A buyer’s guide for enterprise software

Through a series of Big Data consulting missions that were overlapping with the entire IT landscape, data being all over the place, I have observed software purchasing processes of many large companies. Being also an enterprise software vendor myself, I have been baffled countless times by broken buying processes that lead smart people routinely choose about the worst price-quality ratio that the market has to offer. In this post, I am trying to gather a survival kit for buying enterprise software.

8 tips to turn your Big Data into Small Data

Hectic times. Looking at the last entry, I realize it has been half a year already since my last post. The Big Data projects I do, and the more I realize how usually scalability aspects for business projects are irrelevant to the point that the quasi-totality of the valuable data crunching processes could actually be run on a smartphone if the proper approaches are taken. Obviously there is no point in actually doing the analysis on a smartphone, this merely illustrating that really it does not take much computational power.

Big Data: choosing the problem before choosing the solution

My company has started several important big data missions, and I am taking here the opportunity publish some insights are are relevant to all those initiatives. A major (and frequent) pitfall of the Big Data projects consists of starting with a solution instead of starting with a problem. In particular, software vendors (Lokad’s included) are pushing their own Big Data recipe which will randomly involve: Hadoop SAP HANA HBase Amazon EC2 Cassandra Windows Azure Storm Node.

A few tips for Big Data projects

At Lokad, we are routinely working on Big Data projects, primarily for retail, but with occasional missions in energy or biotech companies. Big Data is probably going to remain as one of the big buzzword of 2012, along with a big trail of failed projects. A while ago, I was offering tips for Web API design, today, let’s cover some Big Data lessons (learned the hard way, as always).

Happy talk detector

Over the last couple of months, I have been pushing a lot of content on my company website (Lokad.com), and proofreading a lot of texts produced by colleagues too. The more I write, the more I realize that fighting our innate instinct to produce happy talk is a tough battle. Recently, I came up with a simple rule to detect most happy talk content: When by replacing a sentence by its negation, the resulting message seems totally out of place, then, odds are that the sentence was not carrying much of a message in the first place.

Bizarre pricing, does it matter? (B2B)

My company has just released quantile forecasts upgrade. It’s no less than a small revolution for us, however, unless you’ve got some inventory to manage, it’s probably not too relevant to your business. Another salient aspect is our new pricing for quantiles (the old pricing for classic forecasts remains untouched). Lokad is selling a monthly subscription, and if qiqiqi represents one of the actual quantile values retrieved by the client during the month, then the monthly cost CCC is given by:

Cloud questions from Syracuse University, NY

A few days ago, I received a couple of questions from a student of Syracuse University, NY who is writing a paper about cloud computing and virtualization. Questions are relatively broad, so I am taking the opportunity to directly post here the answers. What was the actual technical and business impact of adopting cloud technology?. The technical impact was a complete rewrite of our codebase. It has been the large upgrade ever undertaken by Lokad, and it did span over 18 months, more or less mobilizing the entire dev workforce during the transition.

Goodbye Subversion, you served me well

I had been a long time Subversion user even before I started my company. Since 2006, the data analytics core of Lokad had been managed over SVN which proved to be a very robust piece of software (combined with TortoiseSVN). We had a few hiccups where the easiest way forward was to delete the local version and check-out again, but otherwise, our SVN hoster has been operating flawlessly over 5 years, which is a long time as far software technology goes.

MathJax, at last a decent way to post maths on the web

For a long time, posting something as simple as a square root on the web has been a major pain. Despite MathML having been around for years, Firefox is still the only browser (that I know of) to render MathML correctly. p=Φ(2ln(12π−−√MH)−−−−−−−−−−−−√)p=Φ(2ln⁡(12πMH)) p=\Phi\left(\sqrt{2\ln\left(\frac{1}{\sqrt{2\pi}}\frac{M}{H}\right)}\right) Recently, I did stumble upon MathJax, an outstanding JavaScript rendering engine for mathematics that works for all major recent browsers. The syntax is derived from the one of LaTeX, and the output is either MathML (if you have Firefox) or plain HTML/CSS otherwise.

Instant transfer with Bitcoin but without 3rd parties

Update 2012-05-17: Double spending can be made extremely difficult through quasi-instant double spending attempt detection. See TransactionRadar.com as an illustration. I now believe that the ideas posted below are moot, because early double spending detection is just the way to go. Bitcoin is a crypto-currency (check out my previous post for some more introductory thoughts) that provides many desirable properties such as decentralization, very low transaction fee, digital-native, … However enabling instant payment has not been a forte of Bitcoin so far.