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Track Custom Events with Google Analytics

You've probably heard of Google Analytics before. We all use the tool to track various things on our websites. The tool provides information such as the location of users, page views, the kind of devices and browsers used by those users, the age group, and a lot more. But what if you want to track certain events which are specific to your website? Say you want to track how many people filled a form, or how many people clicked a link on your website? Google Analytics provides an unbelievably simple way to track these custom events. It's actually just one line of code to track such events. Let's see how you'd do just this. When you create a Google Analytics account, the tool

Data Automation with AI/ML: A Comprehensive Guide

AI

The article discusses the transformative impact of artificial intelligence (AI) and machine learning (ML) on data automation, enhancing efficiency, decision-making, and scalability in businesses. It explores trends like generative AI, AutoML, data governance, and democratization while providing real-world applications across various industries, ultimately guiding businesses in effective AI/ML integration.

Real-Time Data Processing: Understanding the What, Why, Where, Who, and How

data processing

In today’s data-driven world, businesses and organizations are continuously generating massive amounts of data. While processing data in batch mode remains useful, the need for instant decision-making has led to an increasing focus on real-time data processing. This article delves into what real-time data processing is, why it's essential, its various applications, the tools used to achieve it, trends shaping its evolution, and real-world use cases. What is Real-Time Data Processing? Real-time data processing refers to the capability to continuously ingest, process, and output data as soon as it is generated, with minimal latency. Unlike batch processing, which collects and processes data in large groups at set intervals (e.g., daily or hourly), real-time processing works with data immediately as it becomes available,

Exploring the Inner Workings of Google BigQuery: A Deep Dive into Design, Competitors, Use Cases, and Pros/Cons

Google BigQuery

Discover the inner workings of Google BigQuery, a game-changer in big data analytics. Unravel its architecture, including the prowess of its distributed query engine, Dremel, and the innovative Capacitor technology. Compare it with competitors, explore diverse use cases from real-time analytics to healthcare, and weigh its pros and cons. Join us on a journey into the heart of data analytics excellence.

Understanding the Battle of Database Storage: Row-Oriented vs. Columnar

storage-disk

In the realm of database storage, row-wise and columnar approaches stand as stalwarts with distinct advantages. Row-wise storage excels in transactional operations, ensuring data integrity with simplicity. Conversely, columnar storage revolutionizes analytical querying, leveraging vertical organization for rapid attribute retrieval. Understanding their nuances is pivotal in crafting efficient, tailored database solutions for diverse data-driven needs.

Cleaning and Normalizing Data Using AWS Glue DataBrew

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In this post, we’ll see what is AWS Glue DataBrew and how to use it to clean and transform our data in a data pipeline.

Getting Started With JanusGraph

janusgraph

JanusGraph is a graph processing tool that can query distributed graph data in milliseconds. In this post, we’ll see how to get started with it.

Kinesis Data Streams vs. Kinesis Firehose Delivery Streams

sheep

I have talked about Kinesis before, and I'm sure you've been using Kinesis for longer than me. But according to what I've seen, not all teams or companies use all parts of Kinesis. And, there are four parts in Kinesis: Ingest and process streaming data with Kinesis streams - Kinesis Data Streams Deliver streaming data with Kinesis Firehose delivery streams - Kinesis Firehose Delivery Streams Analyse streaming data with Kinesis analytics applications - Kinesis Analytics Ingest and process media streams with Kinesis video streams - Kinesis Video Streams All these four parts offer something different. Well, the last two are definitely different than the first two. But it's the first two that I see a lot of people getting confused with. So I thought I'll

Data Science vs. Artificial Intelligence vs. Machine Learning vs. Deep Learning

It’s very common these days to come across these terms - data science, artificial intelligence, machine learning, deep learning, neural networks, and much more. But what do these buzzwords actually mean? And why should you care about one or the other? I’m trying to answer these questions in this post, to the best of my capacity. But then again, I’m no expert here. This is the knowledge I’ve gained in the last few years of my data science and machine learning journey. I’m sure most of you will have better and easier ways of explaining things than I do, so I’ll be looking forward to reading your comments down below. Let’s get started then. Data Science Data science is all about data,

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