Waitingforcode

APRIL 24, 2024

As a data engineer you're certainly familiar with data skew. Turns out, stream processing also has its skew but more related to time. Yes, this bad phenomena where one task takes considerably more input than the others and often causes unexpected latency or failures.

Process 130

Process Data Engineering Data Engineer Engineering 130

Seattle Data Guy

SEPTEMBER 3, 2024

One of the holy grails that many data teams seem to chase is real-time data analytics. However, there often is a conflation between real-time data analytics and stream processing. appeared first on Seattle Data Guy. After all, if you can have real-time analytics, you can make better decisions faster.

Process 130

Process Data Analytics Data Big Data 130

Analytics Vidhya

FEBRUARY 28, 2023

Introduction Data science has taken over all economic sectors in recent times. To achieve maximum efficiency, every company strives to use various data at every stage of its operations.

Data Science 285

Data Science Data Preparation Big Data Data 285

Christophe Blefari

MARCH 15, 2024

Saying mainly that " Sora is a tool to extend creativity " Last point Mira has been mocked and criticised online because as a CTO she wasn't able to say on which public / licensed data Sora has been trained on. Pandera, a data validation library for dataframes, now supports Polars.

Metadata 272

Metadata Datasets Data Data Warehouse 272

Start Data Engineering

MAY 28, 2024

Building efficient data pipelines with DuckDB 4.1. Use DuckDB to process data, not for multiple users to access data 4.2. Cost calculation: DuckDB + Ephemeral VMs = dirt cheap data processing 4.3. Processing data less than 100GB? Introduction 2. Project demo 3. Use DuckDB 4.4.

Data Pipeline 219

Data Pipeline Python Building Data 219

Seattle Data Guy

NOVEMBER 13, 2024

Much of the data we have used for analysis in traditional enterprises has been structured data. However, much of the data that is being created and will be created comes in some form of unstructured format. However, the digital era… Read more The post What is Unstructured Data?

Unstructured Data 130

Unstructured Data Process Structured Data Data 130

Start Data Engineering

SEPTEMBER 18, 2024

Parts of data engineering 3.1. Identify what tool to use to process data 3.3. Data flow architecture 3. Introduction 2. Requirements 3.1.1. Understand input datasets available 3.1.2. Define what the output dataset will look like 3.1.3. Define SLAs so stakeholders know what to expect 3.1.4.

Project 240

Project Building Datasets Architecture 240

databricks

JULY 8, 2024

We are proud to announce two new analyst reports recognizing Databricks in the data engineering and data streaming space: IDC MarketScape: Worldwide Analytic.

Data Pipeline 122

Data Pipeline Process Cloud Data Engineering 122

Analytics Vidhya

FEBRUARY 7, 2023

Introduction Data engineering is the field of study that deals with the design, construction, deployment, and maintenance of data processing systems. The goal of this domain is to collect, store, and process data efficiently and efficiently so that it can be used to support business decisions and power data-driven applications.

Data Engineering 240

Data Engineering Data Engineer Engineering Data 240

KDnuggets

SEPTEMBER 24, 2024

Healthcare generates a vast amount of unstructured data, including clinical notes, patient messages, and research articles. This data contains valuable insights that can significantly improve patient care, but are difficult to include in traditional modeling techniques due to its unstructured format.

Unstructured Data 100

Unstructured Data Healthcare Process Data 100

Analytics Vidhya

FEBRUARY 28, 2024

Introduction Data is fuel for the IT industry and the Data Science Project in today’s online world. IT industries rely heavily on real-time insights derived from streaming data sources. Handling and processing the streaming data is the hardest work for Data Analysis.

MongoDB 217

MongoDB Data Pipeline Kafka Building 217

Analytics Vidhya

FEBRUARY 23, 2023

Introduction Big Data is a large and complex dataset generated by various sources and grows exponentially. It is so extensive and diverse that traditional data processing methods cannot handle it. The volume, velocity, and variety of Big Data can make it difficult to process and analyze.

Big Data Tools 234

Big Data Tools Big Data Datasets Data 234

Analytics Vidhya

FEBRUARY 6, 2023

Introduction The demand for data to feed machine learning models, data science research, and time-sensitive insights is higher than ever thus, processing the data becomes complex. To make these processes efficient, data pipelines are necessary. appeared first on Analytics Vidhya.

Amazon Web Services 218

Amazon Web Services Data Pipeline Machine Learning Data Science 218

Analytics Vidhya

AUGUST 7, 2024

Introduction Apache Airflow is a crucial component in data orchestration and is known for its capability to handle intricate workflows and automate data pipelines. Many organizations have chosen it due to its flexibility and strong scheduling capabilities.

Data Pipeline 187

Data Pipeline Data Process Data Workflow 187

Confessions of a Data Guy

OCTOBER 31, 2024

I am a glutton for punishment, a harbinger of tidings, a storm crow, a prophet of the data land, my sole purpose is to plumb the depths of the tools we use every day in Data Engineering. appeared first on Confessions of a Data Guy.

Process 113

Process Data Engineering Data Engineer Engineering 113

Analytics Vidhya

FEBRUARY 19, 2023

Introduction Data pipelines play a critical role in the processing and management of data in modern organizations. A well-designed data pipeline can help organizations extract valuable insights from their data, automate tedious manual processes, and ensure the accuracy of data processing.

Data Pipeline 197

Data Pipeline Data Designing Data Process 197

Data Engineering Podcast

SEPTEMBER 10, 2023

Summary Data systems are inherently complex and often require integration of multiple technologies. This offers a single location for managing visibility and error handling so that data platform engineers can manage complexity. With Materialize, you can!

BI 208

BI SQL Machine Learning Data 208

Data Engineering Podcast

FEBRUARY 4, 2024

Summary Stream processing systems have long been built with a code-first design, adding SQL as a layer on top of the existing framework. RisingWave is a database engine that was created specifically for stream processing, with S3 as the storage layer. Want to see Starburst in action?

SQL 173

SQL Data Lake High Quality Data Data Pipeline 173

databricks

AUGUST 30, 2024

Learn how companies can create repeatable and scalable workflows that enable users to quickly turn GenAI innovation from experimentation to reality.

Process 105

Process Building Data 105

Analytics Vidhya

FEBRUARY 4, 2023

Introduction This article will explain the difference between ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) when data transformation occurs. In ETL, data is extracted from multiple locations to meet the requirements of the target data file and then placed into the file.

Data 194

Data Process Cloud Computing Data Analysis 194

Start Data Engineering

MAY 30, 2024

Introduction Data is stored on disk and processed in memory Running the code Run on Codespaces Run on your laptop Using python REPL Python basics Python is used for extracting data from sources, transforming it, & loading it into a destination [Extract & Load] Read and write data to any system [Transform] Process data in Python or instruct (..)

Python 147

Python Data Engineering Data Engineer Engineering 147

Analytics Vidhya

FEBRUARY 6, 2023

Introduction HDFS (Hadoop Distributed File System) is not a traditional database but a distributed file system designed to store and process big data. It is a core component of the Apache Hadoop ecosystem and allows for storing and processing large datasets across multiple commodity servers.

Data Storage 185

Data Storage Big Data Hadoop Datasets 185

Data Engineering Podcast

SEPTEMBER 17, 2023

Summary A significant amount of time in data engineering is dedicated to building connections and semantic meaning around pieces of information. Linked data technologies provide a means of tightly coupling metadata with raw information. Go to dataengineeringpodcast.com/materialize today to get 2 weeks free!

Building 189

Building SQL BI Python 189

Confessions of a Data Guy

SEPTEMBER 9, 2023

In the vast world of data, it’s not just about gathering and analyzing information anymore; it’s also about ensuring that data pipelines, processes, and platforms run seamlessly and efficiently.

Data Engineering 162

Data Engineering Data Engineer Engineering Data Pipeline 162

Data Engineering Podcast

FEBRUARY 11, 2024

Summary Sharing data is a simple concept, but complicated to implement well. There are also numerous technical considerations to be made, particularly if the producer and consumer of the data aren't using the same platforms. Dagster offers a new approach to building and running data platforms and data pipelines.

Data Lake 147

Data Lake High Quality Data Government Data Pipeline 147

Analytics Vidhya

FEBRUARY 28, 2023

A collaborative and interactive workspace allows users to perform big data processing and machine learning tasks easily. Introduction Azure Databricks is a fast, easy, and collaborative Apache Spark-based analytics platform that is built on top of the Microsoft Azure cloud.

Big Data 310

Big Data Machine Learning Cloud Data Process 310

Data Engineering Podcast

MAY 12, 2024

Summary Building a data platform is a substrantial engineering endeavor. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management This episode is supported by Code Comments, an original podcast from Red Hat. Data lakes are notoriously complex.

Management 147

Management Data Lake High Quality Data Machine Learning 147

Jesse Anderson

AUGUST 28, 2024

In the spring of 2024, I ran a new survey to gather more data for my Data Teams book and update my 2023 and 2020 surveys. This survey was designed to get information about how management uses data teams, the value they’re creating, and how they’re creating it. We start by asking some questions about each respondent’s data team.

Data 147

Data Consulting Big Data Data Engineering 147

Data Engineering Podcast

MARCH 17, 2024

Summary A significant portion of data workflows involve storing and processing information in database engines. Validating that the information is stored and processed correctly can be complex and time-consuming, especially when the source and destination speak different dialects of SQL. Data lakes are notoriously complex.

Database 147

Database Data Lake High Quality Data Data Workflow 147

Christophe Blefari

SEPTEMBER 28, 2023

Make your data stack take-off ( credits ) Hello, another edition of Data News. This week, we're going to take a step back and look at the current state of data platforms. What are the current trends and why are people fighting around the concept of the modern data stack. Is the modern data stack dying?

Big Data 147

Big Data Cloud Storage Hadoop SQL 147