Monte Carlo

FEBRUARY 20, 2024

At the heart of every data-driven decision is a deceptively simple question: How do you get the right data to the right place at the right time? The growing field of data ingestion tools offers a range of answers, each with implications to ponder. Times have changed and there are better ways of doing things now.

Data Ingestion 52

Data Ingestion Google Cloud Kafka AWS 52

Data Engineering Podcast

MARCH 25, 2023

Summary The promise of streaming data is that it allows you to react to new information as it happens, rather than introducing latency by batching records together. As your business adapts, so should your data. RudderStack Transformations lets you customize your event data in real-time with your own JavaScript or Python code.

MySQL 130

MySQL Python Architecture Machine Learning 130

Data Engineering Podcast

DECEMBER 25, 2022

Summary Encryption and security are critical elements in data analytics and machine learning applications. We have well developed protocols and practices around data that is at rest and in motion, but security around data in use is still severely lacking.

Machine Learning 130

Machine Learning Systems Data Lake Data Warehouse 130

Knowledge Hut

APRIL 23, 2024

In today's data-driven world, the volume and variety of information are growing unprecedentedly. As organizations strive to gain valuable insights and make informed decisions, two contrasting approaches to data analysis have emerged, Big Data vs Small Data.

Big Data 52

Big Data Datasets Data Analysis Media 52

Snowflake

MARCH 2, 2023

Snowflake enables organizations to be data-driven by offering an expansive set of features for creating performant, scalable, and reliable data pipelines that feed dashboards, machine learning models, and applications. But before data can be transformed and served or shared, it must be ingested from source systems.

Kafka 117

Kafka Data Ingestion Data Pipeline Cloud Storage 117

DoorDash Engineering

JANUARY 30, 2024

However, Cassandra also is notorious for being hard to tune for performance and for the pitfalls that can arise during that process. I will share what we learned as we made our fleet much more performant and cost-effective. It excels in both horizontal and vertical scaling, allowing it to manage large volumes of data effortlessly.

NoSQL 83

NoSQL Database Systems Relational Database 83

DoorDash Engineering

FEBRUARY 22, 2023

Note: A few months back, our peers at the DashMart engineering team released an article elaborating on how they used CockroachDB changefeed to support real-time inventory changes. To support these operations we built an inventory platform to process these items in a reliable, scalable, and fault-tolerant way.

Designing 124

Designing Database Architecture SQL 124

Christophe Blefari

SEPTEMBER 1, 2023

I've taken an unplanned 3-week break since the last Data News, let's be honest, it was necessary! I spent a few hours working on the fancy data stack project and articles are in the works, but it was idealistic to produce quality code and content while enjoying the summer. Like wine, it takes time to get it right.

Food 130

Food Data SQL Python 130

Data Engineering Podcast

DECEMBER 4, 2022

Summary The term "real-time data" brings with it a combination of excitement, uncertainty, and skepticism. In this episode Arjun Narayan explains how the technical barriers to adopting real-time data in your analytics and applications have become surmountable by organizations of all sizes.

Data Lake 100

Data Lake MongoDB MySQL Data Warehouse 100

Data Engineering Podcast

JANUARY 15, 2023

Summary The modern data stack has made it more economical to use enterprise grade technologies to power analytics at organizations of every scale. At the Modern Data Company they created the DataOS platform as a means of driving your full analytics lifecycle through code, while providing automatic knowledge graphs and data discovery.

Coding 130

Coding Building PostgreSQL Data Lake 130

Data Engineering Weekly

JANUARY 28, 2024

RudderStack is the Warehouse Native CDP, built to help data teams deliver value across the entire data activation lifecycle, from collection to unification and activation. Visit rudderstack.com to learn more. I had a chance to meet some of the amazing humans of data engineering.

Data Engineering 57

Data Engineering Data Engineer Engineering Recruitment 57

Scott Logic

NOVEMBER 6, 2023

In this post we’ll take a whistle-stop tour around the topic of data, going from sources and types through to use cases and the technologies involved in processing data. Introduction Over the last decade we’ve heard more and more about data.

Data Lake 52

Data Lake Kafka BI Unstructured Data 52

Snowflake

JANUARY 23, 2024

Many developers and enterprises looking to use machine learning (ML) to generate insights from data get bogged down by operational complexity. Benefits of Snowpark ML Modeling: Feature engineering and preprocessing: Improve performance and scalability with distributed execution for common scikit-learn preprocessing functions.

Machine Learning 113

Machine Learning Metadata Python Telecommunication 113

Knowledge Hut

SEPTEMBER 26, 2023

Organisations are constantly looking for robust and effective platforms to manage and derive value from their data in the constantly changing landscape of data analytics and processing. These platforms provide strong capabilities for data processing, storage, and analytics, enabling companies to fully use their data assets.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Knowledge Hut

JULY 3, 2023

In today's fast-paced and data-driven world, users increasingly depend on real-time intuition to get an aggressive side and define a plan of action. Conventional batch processing techniques seem incomplete in fulfilling the demand of driving the commercial environment. This refers to Real-time data ingestion.

Data Ingestion 52

Data Ingestion Pipeline-centric Google Cloud Media 52

Data Engineering Podcast

AUGUST 3, 2021

Summary Data lake architectures have largely been biased toward batch processing workflows due to the volume of data that they are designed for. With more real-time requirements and the increasing use of streaming data there has been a struggle to merge fast, incremental updates with large, historical analysis.

Data Lake 130

Data Lake Data Warehouse Hadoop Architecture 130

AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. What is a data lake?

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Monte Carlo

MARCH 14, 2023

Data ingestion is the process of collecting data from various sources and moving it to your data warehouse or lake for processing and analysis. It is the first step in modern data management workflows. Table of Contents What is Data Ingestion? Decision making would be slower and less accurate.

Data Ingestion 52

Data Ingestion Data Warehouse Lambda Architecture Raw Data 52

Data Engineering Weekly

JULY 30, 2023

Data Engineering Weekly Is Brought to You by RudderStack RudderStack Profiles takes the SaaS guesswork and SQL grunt work out of building complete customer profiles, so you can quickly ship actionable, enriched data to every downstream team. We handle Petabytes of data!!! All our data is in S3!!! See how it works today.

Data Engineering 52

Data Engineering Data Engineer Engineering Kafka 52

LinkedIn Engineering

AUGUST 23, 2023

Co-authors: Jason (Siyu) Zhu , Amol Ghoting , Birjodh Tiwanna , Maneesh Varshney Introduction At LinkedIn, we strive to provide our members with valuable content that can help them build professional networks, learn new skills, and discover exciting job opportunities.

Architecture 82

Architecture Deep Learning Datasets Machine Learning 82

Cloudera

JUNE 26, 2023

Over time, using the wrong tool for the job can wreak havoc on environmental health. Here are some tips and tricks of the trade to prevent well-intended yet inappropriate data engineering and data science activities from cluttering or crashing the cluster. Over time, those practices lead to cluster and Impala instability.

ETL Tools 75

ETL Tools Programming Language Datasets Data Pipeline 75

Knowledge Hut

JUNE 23, 2023

Real-time data analytics is an essential innovation that enables companies to act quickly on data. By this year, more than half of business systems would base choices on current context data. This demonstrates the rising significance of real-time analytics architecture in the hectic corporate climate of today.

Data Analytics 52

Data Analytics IT Transportation Analytics Architecture 52

Knowledge Hut

APRIL 19, 2023

In today's data-driven world, businesses need to extract, transform, and load data from multiple data sources because of the large amount of data which businesses generate. An ETL pipeline is one of the most common solutions for the efficient processing of large data. What is ETL?

Data Warehouse 52

Data Warehouse Business Intelligence ETL Tools Data Pipeline 52

Maxime Beauchemin

APRIL 26, 2023

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 ??? To support engineers in this process, I am introducing Promptimize , a Python toolkit designed to measure success and outcomes while doing prompt engineering. What a stellar assistant!

SQL 148

SQL Database Engineering Software Engineer 148

ProjectPro

DECEMBER 28, 2021

The digital economy is driven by data disrupting industries across the globe with increasing number of companies wanting to glean valuable insights from real-time data. Allied Market Research estimated the global big data and business analytics market to be valued at $198.08 billion by 2030. billion by 2030.

Architecture 52

Architecture Kafka Java Scala 52

Knowledge Hut

JANUARY 3, 2024

Imagine that I/O is a part of the process that is currently running (which, by definition, does not need the CPU to be accomplished). The OS might then terminate that process and hand off the command to another ready-to-run in-memory programme (i.e., This keeps the system from idly waiting for the I/O work to finish, wasting CPU time.

Systems 98

Systems Utilities Programming Language Programming 98

Lyft Engineering

MARCH 12, 2024

Summary At Lyft we have built a platform for developing, training and serving Reinforcement Learning models for typical internet industry applications with a focus on Contextual Bandits. Those models have been critical for decision making problems that other techniques such as supervised learning or optimization models struggled with.

Algorithm 66

Algorithm Machine Learning Datasets Food 66

Data Engineering Weekly

FEBRUARY 5, 2023

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. The blog is an excellent overview of problems with floating points and integer data types.

Data Engineering 57

Data Engineering Data Engineer Engineering Food 57

Striim

OCTOBER 4, 2022

Traditionally, historical data (or batch data) was used for decision-making. However, lately, there’s a lot of focus on real-time data, which provides more business value. What is real-time data? There’s minimal delay in the collection, processing, and analysis of data by the business.

Media 52

Media Data Data Architecture Data Warehouse 52

Data Engineering Weekly

MARCH 26, 2023

Contribute to the Rudderstack Transformations Library, Win $1000 RudderStack Transformations lets you customize event data in real time with your own JavaScript or Python code. Last year around this time, Bundling vs. Unbundling was the talk of the town. Here are the top 5 key learnings from the report.

Data Engineering 52

Data Engineering Data Engineer Engineering Lambda Architecture 52

ProjectPro

FEBRUARY 21, 2023

With around 35k stars and over 26k forks on Github, Apache Spark is one of the most popular big data frameworks used by 22,760 companies worldwide. Apache Spark is the most efficient, scalable, and widely used in-memory data computation tool capable of performing batch-mode, real-time, and analytics operations.

Scala 52

Scala Programming Language Java Hadoop 52

Data Engineering Weekly

JANUARY 29, 2023

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. link] Sponsored: Upsolver - Write a SQL Query, Get a Data-in-Motion Pipeline!

Data Engineering 52

Data Engineering Data Engineer Engineering Deep Learning 52

Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows. As a result, they can be slow, inefficient, and prone to errors.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Snowflake

MARCH 30, 2023

A 2016 data science report from data enrichment platform CrowdFlower found that data scientists spend around 80% of their time in data preparation (collecting, cleaning, and organizing of data) before they can even begin to build machine learning (ML) models to deliver business value.

Engineering 77

Engineering Raw Data Data Science Scala 77

Rockset

AUGUST 25, 2021

The world is moving from batch to real-time. With Confluent’s recent IPO, streaming data has officially gone mainstream, “becoming the underpinning of a modern digital customer experience, and the key to driving intelligent, efficient operations” to quote from their letter to shareholders.

Aggregated Data 52

Aggregated Data Data Lake Hadoop SQL 52

Towards Data Science

DECEMBER 1, 2023

Why static workload is insufficient and what I learned by comparing HNSWLIB and DiskANN using streaming workload Image by DALLE-3 Vector databases are built for high-dimensional vector retrieval. Indexing throughput measures how fast the ANN index can accept new data points. Data distribution shifts over time.

Database 52

Database Algorithm Datasets Kafka 52

ProjectPro

SEPTEMBER 9, 2021

Apache Hive and Apache Spark are the two popular Big Data tools available for complex data processing. To effectively utilize the Big Data tools, it is essential to understand the features and capabilities of the tools. Hive is built on top of Hadoop and provides the measures to read, write, and manage the data.

Hadoop 52

Hadoop Big Data Tools Java SQL 52