|By Maureen O'Gara||
|April 4, 2013 05:15 AM EDT||
Tableau Software, the 10-year-old Seattle data visualization concern that turns complex databases and spreadsheets into interactive graphics, charts and maps thanks to the VizQL programming language and some patents it holds, filed its S-1 papers with the SEC last Tuesday to go public.
It’s looking to raise maybe $150 million.
Timing and price are of course still not definite and even the $150 million bogey is just a placeholder.
Goldman Sachs and Morgan Stanley will take it out although all the brand- name investment banks have a finger in the pot one way or another.
It will list on the Big Board under the ticker symbol DATA (sweet, wonder what it paid for that).
Tableau claims something like 10,000 clients, the non-geeks at Bank of America, Facebook, Apple, DuPont, Sears, Verizon and Coca-Cola, and its rivals – of which there are many – include IBM, Oracle, SAP, Microsoft, Tibco and Qlik.
Tableau’s revenues were $127.7 million last year, up 105% from the year before, with 70% coming from licensing and the rest from maintenance and services. Net income was down to $1.6 million from $3.38 million evidently because of the money it spent on sales and marketing and R&D.
Still, it’s profitable unlike other enterprise software companies that have IPO’d lately.
It’s expected to spend the IPO money on R&D and building out.
Tableau is an old-fashioned kind of place. It hasn’t gone to the cloud – at least not yet – so its SaaS adventure is presumably ahead of it.
By the way, IDC figures the business analytics market should be worth close to $51 billion by 2016.
One of Tableau’s founders Pat Hanrahan was a founding member of Pixar and got an Academy Award.
The company’s biggest outside stockholder is NEA with a 37.9% position for its $15 million investment followed by Meritech Capital with 6.4%.
Ovum wonders if Tableau can keep on growing 80% a year the way it has. It says it’ll have to manage shareholder expectations and push out of the department and into enterprise-wide deals.
It thinks it will also need new products “with more advanced and richer analytic capabilities and also factor in back-end data management (data integration, data quality and master data management) capabilities if it is to provide enterprises with a full Big Data analytics solution. All this while still preserving the culture that made the company and its products so attractive to customers in the first place.”
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