Start Data Engineering

FEBRUARY 22, 2022

1. Introduction 2. CI 3. Sample project: Data testing with Github Actions 3.1. Prerequisites 3.2. Project overview 3.3. Automating data tests with Github Actions 4. Conclusion 5. Further reading 1. Introduction Automated testing is crucial for ensuring that your code is bug-free and avoiding regressions. If you are wondering How can data tests be integrated into a CI (Continuous Integration) pipeline?

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Data Coding Project Systems 130

Marc Lamberti

FEBRUARY 21, 2022

Airflow dynamic DAGs can save you a ton of time. As you know, Apache Airflow is written in Python, and DAGs are created via Python scripts. That makes it very flexible and powerful (even complex sometimes). By leveraging Python, you can create DAGs dynamically based on variables, connections, a typical pattern, etc. This very nice way of generating DAGs comes at the price of higher complexity and subtle tricky things that you must know.

Python 130

Python Metadata Coding Process 130

KDnuggets

FEBRUARY 21, 2022

A collection of cheat sheets that will help you prepare for a technical interview on Data Structures & Algorithms, Machine learning, Deep Learning, Natural Language Processing, Data Engineering, Web Frameworks.

Data Science 154

Data Science Deep Learning Algorithm Machine Learning 154

Confluent

FEBRUARY 24, 2022

A few years ago I helped build an event-driven system for gym bookings. The pitch was that we were building a better experience for both the gym members booking different […].

Systems 124

Systems Building Data 124

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Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

Business Intelligence

Data Engineering Podcast

FEBRUARY 20, 2022

Summary The life sciences as an industry has seen incredible growth in scale and sophistication, along with the advances in data technology that make it possible to analyze massive amounts of genomic information. In this episode Guy Yachdav, director of software engineering for ImmunAI, shares the complexities that are inherent to managing data workflows for bioinformatics.

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Systems Software Engineer Software Engineering Data Warehouse 100

Cloudera

FEBRUARY 22, 2022

Over the past decade, the successful deployment of large scale data platforms at our customers has acted as a big data flywheel driving demand to bring in even more data, apply more sophisticated analytics, and on-board many new data practitioners from business analysts to data scientists. This unprecedented level of big data workloads hasn’t come without its fair share of challenges.

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Metadata Datasets BI SQL 109

ProjectPro

FEBRUARY 25, 2022

What is a Machine Learning Pipeline? A machine learning pipeline helps automate machine learning workflows by processing and integrating data sets into a model, which can then be evaluated and delivered. A well-built pipeline helps in the flexibility of the model implementation. A pipeline in machine learning is a technical infrastructure that allows an organization to organize and automate machine learning operations.

Machine Learning 52

Machine Learning Building Amazon Web Services AWS 52

Data Engineering Podcast

FEBRUARY 20, 2022

Summary Python has grown to be one of the top languages used for all aspects of data, from collection and cleaning, to analysis and machine learning. Along with that growth has come an explosion of tools and engines that help power these workflows, which introduces a great deal of complexity when scaling from single machines and exploratory development to massively parallel distributed computation.

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Python Data Process IT Building 100

Cloudera

FEBRUARY 23, 2022

The telecommunications industry has been doing well since the pandemic started (not that many would notice). Revenues have remained relatively stable, while consumption has gone up, as virtual engagement has become the primary mode of operations for many businesses (and families!) In the mean-time, digital transformation has been accelerating both as a means to respond to the pandemic, and as a mechanism to drive costs down further, allowing for margin growth.

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Telecommunication Cloud Media Government 94

KDnuggets

FEBRUARY 22, 2022

Machine Learning as a technology, ensures that our current gadgets and their software get smarter by the day. Here are the algorithms that you ought to know about to understand Machine Learning’s varied and extensive functionalities and their effectiveness.

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Machine Learning Algorithm Technology 144

Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

Data

ProjectPro

FEBRUARY 25, 2022

When the world was under lockdown and movement was restricted to an absolute emergency- millions were introduced to the world of online shopping. The convenience of online shopping helped e-commerce platforms record historic sales. While that happened, it is no surprise that the rate of online financial fraud also increased incredibly. Online fraud cases using credit and debit cards saw a historic upsurge of 225 percent during the COVID-19 pandemic in 2020 as compared to 2019.

Machine Learning 52

Machine Learning Project Algorithm Datasets 52

Hepta Analytics

FEBRUARY 24, 2022

Week 3 was about data warehousing, working on the data that was ingested in the week 2. We will take the already ingested data and create an external table from it and optimize the performance of queries through partitioning and clustering. Then automate the whole process using airflow. There are two systems types when dealing with data: Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP).

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Data Warehouse Data Engineering Data Engineer Engineering 52

Cloudera

FEBRUARY 24, 2022

In the latest installment of the EMEA Influential Women in Data webinar series, we welcomed Shirley Collie, Chief Health Analytics Actuary at Discovery Health to discuss everything from how the pandemic has impacted working, to the opportunities within data, and the importance of intentionality. A data-driven organization. Shirley knows better than most about the impact that COVID 19 has had on the world.

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Healthcare Algorithm IT Management 85

KDnuggets

FEBRUARY 25, 2022

Learn data analytics by taking the best YouTube courses. These courses will cover data analysis with Python, R, SQL, PowerBI, Tableau, Excel, and SPSS.

Data Analytics 151

Data Analytics Data Analysis SQL Python 151

Speaker: Nikhil Joshi, Founder & President of Snic Solutions

Is your manufacturing operation reaching its efficiency potential? A Manufacturing Execution System (MES) could be the game-changer, helping you reduce waste, cut costs, and lower your carbon footprint. Join Nikhil Joshi, Founder & President of Snic Solutions, in this value-packed webinar as he breaks down how MES can drive operational excellence and sustainability.

Manufacturing

ProjectPro

FEBRUARY 25, 2022

Read this article to find the right resources for learning MLOps. The blog starts with an introduction to MLOps, skills required to become an MLOps engineer, and then lays out an MLOps learning path for beginners. MLOps is an acronym that represents the combination of Machine-Learning(ML) and Operations. It is a beautiful technique for implementing data science projects that allow businesses to increase their projects’ efficiency minimize the risk of introducing machine learning, artificia

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Deep Learning Algorithm Machine Learning Data Science 52

Rockset

FEBRUARY 24, 2022

Event-based architectures have been gaining popularity for some time. With increased adoption has come a flood of options for aggregating and analyzing events. Which databases are optimized for ingesting streaming events and analyzing them in real time? The answer is complex, nuanced and heavily dependent on the precise problem being solved. This post is intended to help anyone seeking to make a selection from a difficult to understand landscape.

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Confluent

FEBRUARY 23, 2022

In many ways, Storyblocks’ technical journey has mirrored that of most other startups and disruptors: Start small and as simple as possible (i.e., with a PHP monolith) Watch the company […].

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Cloud 52

KDnuggets

FEBRUARY 25, 2022

This blog post aims to describe the vanishing gradient problem and explain how use of the sigmoid function resulted in it.

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IT Machine Learning 158

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

Systems

ProjectPro

FEBRUARY 24, 2022

Working with audio data has been a relatively less widespread and explored problem in machine learning. In most cases, benchmarks for the latest seminal work in deep learning are measured on text and image data performances. Moreover, the most significant advances in deep learning are found in models that work with text and images. Amidst this, speech and audio, an equally important type of data, often gets overlooked.

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Deep Learning Project Datasets Machine Learning 52

Pipeline Data Engineering

FEBRUARY 22, 2022

Data engineering salon. News and interesting reads about the world of data. We’ve only scratched the surface of the full potential for the data warehouse Mikkel Dengsøe, Head of Data Science, Operations & Financial Crime, Monzo Bank Why I think the data warehouse will become the control centre for modern companies Git, SQL, CLI Vicki Boykis, Machine Learning Engineer, Automattic I’ve narrowed it down to three basic tools.

Data Warehouse 52

Data Warehouse Banking Metadata Data Science 52

AltexSoft

FEBRUARY 21, 2022

There has been a lot of buzz around data science, machine learning (ML), and artificial intelligence (AI) lately. As you may already know, to train a machine learning model, you need data. Lots of data, to be more precise. Lots of quality data, to be even more precise. To save you time, watch our 14-minute video on how data is prepared for machine learning.

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Machine Learning Algorithm Healthcare Medical 52

KDnuggets

FEBRUARY 23, 2022

This article outlines some of the most common design patterns encountered when creating successful Machine Learning solutions.

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Speaker: Donna Laquidara-Carr, PhD, LEED AP, Industry Insights Research Director at Dodge Construction Network

In today’s construction market, owners, construction managers, and contractors must navigate increasing challenges, from cost management to project delays. Fortunately, digital tools now offer valuable insights to help mitigate these risks. However, the sheer volume of tools and the complexity of leveraging their data effectively can be daunting. That’s where data-driven construction comes in.

Project

ProjectPro

FEBRUARY 22, 2022

This article will teach you exciting SQL project ideas to develop data analysis skills. You will explore challenging problems that you can quickly solve with this simple query language. It doesn’t matter if you are a beginner or a professional at using SQL; our list of SQL database projects has one for you. Data, data, everywhere! Where’s the way to manage it?

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Data Analysis SQL Project Banking 52

U-Next

FEBRUARY 21, 2022

Artificial Intelligence (AI) is not just making our lives convenient. It is empowering us with information and insights that have the potential to change the world for the better. With its application across diverse industries, market segments and real-world concerns, the role of AI is becoming increasingly inevitable by the day. This is to the extent that we see AI as a savior to some of the most plaguing concerns of humankind.

IT 52

IT Education Machine Learning 52

Preset

FEBRUARY 21, 2022

CrateDB is a distributed SQL database that excels at IoT and Time Series data workflows. In this post, we'll showcase how CrateDB and Superset can be used together.

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Data Workflow SQL Database Data 52

KDnuggets

FEBRUARY 24, 2022

Machine Learning with PyTorch and Scikit-learn is the PyTorch book from the widely acclaimed and bestselling Python Machine Learning series, fully updated and expanded to cover PyTorch, transformers, graph neural networks, and best practices.

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Machine Learning Python 120

Speaker: Evelyn Chou

Choosing the right business intelligence (BI) platform can feel like navigating a maze of features, promises, and technical jargon. With so many options available, how can you ensure you’re making the right decision for your organization’s unique needs? 🤔 This webinar brings together expert insights to break down the complexities of BI solution vetting.

Business Intelligence

ProjectPro

FEBRUARY 21, 2022

Learn PySpark Joins in a single go! From the various type of PySpark joins to their syntax and PySpark join example, this blog has it all for you. Without much ado, let’s dive right into the concepts. Table of Contents Why are PySpark Joins Important for Data Analytics? PySpark Joins- Types of Joins with Examples General Syntax for PySpark Join- PySpark Inner Join PySpark Left Join / PySpark Left Outer Join PySpark Right Join/ PySpark Right Outer Join PySpark Full Outer Join PySpark Left S

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Data Analysis Finance Datasets Big Data 52

U-Next

FEBRUARY 21, 2022

Cryptocurrencies are game-changing. NFTs are revolutionary. Blockchain is super airtight. Agreed. However, amidst all the news on people becoming millionaires through NFTs and cryptocurrencies rewriting conventions, there are also news that are quite alarming – crypto scams. Yes, with the world gradually adapting blockchain applications and concepts and several countries revisiting their policies on cryptocurrencies, this comes at the wrong time.

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Media 52

Preset

FEBRUARY 23, 2022

This article walks you through a potential approach to monitor your Superset usage directly within Superset leveraging the internal metadata database.

Metadata 52

Metadata Database 52

KDnuggets

FEBRUARY 21, 2022

According to a Stack Overflow survey, 13.2% of the data scientists are looking for a new job, as they are not satisfied in their current role. So why is this happening? What are the challenges Data Scientists are facing?

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Data 112

Speaker: Aindra Misra, Senior Manager, Product Management (Data, ML, and Cloud Infrastructure) at BILL

Join us for an insightful webinar that explores the critical intersection of data privacy and AI governance. In today’s rapidly evolving tech landscape, building robust governance frameworks is essential to fostering innovation while staying compliant with regulations. Our expert speaker, Aindra Misra, will guide you through best practices for ensuring data protection while leveraging AI capabilities.

Government