bigger and more complex purchases, it’s refreshing — nay, intoxicating — to see a significantly useful tool sold as a shrink-wrapped product that’s easy for IT to figure out how to buy, install, and maintain — and that costs roughly one-tenth the per-seat price of many competitors’ deployments.
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