What is Microsoft Fabric? In its essence, Microsoft Fabric is a suite of integrated individual analytic tools and services that work together to provide a unified end-to-end analytics experience. It is a SaaS (Software as a Service) product, which means … Read More
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DataOps and data processing
DataOps is a combination of practices, frameworks, architectural patterns, and cultural norms. Its purpose is to help you mitigate the obstacles to managing data with quality and efficiency. This set of practices can bring significant benefits linked to its three … Read More
Unlocking the power of data with dbt
dbt represents a paradigm shift in the way organizations approach data transformation, offering a modern, collaborative, efficient solution for managing data pipelines. Whether you opt for a cloud solution with a managed platform or deploy dbt in an on-premises solution … Read More
Machine Learning model monitoring: types of drift
After having decided on the best type of machine learning model and building it, we need to be aware that a working model will probably have to deal with different patterns of data from those used to train it. This … Read More
Business Intelligence: how to define a governance strategy
Atualmente, as empresas estão a aumentar a sua cultura mais analítica, o que as ajuda a tornarem-se mais data-driven. À medida que essa transformação acontece, existem alguns pontos a ter em conta, sendo um deles a organização de todos os … Read More
BI Framework: why you should have one for your data pipelines
Nowadays, every company has data needs. The way that data is treated and governed has a lot of processes that can be overwhelming at some point. Sometimes, when working with company data, your employees, especially developers, can see themselves developing … Read More
Data Analysis with Write-Back: the next step for Tableau CRM
If you got to this content, certainly you already have considered using tools such as Tableau and Salesforce. But do you know how to enhance its use, how to collect and analyze data the best way possible, and how to … Read More
Guide for monitoring machine learning models
In the dynamic landscape of data science, building and deploying machine learning models is just the beginning. To ensure sustained success and optimal performance, continuous monitoring of these models is crucial. Model monitoring in the data science pipeline involves tracking, … Read More
Data Science Assessment: how to analyze a project’s viability
A importância dos dados é amplamente reconhecida em vários setores e saber aproveitá-los representa um fator essencial que pode trazer uma vantagem competitiva substancial ou mesmo transformar a estrutura fundamental de uma empresa. A área da Data Science tem uma … Read More
Machine Learning model deployment: Why it matters and how to do it
You’ve spent weeks, maybe months, perfecting your machine learning model. The data is clean, the features are engineered and the model’s performance is stellar. But none of that really matters until your model is deployed – until it’s out there, … Read More