Tweag

NOVEMBER 1, 2023

The last important remaining piece to explore is the merge system. In this post, we’ll see how to use the Nickel merge system to write reusable configuration modules, and why the merge approach seems to be more adapted for modular configurations than plain functions, despite Nickel being a functional language.

Metadata 104

Metadata Programming Programming Language Coding 104

Monte Carlo

JULY 11, 2023

Examples of inaccurate data Inaccurate data can arise in a few different ways, all primarily due to manual errors, system hiccups, code changes, or data pipeline breakages. Below, we list a few examples: Data entry errors: Mistakes made during the process of entering data into a system can lead to inaccuracies.

Data Cleanse 40

Data Cleanse Datasets Data Governance Government 40

Knowledge Hut

MARCH 7, 2024

Syncing Across Data Sources Once you import data into Big Data platforms you may also realize that data copies migrated from a wide range of sources on different rates and schedules can rapidly get out of the synchronization with the originating system. Two, it creates a commonality of data definitions, concepts, metadata and the like.

Big Data 98

Big Data Bytes Data Governance Raw Data 98

Tweag

MAY 16, 2023

That’s a dangerous mistake: with the advent of IaC for the cloud, configuration has become an important aspect of modern software systems, and a critical point of failure. A REPL nickel repl , a markdown documentation generator nickel doc and a nickel query command to retrieve metadata, types and contracts from code.

MySQL 131

MySQL Metadata Data Validation Coding 131

Netflix Tech

DECEMBER 3, 2022

Thanks to the Netflix internal lineage system (built by Girish Lingappa ) Dataflow migration can then help you identify downstream usage of the table in question. Workflow Definitions Below you can see a typical file structure of a sample workflow package written in SparkSQL. ??? backfill.sch.yaml ??? daily.sch.yaml ???

Data Pipeline 143

Data Pipeline Scala Metadata Food 143

Monte Carlo

MARCH 4, 2024

Table of Contents How Data Observability Works Made For The Lakehouse: Iceberg and Delta Transform in place: Dynamic Tables and Delta Live Tables Why This Matters How Data Observability Works Data observability provides full visibility into your data, systems, and code so you can find and fix bad data quickly.

Metadata 52

Metadata Data Lake Data Warehouse Data Engineering 52

Data Engineering Podcast

MARCH 27, 2022

You have full control over your data and their plugin system lets you integrate with all of your other data tools, including data warehouses and SaaS platforms. What is your working definition of "data governance" and how does that influence your product focus and priorities?

Data Governance 130

Data Governance Government Cloud Building 130

Monte Carlo

JULY 10, 2023

That’s where the definition of data completeness comes in. For example, let’s say a streaming provider has 10 million overall subscribers who can access its content. Data profiling Data profiling uses a tool or programming language to surface metadata about your data. The same is true with data.

Data Collection 40

Data Collection Data Governance Government Data 40

Christophe Blefari

FEBRUARY 3, 2023

ebay, Variable Hub a data access layer for risk decisioning — Looks like a feature store but for risk topics. Lyft, powering millions of real-time decisions with LyftLearn Serving — Architecture of the decentralized system Lyft use to deploy and serve ml models. In the end actually, the answer depends.

BI 130

BI Google Cloud SQL Machine Learning 130

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

Zalando Engineering

OCTOBER 18, 2023

The query directives are generally useful for clients to express certain types of metadata for the query. The type system directives are available for the locations listed below. We can access the request parameters (like pathname) by running GraphQL over HTTP. The directive @sensitive is used for this purpose.

Metadata 86

Metadata Coding Banking Designing 86

Data Engineering Podcast

MAY 18, 2021

Summary Data lineage is the common thread that ties together all of your data pipelines, workflows, and systems. In order to eliminate the wasted effort of building custom integrations every time you want to combine lineage information across systems Julien Le Dem introduced the OpenLineage specification.

Metadata 100

Metadata Kafka Data Warehouse Hadoop 100

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. Additionally, data catalogs can centrally enforce rules of access, security, and governance, all in a way that is both automatic and visible.

Metadata 52

Metadata Government Data Data Governance 52

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 (not files/blobs) are the only API abstraction for end-users.

Big Data 78

Big Data Data Management Management Metadata 78

Cloudera

OCTOBER 7, 2021

Application Logic: Application logic refers to the type of data processing, and can be anything from analytical or operational systems to data pipelines that ingest data inputs, apply transformations based on some business logic and produce data outputs. Data and Metadata: Data inputs and data outputs produced based on the application logic.

Architecture 124

Architecture Metadata Government Kafka 124

ThoughtSpot

JUNE 28, 2023

Getting started with version control APIs To begin, ensure that the following prerequisites are met: You have admin access (can administer Thoughtspot privilege) to connect ThoughtSpot to a Git repository and deploy commits. dev) would function in the destination ThoughtSpot instance prior to merging a source branch into a target branch (i.e.

Metadata 72

Metadata Accessible Accessibility Utilities 72

LinkedIn Engineering

APRIL 25, 2023

Here are some of the primary differences compared to the widely used architecture in the industry: The GraphQL type system used at LinkedIn is completely autogenerated. Type System Generator The GraphQL type system used at LinkedIn is autogenerated by federating individual entity schemas from the Rest.li Given that our Rest.li

Architecture 109

Architecture Metadata Java Transportation 109

Ascend.io

FEBRUARY 28, 2024

The foundation of any AI system is high-quality data. 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. And crucially, what does the future hold for data engineering in an AI-driven world?

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Monte Carlo

JANUARY 23, 2024

As the machine became smarter with the next generation of data access, we flattened everything to features and columns. Almost every business I walk into, you can talk to the marketing team and the sales team and they have different definitions of things with the same name,” John says. “I Those who don’t embrace it will be left behind.

Pipeline-centric 52

Pipeline-centric Database-centric Metadata Unstructured Data 52

Cloudera

MARCH 14, 2023

For example, a developer may be asked to tap into the data of a newly acquired application, parsing and transforming it before delivering it to the business’s favorite analytical system where it can be joined with existing data sets. Attributes contain key metadata like the source directory of a file or the source topic of a Kafka message.

Data Pipeline 83

Data Pipeline Designing Kafka Metadata 83

Towards Data Science

MAY 26, 2023

Usually an external system is needed (e.g. The good news is, if you use Hamilton, there isn’t the need for another system to get lineage; making use of lineage is straightforward too! Taking this code and connecting with e.g. a version control system (e.g. Adding metadata to make lineage more useful!

Metadata 83

Metadata Data Science Coding Machine Learning 83

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. Lack of governance Our platform lacked governance policies for metric definitions.

SQL 82

SQL Metadata Raw Data Government 82

Knowledge Hut

JULY 24, 2023

In the world of databases, data independence plays a vital role in making sure the flexibility and adaptability of database systems. It allows changes to be made at various levels of a database system without causing disruptions or requiring extensive modifications to the applications that rely on the data.

Database Design 52

Database Design Relational Database Metadata Database 52

ProjectPro

FEBRUARY 8, 2023

Then, Glue writes the job's metadata into the embedded AWS Glue Data Catalog. AWS Glue then creates data profiles in the catalog, a repository for all data assets' metadata, including table definitions, locations, and other features. Why Use AWS Glue? Establish a crawler schedule. AWS Glue object list searches and filtering.

AWS 98

AWS Scala Metadata Data Lake 98

Engineering at Meta

OCTOBER 31, 2023

SCARF scans production data systems to identify tables or assets that are unused and safely removes them. This process can be unexpectedly difficult, because large software systems are inevitably interconnected. Meta has a separate system, DELF , for deleting individual records, rows, and objects.

Data 93

Data Metadata Coding Relational Database 93

Databand.ai

AUGUST 30, 2023

The importance of data quality cannot be overstated, as poor-quality data can result in incorrect conclusions, inefficient operations, and a lack of trust in the information provided by a company’s systems. Consistency: The uniformity of data across different sources or systems.

Data Cleanse 52

Data Cleanse Metadata High Quality Data Datasets 52

AltexSoft

AUGUST 22, 2022

A data fabric is an architecture design presented as an integration and orchestration layer built on top of multiple disjointed data sources like relational databases , data warehouses , data lakes, data marts , IoT , legacy systems, etc., Unified data access. to provide a unified view of all enterprise data. API support.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

Data Engineering Podcast

FEBRUARY 6, 2022

He also explains how he and his team at Privacy Dynamics are working to make those strategies more accessible to organizations so that you can focus on all of the other tasks required of you. You can observe your pipelines with built in metadata search and column level lineage. What are the risks of false positives vs. false negatives?

Data Pipeline 100

Data Pipeline Data Metadata Software Engineer 100

Netflix Tech

NOVEMBER 13, 2023

In this blog post, we will introduce speech and music detection as an enabling technology for a variety of audio applications in Film & TV, as well as introduce our speech and music activity detection (SMAD) system which we recently published as a journal article in EURASIP Journal on Audio, Speech, and Music Processing.

Datasets 89

Datasets Metadata Algorithm Architecture 89

Cloudera

NOVEMBER 13, 2020

The commonly-accepted best practice in database system design for years is to use an exhaustive search strategy to consider all the possible variations of specific database operations in a query plan. Metadata Caching. Impala’s planner simplifies planning in several ways. More on this below.

Metadata 143

Metadata Coding SQL Database 143

LinkedIn Engineering

JUNE 26, 2023

However, we've found that this vertical self-service model doesn't work particularly well for data pipelines, which involve wiring together many different systems into end-to-end data flows. For example, Pinot ingestion by default expects records to be flat, with field names and types that are compatible with the Pinot table definition.

Data Pipeline 112

Data Pipeline Kafka MySQL SQL 112

Precisely

SEPTEMBER 5, 2023

Master Data Management systems (MDM) play an important role in harmonizing data assets across large and midsize enterprises. Many businesses have multiple systems that house customer data, for example. That may include transactional and operational data, reference data, metadata , and audit information, for example.

Data Governance 52

Data Governance Government Data Management Management 52

Monte Carlo

DECEMBER 8, 2023

Data lineage is a visual tool that tracks the movement and transformations of data through various systems, processes, and applications. Data provenance is the record of metadata from data’s original sources, providing the historical context and authenticity of data. Enter: data provenance and data lineage.

Metadata 52

Metadata Data Data Warehouse Government 52

Monte Carlo

DECEMBER 8, 2023

Data lineage is a visual tool that tracks the movement and transformations of data through various systems, processes, and applications. Data provenance is the record of metadata from data’s original sources, providing the historical context and authenticity of data. Enter: data provenance and data lineage.

Metadata 52

Metadata Data Data Warehouse Government 52

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. And during this time they will by definition have a hybrid architecture.

Architecture 74

Architecture Data Architecture Metadata Data Warehouse 74

Rockset

OCTOBER 13, 2023

If the embedding provider is in the cloud, then the availability of your system—even for queries—will depend on the availability of the provider. If your data is too sensitive to send outside your walls, or if system availability is of paramount concern, it is possible to locally produce embeddings.

Database 52

Database Metadata Algorithm Cloud 52

The Modern Data Company

MARCH 1, 2024

Each Data Product is designed for a specific purpose, equipped with the necessary data, transformations, and metadata. Data Products simplify access and processing, empowering faster decision-making. Democratized Data Access: Empower business users with self-service access to relevant data insights, fostering a data-driven culture.

Database-centric 40

Database-centric Data Lake Government Retail 40