Monte Carlo

JULY 11, 2023

Look for potential biases, flaws, or limitations in the data collection process. Below, we list a few examples: Data entry errors: Mistakes made during the process of entering data into a system can lead to inaccuracies. Accurate data without the necessary context or metadata can be challenging to interpret or use effectively.

Data Cleanse 40

Data Cleanse Datasets Data Governance Government 40

Monte Carlo

AUGUST 30, 2023

But there’s a lot to understand in order to both create the most value from your dbt tests and avoid leaning too heavily on a time-intensive process. Custom data tests are generally run every time a dbt `run` command is executed to process your transformations. And one of the most popular approaches is dbt testing.

SQL 52

SQL Datasets Database High Quality Data 52

Christophe Blefari

JANUARY 20, 2024

Every company out there has his own definition for the data engineer role. What is data engineering As I said it before data engineering is still a young discipline with many different definitions. Reddit r/dataengineering wiki a place where some data eng definitions are written. Who are the data engineers? This is not.

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

Monte Carlo

JULY 10, 2023

That’s where the definition of data completeness comes in. Data profiling Data profiling uses a tool or programming language to surface metadata about your data. The same is true with data. If all the information in a data set is accurate and precise, but key values or tables are missing, your analysis won’t be effective.

Data Collection 40

Data Collection Data Governance Government Data 40

Lyft Engineering

OCTOBER 3, 2023

Data quality is an amorphous term, with various definitions depending on the context. In Verity, we defined data quality as follows: Verity’s Definition of Data Quality The measure of how well data can be used as intended. Five aspects of data quality with the definition in italics and an example in quotes.

Big Data 84

Big Data Metadata Data Warehouse Data 84

Towards Data Science

MAY 7, 2024

Now you have to decide what sorts of things to test in order to figure out definitively if the tool is the right commitment for you and the team. This will help create an overall picture of logging, metadata, latency, CDC, and all the other things that come with a pipeline. Gather the team together and determine what these things are.

ETL Tools 84

ETL Tools Metadata Data Integration Data Science 84

Data Engineering Podcast

FEBRUARY 19, 2023

How does that change based on the type of query/processing engine being used? Acryl]([link] The modern data stack needs a reimagined metadata management platform. Acryl]([link] The modern data stack needs a reimagined metadata management platform. How does that change based on the type of query/processing engine being used?

IT 147

IT Data Lake Metadata Data Warehouse 147

Ascend.io

APRIL 22, 2024

A unified platform that combines a powerful metadata core, an extensible plugin architecture, DataAware automation, and multiple AI Assistants. Lack of unified metadata makes it difficult to optimize pipelines, avoid redundant processing, and quantify data engineering costs.

Project 52

Project Metadata Data Pipeline Data Engineering 52

Towards Data Science

NOVEMBER 4, 2023

How to Become a Data Engineer As a data engineer, I am tasked to design efficient data processes almost every day. It was created by Spotify to manage massive data processing workloads. Typical Airflow architecture includes a schduler based on metadata, executors, workers and tasks. Consider this example below.

Data Engineering 86

Data Engineering Data Engineer Engineering BI 86

Data Engineering Podcast

JULY 24, 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. What was your process for determining what subject areas to include in the book? Atlan is the metadata hub for your data ecosystem.

Data Engineering 100

Data Engineering Data Engineer Lambda Architecture Engineering 100

Data Engineering Podcast

FEBRUARY 26, 2023

In this episode he shares that journey and the combination of technical and organizational challenges that he encountered in the process. What is your philosophy on enforcing uniformity in technical systems vs. relying on interface definitions as the unit of consistency?

Building 147

Building Metadata Machine Learning Data Integration 147

Knowledge Hut

MARCH 7, 2024

Foresighted enterprises are the ones who will be able to leverage this data for maximum profitability through data processing and handling techniques. The greatest data processing challenge of 2024 is the lack of qualified data scientists with the skill set and expertise to handle this gigantic volume of data.

Big Data 98

Big Data Bytes Data Governance Raw Data 98

The Pragmatic Engineer

AUGUST 3, 2023

Now after 7 years, Google has announced it will retire Firebase Dynamic Links, but with no definite successor lined up. To make this migration easier and as seamless as possible, we will give developers the ability to export their deep-link metadata.”

Metadata 159

Metadata Engineering Building Technology 159

Data Engineering Podcast

SEPTEMBER 11, 2022

Ananth Packildurai created Schemata as a way to make the creation of schema contracts a lightweight process, allowing the dependency chains to be constructed and evolved iteratively and integrating validation of changes into standard delivery systems. Atlan is the metadata hub for your data ecosystem.

Systems 100

Systems Metadata Building MongoDB 100

Marc Lamberti

SEPTEMBER 22, 2023

That cake doesn’t get magicked into existence; it involves a process – a step-by-step recipe you carefully need to follow; otherwise, you will get something different. Digging into the official definition, you will see that Airflow is noted as an open-source platform that programmatically authors, schedules, and monitors workflows.

Data Pipeline 130

Data Pipeline Python Metadata Database 130

Monte Carlo

JANUARY 23, 2024

Today’s LLMs can already process enormous amounts of unstructured data, automating much of the monotonous work of data science. The ability of LLMs to process unstructured data is going to change a lot of the foundational table stakes that make up the core of engineering ,” he says. Those who don’t embrace it will be left behind.

Pipeline-centric 52

Pipeline-centric Database-centric Metadata Unstructured Data 52

Tweag

APRIL 19, 2023

To allow innovation in medical imaging with AI, we need efficient and affordable ways to store and process these WSIs at scale. A single hospital makes many captures a day, producing terabytes of such data to store and process. Much like Spark, its module ray.data is focused on loading and processing data as scale. width , spec.

Medical 60

Medical Process Cloud Bytes 60

Airbnb Tech

NOVEMBER 28, 2023

To meet this challenge, we introduced the “Midas” process to certify our data. Starting in 2020, the Midas process, along with the work to re-architect our most critical data models, has brought a dramatic increase in data quality and timeliness to Airbnb’s most critical data. Align on the input components for assessing data quality.

Data Warehouse 98

Data Warehouse Metadata Data Certification 98

Zalando Engineering

OCTOBER 18, 2023

The query directives are generally useful for clients to express certain types of metadata for the query. This process is cumbersome, but it is on purpose. on FIELD_DEFINITION For example, it is used in a query definition as follows - type CustomerConsent { status : String ! We will discuss this in detail in the next section.

Metadata 86

Metadata Coding Banking Designing 86

LinkedIn Engineering

APRIL 25, 2023

In our previous blog post on GraphQL, we explained how LinkedIn uses GraphQL to expedite the process of onboarding new use-cases for external API partners. entity schemas already go through a review process, a standardized way of federating these Rest.li specifically for GraphQL. Given that our Rest.li Custom lint rules on Rest.li

Architecture 109

Architecture Metadata Java Transportation 109

Cloudera

MARCH 9, 2021

In this blog, we’ll highlight the key CDP aspects that provide data governance and lineage and show how they can be extended to incorporate metadata for non-CDP systems from across the enterprise. Atlas provides open metadata management and governance capabilities to build a catalog of all assets, and also classify and govern these assets.

Data Governance 94

Data Governance Government Metadata Datasets 94

DoorDash Engineering

APRIL 12, 2023

The Metrics Layer, also known as a Semantic Layer, is a critical component of the modern data stack that has recently received significant industry attention offers a powerful solution to the challenge of standardizing metric definitions. We will also dive deep into our design and implementation processes and the lessons we learnt.

SQL 82

SQL Metadata Raw Data Government 82

François Nguyen

JANUARY 18, 2021

In every step,we do not just read, transform and write data, we are also doing that with the metadata. The Dataops Heritage In my previous article, I have described the loop around the devops part of dataops. Last part, it was added the data security and privacy part.

Data Governance 130

Data Governance Metadata Government Data Pipeline 130

DoorDash Engineering

DECEMBER 5, 2023

Almost six billion messages are processed each day at an average rate of four million messages per minute, which sometimes peaks at double that rate. The slowest step in that process was provisioning Kafka Topics, which involved on-call engineer approval and was prone to failure, further increasing the on-call load.

Kafka 91

Kafka Programming Language Metadata Architecture 91

Data Engineering Podcast

MAY 22, 2022

What is the process for setting up a Flyte deployment? What are the patterns that you and the community have established to encourage discovery and reuse of granular task definitions? Data orchestration engines are a natural point for generating and taking advantage of rich metadata.

Machine Learning 130

Machine Learning Data Engineering Data Engineer Cloud 130

Cloudera

MARCH 14, 2023

Allows them to iteratively develop processing logic and test with as little overhead as possible. Plays nice with existing CI/CD processes to promote a data pipeline to production. Attributes contain key metadata like the source directory of a file or the source topic of a Kafka message.

Data Pipeline 81

Data Pipeline Designing Kafka Metadata 81

Christophe Blefari

FEBRUARY 3, 2023

What's often stays is that AE is between DE and DA, so the definition is often done complementarily to other positions. Think is SQL, avoid writing SQL in a top to bottom approach — A nice post about the mismatch between the logical query processing order and the syntaxic order of SQL queries. Nothing new under the sun.

BI 130

BI Google Cloud SQL Machine Learning 130

Cloudera

SEPTEMBER 29, 2022

It is a set of rubrics around people, process, and technology choices that allow for companies to scale their data systems. . The data product is not just the data itself, but a bunch of metadata that surrounds it — the simple stuff like schema is a given. Data mesh is about people, process, and technology. Data mesh defined.

Architecture 73

Architecture Data Architecture Metadata Data Warehouse 73

Snowflake

DECEMBER 12, 2023

To give customers flexibility for how they fit Snowflake into their data architecture, Iceberg Tables can be configured to use either Snowflake or an external service such as AWS Glue as the table’s catalog to track metadata, with an easy, one-line SQL command to convert the table’s catalog to Snowflake in a metadata-only operation.

Metadata 89

Metadata Python AWS Government 89

RandomTrees

FEBRUARY 6, 2024

Generative AI corrects data imbalances, ensuring fair sentiment analysis on e-commerce platforms, enriches training data for natural language processing (NLP) tasks. Data’s exponential growth : Gen AI holds the potential to address this challenge by automating data processing tasks, extracting valuable insights from the vast amounts of data.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Databand.ai

AUGUST 30, 2023

It utilizes various techniques to identify and resolve data quality issues, ensuring that high-quality data is used for business processes and decision-making. A shorter time-to-value indicates that your organization is efficient at processing and analyzing data for decision-making purposes.

Data Cleanse 52

Data Cleanse Metadata High Quality Data Datasets 52

LinkedIn Engineering

JUNE 26, 2023

For streaming data pipelines, this involves writing stream processing jobs. A developer would need to write and operationalize a custom stream processing job to replicate their Brooklin datastream into a Kafka topic. This means that data pipelines almost always require some form of stream processing in the middle.

Data Pipeline 112

Data Pipeline Kafka MySQL SQL 112

LinkedIn Engineering

JULY 19, 2023

Open source data lakehouse deployments are built on the foundations of compute engines (like Apache Spark, Trino, Apache Flink), distributed storage (HDFS, cloud blob stores), and metadata catalogs / table formats (like Apache Iceberg, Delta, Hudi, Apache Hive Metastore). Tables are governed as per agreed upon company standards.

Big Data 78

Big Data Data Management Management Metadata 78

dbt Developer Hub

DECEMBER 19, 2023

Integration points ​ Discovery API (formerly referred to as Metadata API) Overview — This GraphQL API allows you to query the metadata that dbt Cloud generates every time you run a dbt project. The job level will only provide you the metadata of one job, giving you only a small snapshot of part of the project.

Metadata 52

Metadata Cloud Accessible Accessibility 52

ProjectPro

NOVEMBER 30, 2021

This guide provides definitions, a step-by-step tutorial, and a few best practices to help you understand ETL pipelines and how they differ from data pipelines. It was a manual process and very challenging as well. Instead, loading data can trigger new processes and flows in a Data Pipeline by triggering webhooks in other systems.

Process 52

Process Data Pipeline Data Warehouse AWS 52

Ascend.io

FEBRUARY 28, 2024

Engineers ensure the availability of clean, structured data, a necessity for AI systems to learn from patterns, make accurate predictions, and automate decision-making processes. Through the design and maintenance of efficient data pipelines , data engineers facilitate the seamless flow and accessibility of data for AI processing.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Monte Carlo

FEBRUARY 26, 2024

It uses metadata to create a picture of the data, as well as the relationships between data assets of diverse sources, and the processing that takes place as data moves through systems. Ataccama can be deployed anywhere and can be customized without coding via a metadata-based configuration. Atlan Atlan data catalog.

Metadata 52

Metadata Government Data Data Governance 52