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Data Workflow Related Topics 
Uber Engineering
FEBRUARY 28, 2019
At Uber’s scale, thousands of microservices serve millions of rides and deliveries a day, generating more than a hundred petabytes of raw data. Internally, engineering and data teams across the company leverage this data to improve the Uber experience.
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Uber Engineering
JANUARY 16, 2023
Our Data Workflow Platform team introduces WorkflowGuard: a new service to govern executions, prioritize resources, and manage life cycle for repetitive data jobs. Check out how it improved workflow reliability and cost efficiency while bringing more observability to users.
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Driving Responsible Innovation: How to Navigate AI Governance & Data Privacy
The Ultimate Guide To Data-Driven Construction: Optimize Projects, Reduce Risks, & Boost Innovation
Building Your BI Strategy: How to Choose a Solution That Scales and Delivers
Improving the Accuracy of Generative AI Systems: A Structured Approach
KDnuggets
SEPTEMBER 9, 2024
Exploring the not-so-famous data science libraries that can be useful in your data workflow.
131 Driving Responsible Innovation: How to Navigate AI Governance & Data Privacy
The Ultimate Guide To Data-Driven Construction: Optimize Projects, Reduce Risks, & Boost Innovation
Building Your BI Strategy: How to Choose a Solution That Scales and Delivers
Improving the Accuracy of Generative AI Systems: A Structured Approach
KDnuggets
APRIL 16, 2024
Bring the latest AI implementation to Pandas to improve your data workflow.
141 
KDnuggets
NOVEMBER 30, 2023
Data engineers must prepare and manage the infrastructure and tools necessary for the whole data workflow in a data-driven company.
111 
KDnuggets
JUNE 17, 2024
Exploring the available text Python packages for your data workflow.
107 
Ascend.io
SEPTEMBER 6, 2024
AI-driven data quality workflows deploy machine learning to automate data cleansing, detect anomalies, and validate data. Integrating AI into data workflows ensures reliable data and enables smarter business decisions. Data quality is the backbone of successful data engineering projects.
52 
Monte Carlo
AUGUST 28, 2024
That’s why we’re thrilled to announce our new integration with Select Star , a leading data discovery platform, to continue delivering Monte Carlo’s comprehensive quality insights when and where teams need them. Increase visibility into data workflows with data observability Data observability is crucial for building trusted data and AI.
Hevo
SEPTEMBER 1, 2024
Managing and orchestrating data workflows efficiently is crucial in today’s data-driven world. As the amount of data constantly increases with each passing day, so does the complexity of the pipelines handling such data processes.
KDnuggets
DECEMBER 6, 2023
This week on KDnuggets: Discover GitHub repositories from machine learning courses, bootcamps, books, tools, interview questions, cheat sheets, MLOps platforms, and more to master ML and secure your dream job • Data engineers must prepare and manage the infrastructure and tools necessary for the whole data workflow in a data-driven company • And much, (..)
Ascend.io
JULY 3, 2024
This methodology emphasizes automation, collaboration, and continuous improvement, ensuring faster, more reliable data workflows. With data workflows growing in scale and complexity, data teams often struggle to keep up with the increasing volume, variety, and velocity of data. Let’s dive in!
Cloudera
JUNE 24, 2024
The Evolution of AI-Powered Assistance At Cloudera, we understand the challenges faced by data practitioners. The complexities of modern data workflows often translate into countless hours spent coding, debugging, and optimizing models. Get Started Today Are you ready to unlock the full potential of your data workflows?
Hevo
AUGUST 22, 2024
In the world of data engineering, the choice of tools can significantly impact the efficiency and scalability of your data workflows. Both tools serve distinct purposes but often get compared due to their roles in managing data pipelines. Two popular options are Airbyte and Apache Airflow.
Hevo
AUGUST 21, 2024
In today’s data-driven world, businesses rely heavily on data integration tools to streamline their data workflows. These tools are crucial in extracting, transforming, and loading (ETL) data from various sources into a unified system.
Hevo
AUGUST 16, 2024
In the world of data management, ETL (Extract, Transform, Load) tools play a crucial role in ensuring data is efficiently integrated, transformed, and loaded into data warehouses. The right ETL tools can significantly streamline […]
52 
Hevo
AUGUST 16, 2024
This blog explores the world of open source data orchestration tools, highlighting their importance in managing and automating complex data workflows. From Apache Airflow to Google Cloud Composer, we’ll walk you through ten powerful tools to streamline your data processes, enhance efficiency, and scale your growing needs.
52 
Hevo
AUGUST 4, 2024
With the increase in data size and the diversity of data sources and destinations, companies and data teams are always on the lookout for tools that can simplify creating and managing data workflows.
The Pragmatic Engineer
NOVEMBER 16, 2022
7 November Domino Data Lab (data workflow platform, Series E). In Mexico, the company had a large initiative with private drivers and a fleet of Tesla cars. That operation is in talks of selling to other investors. Meta - 13% layoffs. Widely-reported, e.g. here. 25% of their workforce laid off. Verified.
130 
Towards Data Science
AUGUST 22, 2023
Optimising big data workflows orchestration Continue reading on Towards Data Science »
84 
KDnuggets
JANUARY 4, 2023
These Python packages would improve your data workflow.
117 
Data Engineering Podcast
AUGUST 28, 2022
What are the different concerns that need to be included in a stack that supports fully automated data workflows? There was recently an interesting article suggesting that the "left-to-right" approach to data workflows is backwards.
100 
Data Engineering Weekly
SEPTEMBER 29, 2024
The article details how bypassing intermediate storage steps reduces latency and improves data processing speed. The approach highlights the importance of streamlining data workflows for faster machine learning model training and deployment.
Hevo
JUNE 14, 2024
Azure Data Factory (ADF) is a Microsoft-managed data integration solution that facilitates the creation of cloud-based data workflows. It is a fully managed service that can be used to build data pipelines by orchestrating data movement. It provides multi-cloud support and […]
Hevo
JUNE 7, 2024
No matter where you work or what you do, data will always be a part of your process. With every organization generating data like never before, it is essential to orchestrate tasks and automate data workflows in order to make sure they are properly executed without any delay. Apache Airflow is one of the most […]
40 
François Nguyen
MARCH 22, 2021
TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality. As you can see, this is in the code part where you are building your data pipelines, a misnomer because this is an over simplification. The other benefit is you can also use parameters and build a generic workflows to be re-used.
130 
ThoughtSpot
SEPTEMBER 6, 2023
The pathway from ETL to actionable analytics can often feel disconnected and cumbersome, leading to frustration for data teams and long wait times for business users. And even when we manage to streamline the data workflow, those insights aren’t always accessible to users unfamiliar with antiquated business intelligence tools.
104 
Cloudyard
JUNE 11, 2024
Read Time: 1 Minute, 48 Second RETRY LAST: In modern data workflows, tasks are often interdependent, forming complex task chains. Ensuring the reliability and resilience of these workflows is critical, especially when dealing with production data pipelines.
52 
Cloudera
AUGUST 22, 2024
By developing robust and secure data platforms, our team ensures businesses can derive meaningful insights that drive a competitive advantage. From enhancing data governance and security to optimizing data workflows and enabling real-time analytics, our team’s contributions are instrumental in shaping the future of data-driven enterprises.
Hevo
FEBRUARY 28, 2023
As raw data comes in various forms and sizes, it is essential to have a proper system to handle big data. One of the significant challenges is referencing data points as the complexities increase in data workflows.
52 
Snowflake
APRIL 17, 2024
In this Quickstart, you’ll learn how to perform key actions — from installing the Snowflake Python API to retrieving object data and managing Snowpark Container Services. Dive in to experience how the enhanced Python API streamlines your data workflows and unlocks the full potential of Python within Snowflake.
112 
Ascend.io
JULY 11, 2024
It enhances data quality, governance, and optimization, making data retrieval more efficient and enabling powerful automation in data engineering processes. As practitioners using metadata to fuel data teams, we at Ascend understand the critical role it plays in organizing, managing, and optimizing data workflows.
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.
52 
Monte Carlo
OCTOBER 1, 2024
This full breadth-and-depth approach to data observability requires coverage across the entire data stack, so we’ve continued to layer on robust integrations with new partners.
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.
Data Engineering Weekly
DECEMBER 29, 2022
Data catalogs are the most expensive data integration systems you never intended to build. Data Catalog as a passive web portal to display metadata requires significant rethinking to adopt modern data workflow, not just adding “modern” in its prefix. How happy are you with your data catalogs?
62 
Edureka
JULY 5, 2024
Integration Prepares data for analysis and visualization in Tableau Desktop and Tableau Prep Builder or other analytical tools. Directly visualizes and analyzes prepared data. Workflow Sequential data preparation steps: combining, cleaning, transforming. Interactive data exploration and visualization.
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.
100 
Data Engineering Weekly
DECEMBER 25, 2023
The Rising Impact of AI and Large Language Models 2023 witnessed a substantial impact of AI and large language models in data engineering. These technologies are increasingly automating processes like ETL, improving data quality management, and evolving the landscape of data tools.
Ascend.io
JUNE 10, 2024
At Ascend, we recognize the immense potential in integrating these advanced AI capabilities into our platform, enabling smarter applications and more efficient data workflows.
Cloudyard
FEBRUARY 19, 2024
The data, originating from different formats and sources, requires consolidation into Snowflake tables for comprehensive analysis. Therefore, Snowpark, with its capabilities in simplifying complex data workflows, becomes instrumental in achieving this objective. The journey begins with customer invoice data stored in a CSV file.
52 
Data Engineering Podcast
OCTOBER 22, 2021
In this episode Oliver Laslett describes why dashboards aren’t sufficient for business analytics, how Lightdash promotes the work that you are already doing in your data warehouse modeling with dbt, and how they are focusing on bridging the divide between data teams and business teams and the requirements that they have for data workflows.
100 
Data Engineering Podcast
JULY 17, 2022
Shipyard]([link] Shipyard is an orchestration platform that helps data teams build out solid data operations from the get-go by connecting data tools and streamlining data workflows.
130 
Monte Carlo
JULY 9, 2024
This transition can dramatically reduce latency in data availability, ensuring that information is up-to-date when it reaches end-users. Streamline Data Pipelines: Optimize your data workflows by employing techniques such as parallelization and caching. These methods can significantly enhance data flow efficiency.
52 
Christophe Blefari
SEPTEMBER 28, 2023
When it comes to incrementally change a data platform this is a bit different, you need to find what is going wrong and what could be improved. A lot of companies started with Postgres + dbt + Metabase, don't be ashamed.
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