Towards Data Science

FEBRUARY 6, 2024

ERP and CRM systems are designed and built to fulfil a broad range of business processes and functions. This generalisation makes their data models complex and cryptic and require domain expertise. As you do not want to start your development with uncertainty, you decide to go for the operational raw data directly.

Systems 79

Systems Raw Data Metadata Data Cleanse 79

Data Engineering Podcast

OCTOBER 15, 2021

Summary The binding element of all data work is the metadata graph that is generated by all of the workflows that produce the assets used by teams across the organization. The DataHub project was created as a way to bring order to the scale of LinkedIn’s data needs. No more scripts, just SQL.

Metadata 100

Metadata BI Data Warehouse Government 100

Ascend.io

APRIL 26, 2023

Data teams worldwide are building data pipelines with the point solutions that make up the “modern data stack.” Pipelines built with this approach are slow and require constant manual reprogramming and updates. For a deep dive into this level of automation, take a look at our What Is Data Pipeline Automation paper.

Data Pipeline 52

Data Pipeline Datasets Metadata Data 52

Netflix Tech

MARCH 7, 2024

The Machine Learning Platform (MLP) team at Netflix provides an entire ecosystem of tools around Metaflow , an open source machine learning infrastructure framework we started, to empower data scientists and machine learning practitioners to build and manage a variety of ML systems. ETL workflows), as well as downstream (e.g.

Systems 90

Systems Media Machine Learning Data Warehouse 90

Data Engineering Podcast

FEBRUARY 20, 2022

In this episode Guy Yachdav, director of software engineering for ImmunAI, shares the complexities that are inherent to managing data workflows for bioinformatics. RudderStack’s smart customer data pipeline is warehouse-first. You can observe your pipelines with built in metadata search and column level lineage.

Systems 100

Systems Software Engineer Software Engineering Data Warehouse 100

Ascend.io

NOVEMBER 28, 2023

The terms ‘data orchestration’ and ‘data pipeline orchestration’ are often used interchangeably, yet they diverge significantly in function and scope. Data orchestration refers to a wide collection of methods and tools that coordinate any and all types of data-related computing tasks.

Data Pipeline 52

Data Pipeline IT Data Metadata 52

Cloudera

MARCH 14, 2023

In this blog post we will put these capabilities in context and dive deeper into how the built-in, end-to-end data flow life cycle enables self-service data pipeline development. Key requirements for building data pipelines Every data pipeline starts with a business requirement.

Data Pipeline 83

Data Pipeline Designing Kafka Metadata 83

Data Engineering Podcast

DECEMBER 19, 2021

Summary Building a well managed data ecosystem for your organization requires a holistic view of all of the producers, consumers, and processors of information. The team at Metaphor are building a fully connected metadata layer to provide both technical and social intelligence about your data. No more scripts, just SQL.

Systems 100

Systems Building Metadata Data Warehouse 100

Ascend.io

MARCH 17, 2023

Theoretically, data and analytics should be the backbones of decision-making in business. Like mitochondria power a cell, data powers a business. Today, there are no intelligent systems that deliver data at the pace, and with the impact, leaders need to power the business. But for most companies, that’s not the reality.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52

Ascend.io

MARCH 17, 2023

Theoretically, data and analytics should be the backbones of decision-making in business. Like mitochondria power a cell, data powers a business. Today, there are no intelligent systems that deliver data at the pace, and with the impact, leaders need to power the business. But for most companies, that’s not the reality.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52

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 Data Raw Data Database 62

Towards Data Science

OCTOBER 25, 2023

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. You probably work closely with the colleague who builds the data pipeline that you were consuming. There was only one data team, two at most. How did they do it?

Data Pipeline 79

Data Pipeline SQL Data Architecture Data 79

Netflix Tech

NOVEMBER 14, 2023

We’ll discuss batch data processing, the limitations we faced, and how Psyberg emerged as a solution. Furthermore, we’ll delve into the inner workings of Psyberg, its unique features, and how it integrates into our data pipelining workflows. What is late-arriving data? How does late-arriving data impact us?

Data Engineering 105

Data Engineering Data Engineer Engineering Metadata 105

Ascend.io

MAY 8, 2023

The costs of developing and running data pipelines are coming under increasing scrutiny because the bills for infrastructure and data engineering talent are piling up. For data teams, it is time to ask: “How can we have an impact on these runaway costs and still deliver unprecedented business value?”

Data Pipeline 52

Data Pipeline Data Ingestion Metadata Data 52

Netflix Tech

SEPTEMBER 29, 2022

Timestone: Netflix’s High-Throughput, Low-Latency Priority Queueing System with Built-in Support for Non-Parallelizable Workloads by Kostas Christidis Introduction Timestone is a high-throughput, low-latency priority queueing system we built in-house to support the needs of Cosmos , our media encoding platform. Over the past 2.5

Systems 85

Systems Metadata Media Kafka 85

Snowflake

MAY 15, 2024

There’s a huge gap between the data quality most companies have by default and the data quality needed for successful AI. And that gap is directly affecting the performance and reliability of AI systems everywhere. Metaplane ensures that every company can trust the data that powers their business.

Cloud 108

Cloud Metadata Data Pipeline Government 108

Data Engineering Podcast

AUGUST 13, 2022

Data stacks are becoming more and more complex. This brings infinite possibilities for data pipelines to break and a host of other issues, severely deteriorating the quality of the data and causing teams to lose trust. Data stacks are becoming more and more complex. Sifflet also offers a 2-week free trial.

Metadata 100

Metadata MongoDB Scala MySQL 100

Monte Carlo

JUNE 14, 2023

In this post, we will help you quickly level up your overall knowledge of data pipeline architecture by reviewing: Table of Contents What is data pipeline architecture? Why is data pipeline architecture important? What is data pipeline architecture? Why is data pipeline architecture important?

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Cloudera

FEBRUARY 8, 2021

Below is the entire set of steps in the data lifecycle, and each step in the lifecycle will be supported by a dedicated blog post(see Fig. 1): Data Collection – data ingestion and monitoring at the edge (whether the edge be industrial sensors or people in a vehicle showroom).

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Data Pipeline Building Manufacturing Data Warehouse 116

Data Engineering Podcast

JULY 5, 2021

Summary At the core of every data pipeline is an workflow manager (or several). Deploying, managing, and scaling that orchestration can consume a large fraction of a data team’s energy so it is important to pick something that provides the power and flexibility that you need.

Systems 100

Systems Management Data Warehouse Programming Language 100

Netflix Tech

NOVEMBER 14, 2023

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. The session metadata table can then be read to determine the pipeline input.

Metadata 97

Metadata Data Pipeline Scala Data Workflow 97

Ascend.io

APRIL 12, 2023

From this research, we developed a framework with a sequence of stages to implement data integrity quickly and measurably via data pipelines. Table of Contents Why does data integrity matter? At every level of a business, individuals must trust the data, so they can confidently make timely decisions. Let’s explore!

Data Pipeline 52

Data Pipeline Data Integration Datasets Data 52

Precisely

MAY 13, 2024

Whether you’re bringing a new system online or connecting an existing database with your analytics platform, the process should be simple and straightforward. Integrated data catalog for metadata support As you build out your IT ecosystem, it’s important to leverage tools that have the capabilities to support forward-looking use cases.

Data Integration 52

Data Integration Metadata Amazon Web Services Data Governance 52

Ascend.io

APRIL 22, 2024

This initiative is more than just an upgrade; it’s a reimagining of what a Data Automation Platform can be: dynamic, extensible, and highly intelligent. A unified platform that combines a powerful metadata core, an extensible plugin architecture, DataAware automation, and multiple AI Assistants.

Project 52

Project Metadata Data Pipeline Data Engineering 52

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

In this episode Nick King discusses how you can be intentional about data creation in your applications and services to reduce the friction and errors involved in building data products and ML applications. Atlan is the metadata hub for your data ecosystem. What are some of the unique characteristics of that information?

Building 130

Building IT Metadata MongoDB 130

Data Engineering Podcast

DECEMBER 18, 2022

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. Struggling with broken pipelines? Missing data? Atlan is the metadata hub for your data ecosystem.

Metadata 130

Metadata Business Intelligence Data Lake BI 130

Booking.com Engineering

DECEMBER 2, 2022

BigQuery also offers native support for nested and repeated data schema[4][5]. We take advantage of this feature in our ad bidding systems, maintaining consistent data views from our Account Specialists’ spreadsheets, to our Data Scientists’ notebooks, to our bidding system’s in-memory data.

Systems 52

Systems Cloud MySQL Relational Database 52

Cloudera

DECEMBER 16, 2022

We are pleased to announce that Cloudera has been named a Leader in the 2022 Gartner ® Magic Quadrant for Cloud Database Management Systems. Our open, interoperable platform is deployed easily in all data ecosystems, and includes unique security and governance capabilities. 4-Ready for modern data fabric architectures.

Database 90

Database Cloud Systems Management 90

Data Engineering Podcast

OCTOBER 30, 2022

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. Especially once they realize 90% of all major data sources like Google Analytics, Salesforce, Adwords, Facebook, Spreadsheets, etc.,

Business Intelligence 130

Business Intelligence Metadata MongoDB MySQL 130

Data Engineering Podcast

DECEMBER 29, 2022

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. Struggling with broken pipelines? Missing data? Atlan is the metadata hub for your data ecosystem.

Management 130

Management Metadata Business Intelligence Data Lake 130

Data Engineering Podcast

DECEMBER 4, 2022

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. Data engineers don’t enjoy writing, maintaining, and modifying ETL pipelines all day, every day.

Business Intelligence 100

Business Intelligence Metadata BI MongoDB 100

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

Monte Carlo

MAY 14, 2024

At its core, a table format is a sophisticated metadata layer that defines, organizes, and interprets multiple underlying data files. Table formats incorporate aspects like columns, rows, data types, and relationships, but can also include information about the structure of the data itself.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

The Modern Data Company

JANUARY 22, 2024

In response, The Modern Data Company emerged, driven by a clear mission: to revolutionize data management and address challenges posed by a diverse and rapidly evolving data environment. Data engineering excellence Modern offers robust solutions for building, managing, and operationalizing data pipelines.

Data Integration 98

Data Integration Metadata Government Unstructured Data 98

Data Engineering Podcast

OCTOBER 23, 2022

Applying those same practices to data can prove challenging due to the number of systems that need to be included to implement a complete feature. Atlan is the metadata hub for your data ecosystem. Summary Agile methodologies have been adopted by a majority of teams for building software applications.

Project 130

Project Metadata MongoDB MySQL 130

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