Let's start with the next session, and the last session of the day, which is a lighting
talk by Yordi, you see throughout your vets, a business intelligence architecture for social
and solidarity economy.
So, I would say you.
Thanks very much.
Good evening, first nightly session, the last and maybe the list.
But, go on.
I'm going to talk about business intelligence architecture for social and solidarity economy.
I'm Jordi Seljuvet.
I'm the tensioner.
In my city, I put the tensioner and business intelligence and security issues.
But, it's a lie.
I'm a SQL-Holigan.
I'm working in co-depth.
It's a worker's cooperative.
We call a self-resover for social economy.
We only use free software, we only work for social and solidarity economy entities.
But, what social and solidarity economy is?
Social and solidarity economy refers to a wide range of economic activities that tend to
prioritize social and profitability instead of poorly financial profits.
NGOs, cooperatives, associations, foundations, and all type of entities that
want to transform the world to become a better place.
And, of course, social and solidarity economy companies like other companies need to make decisions based on data.
Sometimes they don't know.
Sometimes they don't want to know.
Sometimes they uncomfortable with that.
But, they need it.
When you want to develop business intelligence project from social and solidarity economy,
first of all, you need to analyze how we social and solidarity economy.
Okay.
You can find car sharing co-operative, telecommunications co-operative.
Lawyers or bulls, architecture bulls, marketplaces, supermarkets and a lot of different kinds of stores.
Schools and a lot and a lot of different businesses.
Sometimes you can find many mature IT departments and databases with thousands of millions of
rows.
Sometimes you can find databases with hundreds of thousands of rows.
And sometimes you find it with rows.
Sometimes you can find entities with only one data source, traditionally an ERP.
Usually you find entities with a lot of different data sources.
Sometimes you find entities with a low budget.
Usually you find entities with a very low budget.
Don't worry.
You never find entities with a high budget.
And of course, you have to develop business intelligence project on any kind of project for social and solidarity economy.
You must use visual.
But not for price because sometimes Google or Microsoft offers free tires for NGOs.
The importance is for building community for sharing knowledge for protecting user privacy in short for freedom.
We have seen that we have a very different kinds of entities in social and solidarity economy.
We have different needs and different architectures.
And also they have a very low budget and they want to interoperate.
Then we need to build different architectures.
And we build different architectures for each type of entity.
Smalls, mediums, large, or asteroids.
Its architecture is based on the previous level.
Then you can start as a small entity and then install the new components.
If you become a medium company.
All architectures are modular.
You can quit from element and install other.
For example, you don't want dbt plus alpha for ETL.
You can install Apache Hop, for example.
And if you, and all entities, all architectures are based on the previous one.
If you become, you start as a small company and then you become a medium.
You only have to install the new components, not the other parts.
Okay.
Hop, hop, hop, hop, we don't it.
We use Ansible.
Because Ansible allows us to choose what to deploy in in this case.
With very eyeballs, with tags.
You can choose if you want to install the progress and the dbt and the superset or whatever you need.
If you are a bigger, you can install a staging area at the lake and so on.
It allows to have to different environments.
The tech changes in software and company relations.
If you define a new variable in your Ansible, then you will install the new components.
If you start a medium company and then you become a large company.
You define the new variables and then Ansible detects these changes and install the new components.
Then you need.
And also, else to encourage variables.
And what we have done from comp depths.
We have an Ansible provisioning of this architecture.
With all the variables, with all the tags.
In order that you can test, you can share in your own communities.
You can do merge requests, you can invest and whatever you want.
With this architecture.
In order to provide all such and such a utility economy.
A architecture for the business intelligence projects.
And also we have Ansible inventories.
With variables defined for our customers.
All are in clear because Ansible and Ansible are in clear variables.
But if you want to test it, you only have to change the capabilities for your own databases.
And deploy on your own servers.
And then you can test the architectures.
Okay.
Let's see some architecture components.
We are going to see the data or housing.
The ETL process and the database relationship.
For data or housing, we use podcasts.
Because it's free because it's robust and has a good community.
And also has extensions.
I like a lot to extensions.
One is time scale.
Not all of us to write very efficient queries from time series.
That it's the most used case in data or housing.
And the other is data for internet or wrapper.
For internet or wrapper, all of us as to access different data sources.
As if they were in the same database.
You can cross different sources.
For example, CSV approaches database.
And my SQL and other projects database in only one query.
And it's very nice for first thing to market.
If you have small companies or million companies with little data.
Because you can cross data very easily from all the sources.
And then put it in a superset and basically.
It allows to simulate the E of an ETL process.
Because it's similar that you have the data on your own server.
But it's not on your own server.
Then if you have a big databases, you will have a big effort with that performance.
How do you solve that with the ETL?
We solve with the ETL because it also does it transform a lot of an ETL system.
And it's SQL in had to be changed.
And for SQL, it's very nice because you can do ETLs only with SQL.
And also, it assumes that an ETL documentation automatically.
I have two things in the world.
Races people are working in documentation.
And the details of me the second one, partially.
Intatso has time control, data quality, and so on.
In green, data sources.
Blue, the medium pass, in orange, the final table.
All tables with the columns, with the time column automatically,
without doing anything.
We can see in the previous talk that you can add more information on your models,
with the description, the description of its case.
But automatically, makes this only with SQL plus little ginger and some more information.
ETLs on the ETL lineage, only with SQL.
Finally, for data visualization, we use superset.
We have seen three cults previous.
It's an iterative session for BWR, with SQL plus ginger, if you want.
And with filters, it's a standard session, user control,
really, really security.
That's very powerful.
This is the powerful feature.
Embring graphics in all websites, set service charts.
Your users can make your charts with track and drop.
That's very nice.
We can see, as well, you can change the colors.
I'm very bad choosing the colors.
But you can do graph, choosing the type, and then,
that can drop for data sets.
That's very nice.
Finally, I want to emphasize the importance of free software
for social and solidarity economy.
Because it allows to have all types of projects,
but specifically, business intelligence projects and systems,
and strengthening the community, protecting the user privacy,
and helping the intercombration.
Thanks very much to everyone to develop, to support, to use free software.
Please don't stop doing that.
It's very important for changing the world and changing the economy.
You want to test our architecture or enhance our architecture.
We are very happy to accept full request,
and share on your own communities,
and things like match, that's all.
Thank you.