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Faster XML Parsing with Elixir

The XML data format has been around since 1996. It was first envisioned as a lingua franca (bridging language) for data to be serialized and read into completely disparate systems (with different programming languages, operating systems, and even hardware). It has been wildly successful in that goal. In software, though, 26 years is like a lifetime — and in hardware, it's an eternity.

Yellowfin Named Embedded Business Intelligence Software Leader in G2 Fall Reports 2022

Yellowfin has again been recognized in the Leader quadrant in the 2022 G2 Fall Grid Reports for Embedded Business Intelligence (Enterprise and Small Business). This is Yellowfin's 13th quarter in a row to be named a leader in a G2 Grid Report. The Yellowfin team are grateful to our customers for the reviews they have provided for our embedded analytics capability and product suite on G2, a leading business software and service comparison source for trusted user ratings and peer-to-peer reviews.

7 Best Data Pipeline Tools 2022

The data pipeline is at the heart of your company’s operations. It allows you to take control of your raw data and use it to generate revenue-driving insights. However, managing all the different types of data pipeline operations (data extractions, transformations, loading into databases, orchestration, monitoring, and more) can be a little daunting. Here, we present the 7 best data pipeline tools of 2022, with pros, cons, and who they are most suitable for. 1. Keboola 2. Stitch 3. Segment 4.

Introduction to Automated Data Analytics (With Examples)

Is repetitive and menial work impeding your data scientists, analysts, and engineers from delivering their best work? Consider automating your data analytics to free their hands from routine tasks so they can dedicate their time to doing more meaningful, creative work that requires human attention. In this blog we are going to talk about: Now let’s dive in.

Fraud Detection in Insurance Claim Process by Using Artificial Intelligence

One of the biggest preventable losses that hurts insurers worldwide is fraudulent insurance claims. The P&C segment accounts for the most fraudulent insurance claims, with auto insurance and workers’ compensation making up the biggest percentage of fraudulent claims that have an annual impact on the insurance business.

How to Do Data Labeling, Versioning, and Management for ML

It has been months ago when Toloka and ClearML met together to create this joint project. Our goal was to showcase to other ML practitioners how to first gather data and then version and manage data before it is fed to an ML model. We believe that following those best practices will help others build better and more robust AI solutions. If you are curious, have a look at the project we have created together.

A Guide to Principal Component Analysis (PCA) for Machine Learning

Principal Component Analysis (PCA) is one of the most commonly used unsupervised machine learning algorithms across a variety of applications: exploratory data analysis, dimensionality reduction, information compression, data de-noising, and plenty more. In this blog, we will go step-by-step and cover: Before we delve into its inner workings, let’s first get a better understanding of PCA. Imagine we have a 2-dimensional dataset.