Monte Carlo

JANUARY 5, 2024

In this article, we’ll peel back the 5 layers that make up data lakehouse architecture: data ingestion, data storage, metadata, API, and data consumption, understand the expanded opportunities a data lakehouse opens up for generative AI, and how to maintain data quality throughout the pipeline with data observability. Metadata layer 4.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

In this article, we’ll peel back the 5 layers that make up data lakehouse architecture: data ingestion, data storage, metadata, API, and data consumption, understand the expanded opportunities a data lakehouse opens up for generative AI, and how to maintain data quality throughout the pipeline with data observability. Metadata layer 4.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Data Engineering Weekly

MARCH 10, 2024

Google: Croissant- a metadata format for ML-ready datasets Google Research introduced Croissant, a new metadata format designed to make datasets ML-ready by standardizing the format, facilitating easier use in machine learning projects. Thanks to Ideas2IT Technologies for hosting us in their fantastic space.

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

Towards Data Science

FEBRUARY 6, 2024

Discoverability : A shared data platform provides a catalog of operational datasets in the form of source-aligned data products that helped me to understand the status and nature of the data exposed. Metadata update Data products need to be understandable. Accessibility : I could easily request access to these data products.

Systems 83

Systems Raw Data Metadata Data Cleanse 83

Data Engineering Podcast

DECEMBER 16, 2019

Summary Building clean datasets with reliable and reproducible ingestion pipelines is completely useless if it’s not possible to find them and understand their provenance. The solution to discoverability and tracking of data lineage is to incorporate a metadata repository into your data platform.

Metadata 100

Metadata PostgreSQL Datasets Data Warehouse 100

François Nguyen

MARCH 22, 2021

and he/she has different actions to execute (reading, calling a vision API, transform, create metadata, store them, etc…). The data domain Discovery portal with all the metadata on the data life cycle 4.Federated TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality.

Architecture 130

Architecture Technology Google Cloud Metadata 130

Cloudera

AUGUST 26, 2021

In this blog post, we will ingest a real world dataset into Ozone, create a Hive table on top of it and analyze the data to study the correlation between new vaccinations and new cases per country using a Spark ML Jupyter notebook in CML. On creation of the bucket, we also upload a COVID dataset [1] that is a CSV with about 100K rows.

Data Science 109

Data Science Cloud Hadoop Metadata 109

dbt Developer Hub

OCTOBER 30, 2023

Well, the warehouse “cheats” by only copying metadata from the source schema to the target schema; the underlying data remains at rest during this operation. This metadata includes materialized objects like tables and views, which is why you see a clone of these objects in the target schema. dbt clone is a new command in dbt 1.6

BI 52

BI Datasets Metadata Data Warehouse 52

Data Engineering Weekly

MARCH 24, 2024

Moirai utilizes a large, diverse dataset and innovative techniques like any-variate attention and multiple patch-size projection layers to model complex, variable patterns. The APIs support emitting unstructured log lines and typed metadata key-value pairs (per line).

Data Engineering 62

Data Engineering Data Engineer Engineering Metadata 62

Lyft Engineering

OCTOBER 3, 2023

Semantic Correctness —  The core.rider_events derived dataset shows a drastic increase in today’s cancels volume, caused by a bug in the origin web service creating the event. Check Result— The numeric measurement of data quality at a point in time, a boolean pass/fail value, and metadata about this run.

Big Data 84

Big Data Metadata Data Warehouse Data 84

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 93

Data Governance Government Metadata Datasets 93

Precisely

SEPTEMBER 11, 2023

By 2025, 50% of data and analytics leaders will be using augmented MDM and active metadata to enhance their capabilities – demonstrating that beyond data quality, automation is also in demand for data governance, data catalog, and security solutions. Problem: “We’re uncertain about compliance with privacy regulations!

Metadata 52

Metadata Data Integration Datasets Data Analysis Tools 52

Ascend.io

FEBRUARY 28, 2024

Metadata Management for Enhanced Machine Interpretation Data engineering extends its importance to the realm of metadata management, providing AI models with essential context about data definitions, classifications, and governance policies. ChatGPT screenshot showing the schema of a dataset and the documentation for it.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Precisely

APRIL 11, 2023

It’s critical that business analysts have the data they need and that IT has the appropriate metadata associated with those datasets for seamless replication into the cloud. The metadata will automatically be cataloged in the suite to enable additional insights.

Accessible 52

Accessible Accessibility Metadata Data Integration 52

LinkedIn Engineering

DECEMBER 12, 2023

We say that an algorithm is differentially private if any result of the algorithm cannot depend too much on any single data record in a dataset. Hence, differential privacy provides uncertainty for whether or not an individual data record is in the dataset.

Algorithm 77

Algorithm Metadata SQL Datasets 77

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

Monte Carlo

APRIL 20, 2024

To do this, you need data monitors that drill “ deep ” into the data using both machine learning and user-defined rules, as well as metadata monitors to scale “ broadly ” across every production table in your environment and to be fully integrated across your stack.

IT 52

IT Metadata Data Warehouse BI 52

Monte Carlo

JANUARY 29, 2024

Schema: Did the organization of the dataset change in a way that will break other data operations downstream? By leveraging the metadata made available in Snowflake, Monte Carlo can automatically detect freshness and volume anomalies within days of deployment, without any additional configuration.

Metadata 64

Metadata High Quality Data Data Pipeline Machine Learning 64

Databand.ai

AUGUST 30, 2023

This includes defining roles and responsibilities related to managing datasets and setting guidelines for metadata management. Data profiling: Regularly analyze dataset content to identify inconsistencies or errors. Automated profiling tools can quickly detect anomalies or patterns indicating potential dataset integrity issues.

Building 52

Building Data Cleanse Data Governance Datasets 52

LinkedIn Engineering

JUNE 2, 2023

These requests require interaction with one or more of our datasets, and the timelines can range from a few days to a couple of weeks. LHR is featured in our monthly Workforce Reports Once the publishing process is complete, our metric and the associated datasets are all discoverable via DataHub , our metadata management platform.

Building 75

Building Banking Datasets Media 75

phData: Data Engineering

DECEMBER 16, 2021

When setting your data catalog, it is tempting to leave it with a technical team that can keep the automation running, onboard new datasets, and support upgrades and downtime. The Lead Steward will also be responsible for making sure the metadata is properly defined and agreed on. How will Human-Driven Metadata be Captured?

Metadata 52

Metadata Datasets Data Education 52

Monte Carlo

MARCH 12, 2024

Dataplex works with your metadata. As you add new data sources to your data stores, Dataplex leverages the structured and unstructured metadata with built-in data quality checks to maintain integrity. You can export these results to a BigQuery table, Looker dashboard, or other aggregated report to do a full analysis.

Google Cloud 52

Google Cloud Metadata SQL Data Lake 52

Datakin

AUGUST 5, 2021

Each dataset and job exists in a unique operational context, with interdependencies that may seem simple…until they multiply. Lineage metadata is the thread that connects it all together. However, there is more than one way to capture lineage metadata. When we look into that job, it failed because of yet another failed job.

Metadata 52

Metadata Relational Database Datasets SQL 52

Christophe Blefari

JUNE 16, 2023

The Spanish startup develop a tool where you quickly explore datasets and then build charts or AI models on top of it. Masthead does not run SQL on your data—which generate costs uplift—but reading logs and metadata to identify anomalies. We don't need spaces ( credits ) Data Economy 🤖 Graphext raises $4.6m

Programming Language 130

Programming Language SQL PostgreSQL Data 130

Monte Carlo

APRIL 24, 2023

However, one of the biggest trends in data lake technologies, and a capability to evaluate carefully, is the addition of more structured metadata creating “lakehouse” architecture. If not paired with Glue, or another metastore/catalog solution, S3 will also lack some of the metadata structure required for more advanced data management tasks.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Cloudyard

APRIL 4, 2024

Metadata Management: Stores segmented customer data in the “CUSTOMER_SEGMENTS” table within the Snowflake database for easy access and retrieval for further analysis. Scalability: Handles large datasets efficiently, making it ideal for growing businesses.

Retail 40

Retail Data Ingestion Metadata Datasets 40

Silectis

FEBRUARY 3, 2021

Data lineage refers to the entire lifecycle of a dataset from its sources of origin all the way to its current state. To visualize data lineage, most tools leverage a DAG (directed acyclic graph) interface in which each node represents a dataset, and each edge represents a producer/consumer relationship. What is Data Lineage?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

phData: Data Engineering

SEPTEMBER 19, 2023

Metadata Management Data modeling methodologies help in managing metadata within the data lake. Metadata describes the characteristics, attributes, and context of the data. By incorporating metadata into the data model, users can easily discover, understand, and interpret the data stored in the lake.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Rockset

APRIL 18, 2023

Under the hood, Rockset utilizes its Converged Index technology, which is optimized for metadata filtering, vector search and keyword search, supporting sub-second search, aggregations and joins at scale. Fast Search: Combine vector search and selective metadata filtering to deliver fast, efficient results.

Unstructured Data 105

Unstructured Data Metadata Machine Learning SQL 105

Knowledge Hut

OCTOBER 26, 2023

Data sources you can refer to: Walmart sales forecasting:  the dataset available from the “ Walmart store sales forecasting” project that was available on Kaggle. It includes the UCI machine learning repository and dataset. It contains weekly sales data for more than 40+ stores and 99 departments over a 3 - year period.

Machine Learning 52

Machine Learning Project Datasets Algorithm 52

Monte Carlo

DECEMBER 20, 2023

Tomasz predicts that since most workloads are small, data teams will begin to use in-process and in-memory/in-process databases to analyze and move datasets. Low-impact approaches like metadata monitoring and tools that allow teams to see and right-size utilization will be invaluable in 2024 9.

Amazon Web Services 52

Amazon Web Services Metadata AWS Data 52

Monte Carlo

DECEMBER 20, 2023

Tomasz predicts that since most workloads are small, data teams will begin to use in-process and in-memory/in-process databases to analyze and move datasets. Low-impact approaches like metadata monitoring and tools that allow teams to see and right-size utilization will be invaluable in 2024 9.

Amazon Web Services 52

Amazon Web Services Metadata AWS Data 52

Data Engineering Podcast

FEBRUARY 3, 2019

Datasets need to come from research projects that meet the normal standards of professional conduct (laws, ethics, professional norms) articulated by archaeology’s professional societies. Another issues is that it will take a long time to publish enough data to power many "meta-analyses" that draw upon many datasets.

Digital Media 100

Digital Media Media PostgreSQL Datasets 100

phData: Data Engineering

DECEMBER 16, 2021

Where is your metadata stored? You can determine which datasets are popular and might be a good candidate to transition to the data catalog right away. Once Alation is being used to curate metadata, machine learning pattern recognition is used to determine usage patterns inside the catalog itself.

Metadata 52

Metadata Datasets ETL Tools Cloud 52

Precisely

MAY 31, 2023

Shared Business and Technical Metadata As IT landscapes grow larger and more complex, organizations struggle to gain a holistic understanding of where data comes from, how it’s used, and which data is most critical to the business. The Data Integrity Suite’s Data Catalog of business and technical metadata connects all Suite services.

Data Integration 52

Data Integration Metadata Data Governance Data 52

Monte Carlo

OCTOBER 5, 2023

Data cleansing is the process of identifying and correcting or removing inaccurate records from the dataset, improving the data quality. increased vigilance in maintaining thorough documentation and metadata. This way you can identify inconsistencies, errors, and missing values that need to be addressed.

Data Cleanse 52

Data Cleanse ETL Tools Datasets High Quality Data 52

AltexSoft

AUGUST 29, 2023

Such an object storage model allows metadata tagging and incorporating unique identifiers, streamlining data retrieval and enhancing performance. Tools like Apache Atlas or Collibra can add this governance layer, enabling robust policy management and metadata tagging (contextual information about the stored data).

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52