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Introduction Thanks to the continued push towards a privacy-first internet, first-party customer data has never been more important to digital organizations. With the imminent death of third-party cookies and the rising expectations of modern consumers, companies are quickly moving to invest in implementing scalable customer data infrastructures that can deliver on their many needs.
In today’s data-driven world, businesses collect and store vast amounts of data from various sources. However, raw data is often unstructured, inconsistent, and may not be immediately usable for analysis or decision-making. That’s where data transformation comes into play.
Summary Real-time capabilities have quickly become an expectation for consumers. The complexity of providing those capabilities is still high, however, making it more difficult for small teams to compete. Meroxa was created to enable teams of all sizes to deliver real-time data applications. In this episode DeVaris Brown discusses the types of applications that are possible when teams don't have to manage the complex infrastructure necessary to support continuous data flows.
In this digital world, Data is the backbone of all businesses. With such large-scale data production, it is essential to have a field that focuses on deriving insights from it. What is data analytics? What tools help in data analytics? How can data analytics be applied to various industries? We will be answering all these […] The post What is Data Analytics?
In Airflow, DAGs (your data pipelines) support nearly every use case. As these workflows grow in complexity and scale, efficiently identifying and resolving issues becomes a critical skill for every data engineer. This is a comprehensive guide with best practices and examples to debugging Airflow DAGs. You’ll learn how to: Create a standardized process for debugging to quickly diagnose errors in your DAGs Identify common issues with DAGs, tasks, and connections Distinguish between Airflow-relate
Mastering AI-Powered Product Development: Introducing Promptimize for Test-Driven Prompt Engineering originally posted here-> [link] AI, AGI, LLM, and GPT are the buzzwords of the moment. Like you, I’m excited, concerned, and constantly getting goosebumps as I try to keep up with everything happening in the field. It’s time for me to put on my helmet, secure it with duct tape, and contribute something that can help propel this frenzy forward ???
Data lakes have made the data-on-read schema popular. Things seem to change with the new open table file formats, like Delta Lake or Apache Iceberg. Why? Let's try to understand that by analyzing their schema evolution parts.
Data lakes have made the data-on-read schema popular. Things seem to change with the new open table file formats, like Delta Lake or Apache Iceberg. Why? Let's try to understand that by analyzing their schema evolution parts.
Introduction South Africa is not an exception as data science-driven economic change sweeps the world. The nation is seeing an increase in demand for qualified data science workers as a result of its booming IT sector and developing data-driven industries. Effective Graduate Training Programmes, Graduate Development Programmes, and Graduate Programs in data science must be […] The post Academia to Industry: Data Science Graduate Programs for South Africa’s Future appeared first on An
Anyone who’s been working in Data Land for any time at all, knows that the reality of life very rarely matches the glut of shiny snake oil we get sold on a daily basis. That’s just part of life. Every new tool, every single thingy-ma-bob we think is going to solve all our problems and […] The post Real Talk about Running Databricks + Delta Lake at Scale. appeared first on Confessions of a Data Guy.
Ruchir Jha , Brian Harrington , Yingwu Zhao TL;DR Streaming alert evaluation scales much better than the traditional approach of polling time-series databases. It allows us to overcome high dimensionality/cardinality limitations of the time-series database. It opens doors to support more exciting use-cases. Engineers want their alerting system to be realtime, reliable, and actionable.
Apache Airflow® 3.0, the most anticipated Airflow release yet, officially launched this April. As the de facto standard for data orchestration, Airflow is trusted by over 77,000 organizations to power everything from advanced analytics to production AI and MLOps. With the 3.0 release, the top-requested features from the community were delivered, including a revamped UI for easier navigation, stronger security, and greater flexibility to run tasks anywhere at any time.
Introduction Apache Kafka is an open-source publish-subscribe messaging application initially developed by LinkedIn in early 2011. It is a famous Scala-coded data processing tool that offers low latency, extensive throughput, and a unified platform to handle the data in real-time. It is a message broker application and a logging service that is distributed, segmented, and […] The post A Detailed Guide of Interview Questions on Apache Kafka appeared first on Analytics Vidhya.
With the widespread adoption of Rest.li since its inception in 2013, LinkedIn has built thousands of microservices to enable the exchange of data with our engineers and our external partners. Though this microservice architecture has worked out really well for our API engineers, when our clients need to fetch data they find themselves talking to several of these microservices.
Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage
There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.
The article shows effective coding procedures for fixing noisy labels in text data that improve the performance of any NLP model. The impact is proved by the comparison of the ML algorithm on starting and cleaning the dataset.
In the wake of ChatGPT and Generative AI DoorDash is identifying ways this new technology can enhance the customer’s ordering experience on the platform. The company is exploring the use of Generative AI, a subset of Artificial Intelligence that generates novel content based on existing data, and how it can be implemented effectively with consideration for the privacy and security of personal information.
Speaker: Andrew Skoog, Founder of MachinistX & President of Hexis Representatives
Manufacturing is evolving, and the right technology can empower—not replace—your workforce. Smart automation and AI-driven software are revolutionizing decision-making, optimizing processes, and improving efficiency. But how do you implement these tools with confidence and ensure they complement human expertise rather than override it? Join industry expert Andrew Skoog as he explores how manufacturers can leverage automation to enhance operations, streamline workflows, and make smarter, data-dri
Scrum Masters are important to the success of Scrum teams because they lead many of the activities that make sure the team works well together, improve consistency, and gives the client something of value. In this article, we will look at how a scrum master facilitates events such as daily scrum meetings, sprint planning, sprint review, and sprint retrospective meetings.
With Airflow being the open-source standard for workflow orchestration, knowing how to write Airflow DAGs has become an essential skill for every data engineer. This eBook provides a comprehensive overview of DAG writing features with plenty of example code. You’ll learn how to: Understand the building blocks DAGs, combine them in complex pipelines, and schedule your DAG to run exactly when you want it to Write DAGs that adapt to your data at runtime and set up alerts and notifications Scale you
Computing is all about transforming data. A wide variety of domains, such as multimedia, securities trading or compilers, allow decomposing the corresponding transformations into a sequence of well-defined steps. Moreover, these steps can be combined in different ways, perhaps omitting some or changing the order of others, producing different data processing pipelines tailored to a particular task at hand.
In this new webinar, Tamara Fingerlin, Developer Advocate, will walk you through many Airflow best practices and advanced features that can help you make your pipelines more manageable, adaptive, and robust. She'll focus on how to write best-in-class Airflow DAGs using the latest Airflow features like dynamic task mapping and data-driven scheduling!
A structure provides the required clarity to focus efforts, especially while starting a new project. A model plays the same role in the case of software, and agile modeling provides a way to optimize the modeling efforts through the development lifecycle. Modeling helps developers understand all the components and their interactions. In addition, it allows a chance to understand the system from multiple perspectives, including functional, performance, and security considerations, thus helping th
Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage
When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m
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