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Amiato’s big data A/B testing solution will help the little guy as well as the big beasts with big IT teams

The term “big data A/B test­ing” is almost guar­an­teed to induce a throb­bing sen­sa­tion in the tem­ples of the aver­age prod­uct man­ag­er.  Vital­ly nec­es­sary but com­pli­cat­ed and tedious, most prod­uct man­agers will go run­ning for the near­est engi­neer or IT admin­is­tra­tor for help. But a new prod­uct from Palo-Alto-based start­up Ami­a­to deliv­ers sophis­ti­cat­ed A/B test­ing analy­sis on a big data scale for medi­um-sized enter­pris­es which may have very lean IT and engi­neer­ing support.

Bridg­ing a gap in the data analy­sis market

Amiato’s offer­ing requires lit­tle in the way of IT exper­tise; a pass­ing acquain­tance with SQL – which many prod­uct man­agers already have – is all it takes.  It’s clev­er­ly bridg­ing a gap in the big data analy­sis mar­ket: tools like Google Ana­lyt­ics, Opti­mize­ly and Mix­pan­el pro­vide real-time test­ing feed­back but, user-friend­ly though they are, they don’t let users ask many ques­tions. Any­one who wants to dig deep­er and dis­cov­er the “why” of what’s hap­pen­ing on, say, their web­site had bet­ter have good tech­ni­cal team on hand. Sophis­ti­cat­ed tools like Google Big­Query, Splunk and Cloudera’s Impala can do this kind of thing, but they’re not for tech­ni­cal novices – IT admin needs to work on the data logs to get them into the right for­mat before they’re loaded.

That’s time-con­sum­ing and intim­i­dat­ing for mid-lev­el firms with scant engi­neer­ing resources. But Ami­a­to has come up with a near-ide­al solu­tion for these firms. Users can sim­ply load JSON files or oth­er types of semi-struc­tured data into Amiato’s sys­tem with­out the need for any kind of pri­or tech­ni­cal “mas­sag­ing.” Files can sim­ply uploaded into an Ama­zon S3 buck­et (it’ll even take a full data dump) and Ami­a­to auto­mat­i­cal­ly works out the struc­ture and then maps it straight onto a table.

A prod­uct manager’s dream?

Ami­a­to co-founder Mehul Shah says that the prod­uct, which has just bagged $2 mil­lion in invest­ment and is avail­able to cus­tomers now for free test­ing, is tar­get­ed on prod­uct man­agers or advanced prod­uct man­agers in com­pa­nies spe­cial­iz­ing in fields like online retail­ing or gaming.

As Shah put it, it’s for firms that have out­grown off-the-shelf tools but are “scared of fig­ur­ing out how to put togeth­er a huge data team and work with huge pieces of infra­struc­ture.”  All in all, it looks like this devel­op­ment is going to make a lot of prod­uct man­agers hap­pi­er folk — not to men­tion chief rev­enue officers.

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