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Loading...I love this type of visual charts that represent the numbers in a different way. This one from the analysis point of view is not useful, at least to me, but it’s a nice perspective to see how it goes.
https://www.finviz.com/map.ashx
Today, we have almost all green:
(No Ratings Yet)Loading...I found this web that publishes different data related to the oil production and their derivates.
You can download the data and prepare more detailed reports, or you can use the graph chart available to draw simple charts.
(No Ratings Yet)Loading...This couple of videos helped me to understand how agility can be implemented into complex software development environments.
A lot of agility knowledge shared in these videos, and so many topics related to SAFe,
In video #2 there is an explanation about how to lead with chaos and bureaucracy that is really interesting (starts in minute 9:00), and it is represented by this picture:
(No Ratings Yet)Loading...Time to learn, time to read, now working on a deal where the customer is implementing their own version of SAFe.
There are a lot of documentation and intelligence on all of this, very interesting time learning about it.
Something I do not like is that is a closed community, I understand that organizations need ways to finance themselves, but to impose a training payment is a stopper for the expansion of these practices.
(No Ratings Yet)Loading...I was yesterday night navigating onto the different charts and data that are available in this web: https://tradingeconomics.com
The purpose is to define a set of macro indicators that enable me to contrast macro trends into a sector, so I can advance in general terms the trend of the sector or identify a divergence.
For instance, the manufacturing sector has a lot of dependency on:
Here I can check all this. The difficulty is going to define the right indicators to check, and simplify the amount of data to be reviewed.
(No Ratings Yet)Loading...Esta es una pregunta que muchos en España nos hacemos con el incremento progresivo de la tarifa de la luz.
Han surgido mucha competencia con los cambios legislativos y esta solución es muy interesante para responder la pregunta y para entender las variables que influyen en el precio final de la factura.
El Tarificanator, la solución para saber qué tarifa de la luz es mejor para tu casa: PVPC o mercado libre
Este artículo, que merece varias lecturas para entender bien los detalles, contiene un enlace a una excel que ayuda a realizar el ejercicio y que ayuda a entender las variables que influyen.
Gracias a la consultora Ingebau por su publicación.
(No Ratings Yet)Loading...I continue being curious about OSINT, and I found this project named Open-source Twitter Intelligence in GIT Hub .
It’s a set of code that do scraping on Twitter without using Twitter’s API, allowing you to scrape a user’s followers, following, Tweets and more.
Apparently Twitter’s API has some limits and this approach avoid them.
It’s written in Perl, so I cloned with PyCharm, I uploaded some libraries and I created a test.py file that enabled me to test it:
import twint c = twint.Config() c.Username = "joa_pen" c.Custom["tweet"] = ["id"] c.Custom["user"] = ["bio"] c.Limit = 10 c.Store_csv = True c.Output = "none" twint.run.Search(c)
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3.00 out of 5)Loading...Leyendo documentación sobre seguridad y tratando de entender como se ponen en práctica los conceptos de OSINT, encontré un vídeo sencillo de como usar EO-Ripper.py para rastrear correos electrónicos y sus contraseñas:
Me pareció curioso probarlo, de manera que encontré un hueco días más tarde.
Los pasos que di esta vez han sido:
(No Ratings Yet)Loading...I do not why, but sometimes I feel identified with this meme.
Being a Project Manager is easy, it’s like riding a bike. Except the bike is on fire, you’re on fire, everything is on fire and you’re in hell
(No Ratings Yet)Loading...On August 3rd 2018 I wrote about some behaviors of S&P. These behaviors and my desire to develop reports to understand trends at monthly level took me to draw this figure the same day:
At the end of August I took the decision that I was going to sell the majority of my positions. I did it.
In September I was astonished with the defiance to gravity of the market and a little bit pissed-off with the trend.
Now in October, specially in the second half of the month, I have seen how this has been evolving. The Q3 closing reports seemed to be the flutter of the butterfly that changed the trend.
It’s just a graphic, it’s just a figure, it’s just a coincidence, but I’m happy about all I learned to be able to draw it.
