Towards Data Science

OCTOBER 25, 2023

Not too long ago, almost all data architectures and data team structures followed a centralized approach. As a data or analytics engineer, you knew where to find all the transformation logic and models because they were all in the same codebase. There was only one data team, two at most.

Data Pipeline 82

Data Pipeline SQL Data Architecture Data 82

Workfall

AUGUST 14, 2023

Reading Time: 7 minutes In today’s data-driven world, efficient data pipelines have become the backbone of successful organizations. These pipelines ensure that data flows smoothly from various sources to its intended destinations, enabling businesses to make informed decisions and gain valuable insights.

Data Pipeline 62

Data Pipeline Raw Data Data Database 62

Netflix Tech

NOVEMBER 14, 2023

By Abhinaya Shetty , Bharath Mummadisetty At Netflix, our Membership and Finance Data Engineering team harnesses diverse data related to plans, pricing, membership life cycle, and revenue to fuel analytics, power various dashboards, and make data-informed decisions. We expect complete and accurate data at the end of each run.

Data Engineering 105

Data Engineering Data Engineer Engineering Metadata 105

Jesse Anderson

NOVEMBER 14, 2023

A Guest Post by Ole Olesen-Bagneux In this blog post I would like to describe a new data team, that I call ‘the data discovery team’. Data discovery is thought of in different ways in data science and in information science respectfully. In an enterprise data reality, searching for data is a bit of a hassle.

Metadata 147

Metadata Data Science Big Data Data 147

Snowflake

MAY 15, 2024

According to Infosys, 35% of AI projects will either fail or experience delays because of poor data quality. There’s a huge gap between the data quality most companies have by default and the data quality needed for successful AI. Metaplane ensures that every company can trust the data that powers their business.

Cloud 90

Cloud Metadata Data Pipeline Government 90

Data Engineering Podcast

AUGUST 13, 2022

Summary Data is useless if it isn’t being used, and you can’t use it if you don’t know where it is. Data catalogs were the first solution to this problem, but they are only helpful if you know what you are looking for. Data stacks are becoming more and more complex. Sifflet also offers a 2-week free trial.

Metadata 100

Metadata MongoDB Scala MySQL 100

Precisely

MAY 13, 2024

Key Takeaways: Data integration is vital for real-time data delivery across diverse cloud models and applications, and for leveraging technologies like generative AI. As enterprise technology landscapes grow more complex, the role of data integration is more critical than ever before.

Data Integration 52

Data Integration Metadata Amazon Web Services Data Governance 52

Towards Data Science

APRIL 6, 2023

Today’s post follows the same philosophy: fitting local and cloud pieces together to build a data pipeline. And, when it comes to data engineering solutions, it’s no different: They have databases, ETL tools, streaming platforms, and so on — a set of tools that makes our life easier (as long as you pay for them). not sponsored.

AWS 79

AWS Data Pipeline Amazon Web Services Python 79

Data Engineering Podcast

NOVEMBER 13, 2022

Summary Building data products is an undertaking that has historically required substantial investments of time and talent. With the rise in cloud platforms and self-serve data technologies the barrier of entry is dropping. Atlan is the metadata hub for your data ecosystem.

Building 130

Building Metadata MongoDB MySQL 130

Netflix Tech

DECEMBER 14, 2023

Engineers from across the company came together to share best practices on everything from Data Processing Patterns to Building Reliable Data Pipelines. The result was a series of talks which we are now sharing with the rest of the Data Engineering community!

Data Engineering 103

Data Engineering Data Engineer Engineering Metadata 103

Data Engineering Podcast

NOVEMBER 6, 2022

Summary A lot of the work that goes into data engineering is trying to make sense of the "data exhaust" from other applications and services. Atlan is the metadata hub for your data ecosystem. Data engineers don’t enjoy writing, maintaining, and modifying ETL pipelines all day, every day.

Building 130

Building IT Metadata MongoDB 130

Ascend.io

APRIL 22, 2024

At Ascend, we believe it’s time to rethink data engineering from the ground up. As the world of data continues to evolve at a breakneck pace, we are thrilled to announce the next revolutionary step in our journey – Project Inception. Read More: The State of Data Engineering in 2023: Does Your Data Program Stack Up?

Project 52

Project Metadata Data Pipeline Data Engineering 52

Ascend.io

APRIL 12, 2023

Right now, at this moment, are you prepared to act on your company’s data? So when we talk about making data usable, we’re having a conversation about data integrity. Data integrity is the overall readiness to make confident business decisions with trustworthy data, repeatedly and consistently. If not, why?

Data Pipeline 52

Data Pipeline Data Integration Datasets Data 52

Netflix Tech

NOVEMBER 14, 2023

In the previous installments of this series, we introduced Psyberg and delved into its core operational modes: Stateless and Stateful Data Processing. Now, let’s explore the state of our pipelines after incorporating Psyberg. Pipelines After Psyberg Let’s explore how different modes of Psyberg could help with a multistep data pipeline.

Metadata 97

Metadata Data Pipeline Scala Data Workflow 97

Data Engineering Podcast

JULY 17, 2022

Summary There are extensive and valuable data sets that are available outside the bounds of your organization. Whether that data is public, paid, or scraped it requires investment and upkeep to acquire and integrate it with your systems. Atlan is the metadata hub for your data ecosystem.

Data Management 130

Data Management Management Metadata MongoDB 130

Data Engineering Podcast

DECEMBER 4, 2022

Summary Business intelligence is the foremost application of data in organizations of all sizes. Zing Data is building a mobile native platform for business intelligence. Atlan is the metadata hub for your data ecosystem. And don’t forget to thank them for their continued support of this show!

Business Intelligence 100

Business Intelligence Metadata BI MongoDB 100

Christophe Blefari

JANUARY 20, 2024

Learn data engineering, all the references ( credits ) This is a special edition of the Data News. But right now I'm in holidays finishing a hiking week in Corsica 🥾 So I wrote this special edition about: how to learn data engineering in 2024. The idea is to create a living reference about Data Engineering.

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

Data Engineering Podcast

OCTOBER 30, 2022

In its current incarnation it has become a ubiquitous need for analytics and opportunities to answer questions with data. In this episode Amir Orad discusses the Sisense platform and how it facilitates the embedding of analytics and data insights in every aspect of organizational and end-user experiences.

Business Intelligence 130

Business Intelligence Metadata MongoDB MySQL 130

Towards Data Science

FEBRUARY 6, 2024

This generalisation makes their data models complex and cryptic and require domain expertise. Even harder to manage, a common setup within large organisations is to have several instances of these systems with some underlaying processes in charge of transmitting data among them, which could lead to duplications, inconsistencies, and opacity.

Systems 83

Systems Raw Data Metadata Data Cleanse 83

Data Engineering Podcast

JUNE 19, 2022

Summary Data analysis is a valuable exercise that is often out of reach of non-technical users as a result of the complexity of data systems. Atlan is the metadata hub for your data ecosystem. Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code.

Metadata 130

Metadata Unstructured Data MongoDB MySQL 130

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. TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality. How do we build data products ? How can we interoperate between the data domains ?

Architecture 130

Architecture Technology Google Cloud Metadata 130

Data Engineering Podcast

JULY 10, 2022

Summary Building a data platform is a journey, not a destination. In this episode Inbar Yogev and Lior Winner share the journey that they and their teams at Riskified have been on for their data platform. They also discuss how they have established a guild system for training and supporting data professionals in the organization.

Metadata 100

Metadata MongoDB MySQL Data Pipeline 100

Data Engineering Podcast

OCTOBER 9, 2022

Summary The core of any data platform is the centralized storage and processing layer. For many that is a data warehouse, but in order to support a diverse and constantly changing set of uses and technologies the data lakehouse is a paradigm that offers a useful balance of scale and cost, with performance and ease of use.

Metadata 100

Metadata AWS MongoDB MySQL 100

dbt Developer Hub

SEPTEMBER 14, 2021

Embedding the DAG within the IDE makes investigating project structure a lot easier The Metadata API : Now in GA! Assess data health with the metadata generated by recent dbt job runs Dashboard Status Tiles : Embed this tile anywhere iFrames live to quickly check data freshness New Resources ​ Things to Read ?

Metadata 52

Metadata Data Pipeline Python Cloud 52

Data Engineering Podcast

SEPTEMBER 25, 2022

Summary Regardless of how data is being used, it is critical that the information is trusted. The practice of data reliability engineering has gained momentum recently to address that question. Atlan is the metadata hub for your data ecosystem. And don’t forget to thank them for their continued support of this show!

Building 100

Building Metadata MongoDB MySQL 100

Christophe Blefari

OCTOBER 20, 2023

Read my dbt multi-project guide 📺 On the content side I'll also present next week the Fancy Data Stack project at the Data Engineering And Machine Learning Summit 2023 organised by Seattle Data Guy. This post gives great insights about the impact on the data platform team. What are the main differences?

Generalist 130

Generalist Entertainment NoSQL Datasets 130

Data Engineering Podcast

AUGUST 21, 2022

Summary The position of Chief Data Officer (CDO) is relatively new in the business world and has not been universally adopted. In this episode Tracy Daniels, CDO of Truist, shares her journey into the position, her responsibilities, and her relationship to the data professionals in her organization.

Metadata 100

Metadata MongoDB MySQL Data Lake 100

Data Engineering Podcast

AUGUST 28, 2022

For data engineers, this is a monumental undertaking. Atlan is the metadata hub for your data ecosystem. Instead of locking your metadata into a new silo, unleash its transformative potential with Atlan’s active metadata capabilities. The only thing worse than having bad data is not knowing that you have it.

Data Engineering 100

Data Engineering Data Engineer MongoDB Metadata 100

Data Engineering Podcast

JULY 3, 2022

Summary The ecosystem for data tools has been going through rapid and constant evolution over the past several years. These technological shifts have brought about corresponding changes in data and platform architectures for managing data and analytical workflows. Atlan is the metadata hub for your data ecosystem.

Architecture 100

Architecture Metadata MongoDB MySQL 100

Data Engineering Weekly

MAY 16, 2023

In the first part of this series, we talked about design patterns for data creation and the pros & cons of each system from the data contract perspective. In the second part, we will focus on architectural patterns to implement data quality from a data contract perspective. Why is Data Quality Expensive?

Engineering 110

Engineering Kafka Data Pipeline Data Warehouse 110

Netflix Tech

MARCH 10, 2023

This platform has evolved from supporting studio applications to data science applications, machine-learning applications to discover the assets metadata, and build various data facts. During this evolution, quite often we receive requests to update the existing assets metadata or add new metadata for the new features added.

Management 94

Management Kafka Metadata Media 94

Marc Lamberti

SEPTEMBER 22, 2023

Stemming from this analogy, “you” is the orchestrator in data orchestration, and the recipe is the data pipeline. It was created in 2014 by Airbnb and has since been widely adopted by the data engineering community, primarily as it was the first orchestrator allowing to author data pipelines programmatically.

Data Pipeline 130

Data Pipeline Python Metadata Database 130

Data Engineering Podcast

JUNE 12, 2022

Summary Building a well rounded and effective data team is an iterative process, and the first hire can set the stage for future success or failure. Trupti Natu has been the first data hire multiple times and gone through the process of building teams across the different stages of growth.

Metadata 100

Metadata Unstructured Data Business Intelligence MongoDB 100

Monte Carlo

APRIL 20, 2024

That’s where you really want to focus your data quality monitoring.” And it’s true – you need to go “deep” on certain data sets; but if you’re not monitoring broadly as well, you’re missing the boat—and a whole lot of bad data. What is data quality monitoring?

IT 52

IT Metadata Data Warehouse BI 52

Data Engineering Podcast

JULY 31, 2022

Summary Data lineage is the roadmap for your data platform, providing visibility into all of the dependencies for any report, machine learning model, or data warehouse table that you are working with. Atlan is the metadata hub for your data ecosystem.

IT 100

IT Metadata MongoDB MySQL 100

Monte Carlo

JANUARY 29, 2024

It’s one thing to get your data into a modern data cloud. Monte Carlo is thrilled to be part of the Snowflake Horizon partner ecosystem as we leverage many of the pre-built features Snowflake provides in order to help organizations reduce their data downtime and improve data quality at scale.

Metadata 64

Metadata High Quality Data Data Pipeline Machine Learning 64

Ascend.io

FEBRUARY 28, 2024

The rise of generative AI is changing more than just technology; it’s reshaping our professional landscapes — and yes, data engineering is directly experiencing the impact. How does AI recalibrate the workload and priorities of data teams? How can data engineers harness the power of AI?

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52