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Data Science Week - microanons for those who do not know

It is logical that recently the number of various conferences and other public events in the field of data analysis has increased dramatically. Surely many have already heard about OpenData or PyData , and someone, for sure, even been to them. But we all know perfectly well that it’s not a trivial task to ask the leadership for an opportunity to go to the conference (even if you speak on it). The problem is that most of these meetings take place somewhere in the States (for example, in Texas) or in some other Sweden, so the budget for a trip, especially as part of a crisis, is not every office will allow itself to be allocated.

In Russia, however, there is a positive trend - many take the initiative and carry out such activities on their own. Even if these are not always global conferences, but more in-camera meetings, the MDS and MIDSM gather more and more interested people each time. And such meetings, by the way, are not only in Moscow.

It just so happened that after completing the Data Science courses under the wing of the Laboratory of New Professions, we became friends with many guys from there on the basis of big data, analytics, and other interesting nonsense. And yes, if you have read this far, you have already guessed that they are organizing another similar IT-festival, and I plan to visit it.

So, Data Science Week will be held in Digital October from August 24 to August 30. His program is as follows:
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24.08 Monetization of big data

Speeches:


25.08 Open Data

Speeches:


26.08 Data Scientist: Work Tools

Speeches:


27.08 Data driven business

Speeches:


28.08 Advanced Spark

Speeches:


08/29/30/08 Datathon

Judging by the program, comrades should be given their due - they could arrange daily net business reports with technical reports on different days as much as possible so that people from different spheres would have to miss as little as possible. The list may still be expanded / corrected, as there will be more details.

The first day is all about how to make money on big data in various industries: marketing and advertising, banking, telecom, recommendation systems. It will be especially interesting to hear about Bookmate and e-contenta collaboration in the field of building quality money-generating recommendations. I also recommend listening to the Data-Centric Alliance (telling about their DMP-system) to those who have no idea how the data from “raw” becomes “less raw”, and where is the monetization. In general, this is more likely to be more interesting to business people than to scientists and programmers, but, nevertheless, useful.

On the second day, it’s worth going, if it’s interesting not only how to make money on data science, but also how you can try using them to bring some public benefit. The key to positive developments in this area is open data. It is interesting to hear what is being done in this direction. In fact, data journalism and all sorts of “reports on reports” is a job akin to washing gold out of the sand, and with proper skill you can find real treasures there. It is rumored that even cones from the government of the Moscow region want to join the bigdate, but this is not yet confirmed. Although the fact that governmental analytical centers periodically recruit personnel for serious research in the field of urban planning and other magic is a fact.

The third day is probably the most technical. The classics of the genre and the familiar to many date-techies of the community - as always, you can listen to professionals about the experience of using any tools and pitfalls that they encountered. Using Akka in Facetz.DCA, Mahout - in REES46.com, IPython Notebook (now completely Jupyter) - in Ozone. Overview of solutions from Microsoft, IBM, Oracle for work in the field of Data Science. I know firsthand that the task of “building an analytical system” even in the eyes of the business looks extremely blurry, and at the development level one has to quickly select several of the hundreds of approaches, because trying all the options will not have enough time or money. So listen to those who have already sawed, still worth it.

On the fourth day, a whole set of business cases is planned on how to use Data Science in your daily work and improve business efficiency. Here and analytics, and recommendation systems. Remember, a couple of weeks ago there were contests from Avito on Kaggle and a couple more sites? So, as I understand it, the speakers are expected from there, who will talk about the results and, perhaps, even fill up the technical details from above.

The fifth day is completely devoted to the thing that people have been talking about so much lately - Apache Spark. IBM will come, who recently (July 2015) have seriously invested in the project, and promise, sort of, to tell you what they think about its future and how they are going to develop it. Another promise is a master class on the deployment of Spark infrastructure in 30 minutes. Wait and see.

Well, at the weekend there will be a dataton where you can try your hand at solving real problems in the field of Data Science. I'm not sure that I will get to it, but if I find time, I will try to describe my impressions, pros and cons. We will write down

Oh yeah, I almost forgot: the event is free, but registration is required, so be sure to register .

Source: https://habr.com/ru/post/265105/

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