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Data Science and Egineering

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What Is a foreign key?

What is a foreign key constraint? Why is it important in relational databases? Find out all about foreign keys in this article.

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Facts and dimensions in a data warehouse?

Facts and dimensions are the fundamental elements that define a data warehouse. They record relevant events of a subject or functional area (facts) and the characteristics that define them (dimensions).

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Useful database tools for SQL server

Is creating complex SQL Server databases a challenge? Read on and discover our top SQL Server database tools.

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How to interview A data analyst candidate

How do you usually interview a data analyst candidate? In this article, I’ll share some of the guidelines and areas you can focus on when interviewing a data analyst candidate. These serve as pointers to aid with your interview.

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Google BigQuery architecture

A good understanding of BigQuery architecture is useful when implementing various BigQuery best practices including controlling costs, optimizing query performance, and optimizing storage.

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Get started with ETL: tutorial

We’ll provide an overview of ETL, and a few generic examples of key ETL tasks, such as data extraction, header and trailer processing and data masking, which you can apply to your specific environment.

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3 Ways to build an ETL process

Well, wish no longer! In this article, we’ll show you how to implement two of the most cutting-edge data management techniques that provide huge time, money, and efficiency gains over the traditional Extract, Transform, Load model.

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Data lake vs. data warehouse

In this page we’ll define these strategies, explain the differences, and show that “data warehouse vs. data lake” is no longer the question. The two technologies go hand in hand, especially as many move to cloud-native data infrastructure.

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DB vs. data warehouses vs. data lakes

Perhaps you’ve heard the terms “database,” “data warehouse,” and “data lake,” and you’ve got some questions. Are these different words to describe the same thing? If not, what are the differences? And when should you choose one over the other? We’ll explore answers to these questions and more in this article.

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Top 10 data science myths busted

With the popularity of data science, there are a lot of myths about it that circulate around. If you’re interested in pursuing a career in data science, it’s important to be aware of these myths and bust them.

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What is data mining? Concept & application

But what good is all this stuff? Although corporate raw data is rich with potentially useful information, the number and enormity of databases make extraction of actionable business knowledge quite challenging.

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Beginner’s guide to big data

Big data is a term that describes datasets that are too large to be processed with the help of conventional tools and also is sometimes used to call a field of study that concerns those datasets. In this post, we will talk about the benefits of big data and how businesses can use it to […]

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A beginner’s guide to data mining techniques

Companies use data mining to analyze recorded data, such as user preferences, sales figures, and historical inventory levels. If they are able to identify trends and recurrent patterns in this data, they can make better decisions. In this blog post, we will look at how data mining differs from machine learning and what data mining […]

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Data warehouses vs. data lakes vs. data lakehouses

The most popular solutions for storing data today are data warehouses, data lakes, and data lakehouses. This post gives a detailed overview of these storage options and their pros and cons for specific purposes.

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