Business Platform Team

Anant Corporation Blog: Our research, knowledge, thoughts, and recommendations about building and managing online business platforms.

Tag Archives: data processing


Cover image for Data Engineer's Lunch #26

Data Engineer’s Lunch #26: Akka Actors for Data Processing

In Data Engineer’s Lunch #26, we will discuss how to use Akka Actors for concurrent data processing operations. The live recording of the Data Engineer’s Lunch, which includes a more in-depth discussion, is also embedded below in case you were not able to attend live. If you would like to attend a Data Engineer’s Lunch live, it is hosted every Monday at noon EST. Register here now!

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Introduction to awk for data engineering

Data Engineer’s Lunch #16: Introduction to awk for Data Engineering

In Data Engineer’s Lunch #16: Introduction to awk for Data Engineering, we introduce awk, a domain-specific language and text processor, and how we can use this tool for data engineering. The live recording of the Data Engineer’s Lunch, which includes a more in-depth discussion and live walkthrough, is also embedded below in case you were not able to attend live. If you would like to attend Data Engineer’s Lunch in person, it is hosted every Monday at 12 PM EST. Register here now!

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Data Engineer’s Lunch #4: Airflow for Data Engineering

In case you missed it, the fourth installment of our weekly data engineering lunch was presented by guest speaker Will Angel. It covered the topic of using Airflow for data engineering. Airflow is a scheduling tool for managing data pipelines. The live recording of the Data Engineer’s Lunch, which includes a more in-depth discussion, is also embedded below in case you were not able to attend live. If you would like to attend a Data Engineer’s Lunch live, it is hosted every Monday at noon EST. Register here now!

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Database Aggregations for Machine Learning

The first part of any machine learning project is to gather data. This sounds easy. You may think that this puts you in the perfect position to work with data you have in relational databases. In some circumstances that may be correct. However, most of the ways that we store data in databases for business platforms are sub-optimal for using machine learning. They require more work to gain the insights we want out of our data.

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modern library

Data & Analytics Trend 2 – Augmented Data Management

This is the second part of our “Diving deep into Gartner’s Top 10 Data and Analytics Technology Trends for 2019” blog series. In this series, we’ll explore the top 10 Data & Analytics 2019 trends identified by Gartner. If you haven’t yet seen the first post on Augmented Analytics check it out here.

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