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Analytics

Data engineering in 2020

Data Engineers are forever flying the flag for open-source technology. But now that we’re safely locked away in our homes - potentially for the rest of the year - a new danger looms: That we get distracted by our new data tools and lose touch with delivering value to the business. Today most Data Engineers around the world are working from home, and at first glance it may seem like this works. After all, a solid internet connection is all we need to carry on doing what we were doing...

How we build custom data extractors to meet client ETL Needs

On one of our webinars in April 2020 we talked about the developer portal and how our developer community are pushing the Keboola Connection platform into places that often surprise our own core team. Our partners often are the creative ones, adding their knowledge and expertise to expand our platform in service of our shared customers and their varying needs. This is a guest post, written by Johnathan Brook, Solutions Architect at 4 Mile Analytics.

Databases Demystified Lesson 1 Introduction to Databases and SQL

In the first episode of Databases Demystified with Michael Kaminsky, we give a high-level overview of the most important concepts in databases. We start with a brief history of databases going from the invention of relational databases through present day and we talk about the differences between analytical and transactional databases, distributed and single-node databases, and in-memory vs on-disk databases We finish up talking briefly about SQL and what makes it special.

Are Your Machine Learning Models Wrong?

In addition to the very real negative impact on every person around the world, the COVID-19 pandemic is driving business disruptions and closures at an unprecedented scale. Enormous government stimulus programs are resulting in explosions in fiscal deficits, regulators are relaxing capital constraints on banks and central banks are supporting economic stability with a range of interest rate cuts and other stimulus measures.

5 Challenges of Building Data Applications

Fast-growing software companies are building data applications for a variety of uses, from marketing apps that provide customer insights, to IoT apps that handle device feedback, and data analytics apps that process both historical and near real-time data. But developers often face obstacles when building, designing, and supporting applications that need to parse large volumes of information.