Engineering at Meta

JANUARY 22, 2025

In order to build high-quality data lineage, we developed different techniques to collect data flow signals across different technology stacks: static code analysis for different languages, runtime instrumentation, and input and output data matching, etc.

Data Warehouse 111

Data Warehouse SQL Programming Language Data 111

Data Engineering Weekly

FEBRUARY 2, 2025

I finally found a good critique that discusses its flaws, such as multi-hop architecture, inefficiencies, high costs, and difficulties maintaining data quality and reusability.

Data Engineering 58

Data Engineering Data Engineer Engineering Data Lake 58

Monte Carlo

OCTOBER 31, 2024

In addition, AI data engineers should be familiar with programming languages such as Python , Java, Scala, and more for data pipeline, data lineage, and AI model development.

Data Engineering 52

Data Engineering Data Engineer Engineering Unstructured Data 52

Data Engineering Podcast

JUNE 29, 2020

This was a great conversation about the complexities of working in a niche domain of data analysis and how to build a pipeline of high quality data from collection to analysis.

Data Collection 100

Data Collection Management High Quality Data Metadata 100

Monte Carlo

JANUARY 21, 2025

Data Governance & Ethics : Understand emerging data regulations and ethical frameworks that shape how organizations collect, store, and use data. Why Gartners Data & Analytics Summit Matters In a world where real-time insights and advanced analytics can make or break an enterprise, staying ahead of the curve is crucial.

Data Analytics 52

Data Analytics Pipeline-centric Food Data Lake 52

Cloudera

AUGUST 21, 2021

million customers worldwide, recognized how the immense volume of data they maintained could provide better insight into customers’ needs. Since leveraging Cloudera’s data platform, Rabobank has been able to improve its customers’ financial management. Rabobank , headquartered in the Netherlands with over 8.3

Banking 103

Banking Raw Data High Quality Data Cloud 103

Maxime Beauchemin

JANUARY 20, 2017

The fact that ETL tools evolved to expose graphical interfaces seems like a detour in the history of data processing, and would certainly make for an interesting blog post of its own. Sure, there’s a need to abstract the complexity of data processing, computation and storage.

Data Engineering 130

Data Engineering Data Engineer Engineering ETL Tools 130

Databand.ai

AUGUST 30, 2023

Data quality monitoring refers to the assessment, measurement, and management of an organization’s data in terms of accuracy, consistency, and reliability. It utilizes various techniques to identify and resolve data quality issues, ensuring that high-quality data is used for business processes and decision-making.

Data Cleanse 52

Data Cleanse Metadata High Quality Data Datasets 52

Data Science Blog: Data Engineering

AUGUST 22, 2024

Tools like BiG EVAL are leading data quality field for all technical systems in which data is transported and transformed. BiG EVAL utilizes plausibility and validation mechanisms to adopt proactive quality assurance and enable short release cycles in agile projects as well.

Data Preparation 52

Data Preparation Transportation High Quality Data Data Science 52

Precisely

MARCH 14, 2023

Read Quality data you can depend on – today, tomorrow, and beyond For many years Precisely customers have ensured the accuracy of data across their organizations by leveraging our leading data solutions including Trillium Quality, Spectrum Quality, and Data360 DQ+. What does all this mean for your business?

Data Integration 52

Data Integration High Quality Data BI Data 52

Precisely

NOVEMBER 29, 2023

Organizations should be careful not to automate business processes before considering which data sets those processes impact. Automation increases the potential to create a large volume of bad data very quickly. Digital transformation leverages data and new technologies to drive value through innovation and efficiency.

High Quality Data 64

High Quality Data Data Integration Process Building 64

Precisely

AUGUST 15, 2024

Sign up today for your free trial Sign up Making Your Data AI-Ready Using AI in data engineering workflows can automate processes including data acquisition, profiling, transformation, and cleansing – all with the goal of creating high-quality, accurate data that can be used to build and train effective AI models.

Government 64

Government Business Analyst High Quality Data Data 64

Wayne Yaddow

FEBRUARY 6, 2025

Orchestration & Dependencies : Involves the scheduling and coordination of multiple data processing steps, ensuring each stage completes successfully before the next begins. As new data sources, dependencies, and compliance requirements emerge, adapting mitigation techniques will prevent disruptions and maintain data integrity.

Data Pipeline 52

Data Pipeline Manufacturing High Quality Data Healthcare 52

Ascend.io

JULY 11, 2024

Leveraging details about data and how it is processed enhances several key aspects of data management: Ensuring Data Quality Metadata ensures data accuracy and consistency by maintaining information about data sources, updates, and validation rules.

Metadata 52

Metadata IT Government High Quality Data 52

DataKitchen

SEPTEMBER 21, 2023

L1 is usually the raw, unprocessed data ingested directly from various sources; L2 is an intermediate layer featuring data that has undergone some form of transformation or cleaning; and L3 contains highly processed, optimized, and typically ready for analytics and decision-making processes. What is Data in Use?

Raw Data 69

Raw Data Data Business Intelligence Data Engineering 69

Ascend.io

JUNE 10, 2024

See it for yourself: Check out a demo of Ascend’s new AI capabilities #2 - Expanded Data Engineering Capabilities Will Unlock Deeper Business Value With the demand for AI use cases climbing, the need to efficiently extract high quality data has introduced new opportunities and complexities.

Data Engineering 52

Data Engineering Data Engineer Engineering High Quality Data 52

Striim

JULY 10, 2024

The surge in package theft due to more online shopping overwhelmed traditional security measures and data management systems, which showcased significant operational vulnerabilities.

Management 52

Management Transportation Machine Learning High Quality Data 52

Databand.ai

JULY 17, 2023

By adopting a set of best practices inspired by Agile methodologies, DevOps principles, and statistical process control techniques, DataOps helps organizations deliver high-quality data insights more efficiently.

Data Pipeline 52

Data Pipeline Machine Learning High Quality Data Data Ingestion 52

Ripple Engineering

JANUARY 29, 2024

  A lack of a centralized system makes building a single source of high-quality data difficult. The key aspect of any business-centric team in delivering products and features is to make critical decisions on ensuring low latency, high throughput, cost-effective storage, and highly efficient infrastructure.

Database-centric 52

Database-centric Pipeline-centric NoSQL High Quality Data 52

RandomTrees

SEPTEMBER 10, 2024

AI enhances predictive maintenance in several ways: Data Analysis: In real-time modes, AI processes large volumes of information while detecting any patterns or anomalies that could indicate an impending failure ahead of traditional monitoring systems.

Transportation 59

Transportation Manufacturing Machine Learning Algorithm 59

Picnic Engineering

DECEMBER 12, 2023

The rich context provided by our Snowflake-powered Data Warehouse enhances their performance, allowing us to create a robust feature set for training. Training these models on our historical demand and assessing their performance is manageable as a one-time project since concepts like data drift are still not a big concern.

Machine Learning 52

Machine Learning Deep Learning Food Software Engineer 52

Workfall

JULY 4, 2023

DBT’s superpowers include seamlessly connecting with databases and data warehouses, performing amazing transformations, and effortlessly managing dependencies to ensure high-quality data. Each successful deployment enriches its data ecosystem, empowering decision-makers with valuable, up-to-date insights.

Data Warehouse 69

Data Warehouse SQL Database PostgreSQL 69

Monte Carlo

OCTOBER 10, 2024

As the use of AI becomes more ubiquitous across data organizations and beyond, data quality rises in importance right alongside it. After all, you can’t have high-quality AI models without high-quality data feeding them. That’s like trying to cook something using only spoiled ingredients.

Unstructured Data 52

Unstructured Data Google Cloud Machine Learning ETL Tools 52

Monte Carlo

FEBRUARY 20, 2024

Consideration What to Look For Integration Capabilities Support for a diverse array of data sources and destinations, ensuring compatibility with your data ecosystem. Batch vs. Streaming Assess if your data processing leans towards real-time analytics or if batch processing suffices for your use case.

Data Ingestion 52

Data Ingestion Google Cloud Kafka AWS 52

Monte Carlo

JULY 27, 2023

These specialists are also commonly referred to as data reliability engineers. To be successful in their role, data quality engineers will need to gather data quality requirements (mentioned in 65% of job postings) from relevant stakeholders.

Engineering 52

Engineering Healthcare Data Warehouse Scala 52

Edureka

FEBRUARY 7, 2023

An Azure Data Engineer is responsible for designing, implementing, and maintaining data management and data processing systems on the Microsoft Azure cloud platform. They work with large and complex data sets and are responsible for ensuring that data is stored, processed, and secured efficiently and effectively.

Data Engineering 52

Data Engineering Data Engineer Engineering Programming Language 52

DareData

JULY 25, 2024

And they need to learn from quality data. The same applies to machine learning — it needs high-quality data. How has your organization integrated AI and ML into its processes? For example, retail companies can operate without focusing on data, though being competitive is another matter.

Machine Learning 52

Machine Learning Data Science Algorithm High Quality Data 52

Knowledge Hut

JUNE 28, 2023

Business Intelligence: Business Intelligence can handle moderate to large volumes of structured data. While it may not be designed specifically for big data processing, it can integrate with data processing technologies to analyze substantial amounts of data.

Data Mining 52

Data Mining Business Intelligence BI Structured Data 52

Knowledge Hut

APRIL 25, 2024

Data-driven Orientation: Both big data and machine learning embrace a data-centric approach. They prioritize the utilization of data to acquire insights, generate predictions, and inform decision-making. Data Processing: Both big data and machine learning encompass the processing and examination of extensive datasets.

Machine Learning 52

Machine Learning Big Data Unstructured Data Data Mining 52

Ascend.io

FEBRUARY 28, 2024

While data engineering and Artificial Intelligence (AI) may seem like distinct fields at first glance, their symbiosis is undeniable. The foundation of any AI system is high-quality data. Here lies the critical role of data engineering: preparing and managing data to feed AI models.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

DataKitchen

JULY 27, 2023

Azure Databricks Delta Live Table s: These provide a more straightforward way to build and manage Data Pipelines for the latest, high-quality data in Delta Lake. Azure Machine Learning can then use this data to train, test, and deploy machine learning models. It does the job.

Data Pipeline 52

Data Pipeline BI Machine Learning Data Preparation 52

Monte Carlo

FEBRUARY 21, 2023

Reduced reliance on IT Integral to a data fabric is a set of pre-built models and algorithms that expedite data processing. You can also feel confident that users at your organization will more readily adopt your data fabric, because they’ll know they can trust the insights it generates.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Monte Carlo

FEBRUARY 21, 2023

Reduced reliance on IT Integral to a data fabric is a set of pre-built models and algorithms that expedite data processing. You can also feel confident that users at your organization will more readily adopt your data fabric, because they’ll know they can trust the insights it generates.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Knowledge Hut

APRIL 23, 2024

Gathering data at high velocities necessitates capturing and ingesting data streams as they occur, ensuring timely acquisition and availability for analysis. Utilizing is related to the data processing and analyzing speed for gleaning useful insights.

Big Data 52

Big Data Media Datasets Unstructured Data 52

Databand.ai

JULY 10, 2023

Databand allows data engineering and data science teams to define data quality rules, monitor data consistency, and identify data drift or anomalies. It also provides real-time notifications and alerts, enabling teams to proactively address issues and maintain high-quality data.

Data Pipeline 52

Data Pipeline Algorithm Data Engineering Data Engineer 52

Monte Carlo

JANUARY 31, 2023

The problem: over-reliance on manual testing and a lack of visibility across domains Checkout.com’s decentralized data structure and reliance on manual tests and monitors meant that data engineering was a single point of failure for data issues. And I hope that this trend will continue moving forward.”

Data 52

Data Data Engineering Data Engineer High Quality Data 52

Knowledge Hut

MARCH 5, 2024

Technology According to a Glassdoor report, data engineering average salary at large companies generally ranges from S$86,288 to S$171,980. Data engineers in the technology industry focus on data streaming and data processing pipelines. Size issues are another major data engineering issue for technology companies.

Data Engineering 52

Data Engineering Data Engineer Engineering Education 52