Integrating databases in different locations to create a unified database - database

I am working on a research project where we are trying to build a machine learning model for a disease prediction. For this we have data from hospitals around the country. The problem is each hospital is having their own database model(RDBMS, Nosql), different column names for patient records. Are there any solutions available on how to integrate all this data to create a machine learning on top of it?

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Combining multiple databases in Notion

I am more familiar with Excel but want all my information in Notion since it’s so powerful.
I’m trying to track weeks of results for multiple individuals on a team. I would like to see a team view but also see the individual performance on a weekly basis.
I want to have the information from each team member rollup to the database that has the sum of all teams for that particular week.
Team page
Teammate 1
Teammate 2

Mass Updating prices in a 2000 articles sql table

I'm completely new in the e-commerce - SQL world and I'm seeking some expert opinion.
I just built an book store e-commerce. The table has 2000 book records and the user until now has edited the prices in Excel with formulas where he bulk edits hundreds (or thousands) of prices at once, associating the isbn number of his catalog's books with the isbn numbers of the spreadsheets the editorials sent him.
Now they'll sale books online with this e-commerce and i was wondering what is the best way i can get them a tool to solve that problem since it's insane for them to edit the prices one by one.
I built a really reactive form with javascript events but still they're still editing one by one which isn't a solution.
The site was built with laravel 5.7.
You can upload the excel file and update the records using book ISBN. Just read from excel and update in sql

Cassandra - How to model this use case?

I am new to Cassandra, my question may be silly so please excuse me for that. I have a confusion on how to create the DB model for following use case. Using company-employee example for better understanding
There is a company having employees. One employee (may be senior) can work on different projects at the same time. In each project the employee has to perform different role ( software engineer, software tester, software designer, technical lead,architect, project manager, etc) due to seniority.
Also the employee's duration in each project (2 months, 4 months, 3 weeks, etc) is different. The employee's working hours are different in each project (2 hrs/day, 1 hr/week, etc)
Now the problem statement is how can I model this use case. How can I store the data of employee working for different project with different role with different duration and different work hours? Can I fit this information in one row of a table or do I need to create multiple rows for that employee?
Please, if possible, give details.

Which database to use for highly-connected data model with frequent schema changes?

I am currently working on a project, where we use web mining (web crawlers) to build up a company database. At the moment we employ PostgreSQL as our main database, however, I feel it will cause a lot of problems in the future, because as our crawler develop and extract more data we'll see many schema changes/additions.
Some examples:
At the moment we store one address per company, but at one point we might want to store multiple addresses. (1 - 1 relationship transforms to 1 - n, or even n - n)
Companies in different industries have very different attributes, e.g. for we have a lot of NULL-fields in our relational schema at the moment.
Different degrees of information available, e.g. for some companies we only know the CEO's name, which could be stored in a single attribute of the company. For other companies we might want to use a relationship to a Person relation, because we have a photo, birthdate, CV etc... (the schema is not fixed)
What kind of database would be suited for such a task? I've looked into MongoDB, Neo4J, OrientDB. Some requirements which are important for us:
No license fee for non-open-source commercial projects
Should scale to storing 100GB - 1000TB, while executing OLAP queries for displaying a web interface (company query interface) in millisecond range

Has anyone 'integrated' databases using an ontology tool such as Protege?

I don't know that 'integrated' is the correct word, but has anyone had to build a knowledge base by integrating multiple disparate databases together? For example, if I were to build an ontology linking a car value ($) database with my personal finance database, I'd want to be able to build a query to find out "Can I buy a Delorian?" I'm wondering what tools/methods people have used to build this sort of thing.

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