Monte Carlo

AUGUST 25, 2023

One advantage of data warehouses is their integrated nature. As fully managed solutions, data warehouses are designed to offer ease of construction and operation. A warehouse can be a one-stop solution, where metadata, storage, and compute components come from the same place and are under the orchestration of a single vendor.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

François Nguyen

JANUARY 18, 2021

To finish the trilogy (Dataops, MLops), let’s talk about DataGovOps or how you can support your Data Governance initiative. In every step,we do not just read, transform and write data, we are also doing that with the metadata. Last part, it was added the data security and privacy part.

Data Governance 130

Data Governance Metadata Government Data Pipeline 130

Monte Carlo

JULY 10, 2023

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. That’s where the definition of data completeness comes in. Be sure to use random sampling to select representative subsets of your data.

Data Collection 40

Data Collection Data Governance Government Data 40

Monte Carlo

AUGUST 30, 2023

Your test passes when there are no rows returned, which indicates your data meets your defined conditions. Also, remember data governance. Stored test failure data should adhere to your relevant policies or regulations, including data privacy and security, and is only made accessible to the appropriate team members.

SQL 52

SQL Datasets Database High Quality Data 52

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. How do we build data products ? How can we interoperate between the data domains ? This is really for us the definition of a self serve platform. What you have to code is this workflow !

Architecture 130

Architecture Technology Google Cloud Metadata 130

ThoughtSpot

OCTOBER 9, 2023

How ThoughtSpot builds trust with data catalog connectors For many, the data catalog is still the primary home for metadata enrichment and governance. Think: data descriptions, data quality markers, business owners, etc. Set how often you want the metadata to sync from Alation to ThoughtSpot.

Metadata 83

Metadata Government Data Data Governance 83

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

RandomTrees

FEBRUARY 6, 2024

Transformation: Shaping Data for the Future: LLMs facilitate standardizing date formats with precision and translation of complex organizational structures into logical database designs, streamline the definition of business rules, automate data cleansing, and propose the inclusion of external data for a more complete analytical view.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Christophe Blefari

JUNE 16, 2023

The power of pre-commit and SQLFluff —SQL is a query programming language used to retrieve information from data storages, and like any other programming language, you need to enforce checks at all times. Cube announcements ; Data Graph and Orchestration API — This is 2 announcement from Cube.

Programming Language 130

Programming Language SQL PostgreSQL Data 130

Monte Carlo

FEBRUARY 26, 2024

A data catalog is a constantly updated inventory of the universe of data assets within an organization. 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.

Metadata 52

Metadata Government Data Data Governance 52

The Modern Data Company

MARCH 1, 2024

Instead of forcing all data through a centralized bottleneck, they break it down into modular, self-contained units. 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.

Database-centric 40

Database-centric Data Lake Government Retail 40

Cloudera

JUNE 7, 2023

By now, almost everyone across the tech landscape has heard of the Zero Trust (ZT) security model, which assumes that every device, application, or user attempting to access a network is not to be trusted (see NIST definitions below). Cloudera Shared Data Experience (SDX) is a core component of Cloudera Data Platform’s architecture.

Government 79

Government Metadata Data Lake Data 79

Databand.ai

AUGUST 30, 2023

Finally, you should analyze the results of your data performance tests and implement any necessary improvements to your data processing systems and infrastructure. Metadata is data about data, such as data definitions, data lineage, and data quality rules, that helps organizations understand and manage their data more effectively.

Data Cleanse 52

Data Cleanse Metadata High Quality Data Datasets 52

François Nguyen

MARCH 7, 2021

In this article, Juan Sequada gives maybe one of the best definition of Data Mesh ” It is paradigm shift towards a distributed architecture that attempts to find an ideal balance between centralization and decentralization of metadata and data management.”

Government 130

Government Data Governance Data Metadata 130

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

DataKitchen

FEBRUARY 2, 2023

A combined, interoperable suite of tools for data team productivity, governance, and security for large and small data teams. And the tools for acting on data are consolidating: Tableau does data prep, Altreyx does data science, Qlik joined with Talend, etc. Can that be done with minimal vendor tools?

Metadata 52

Metadata BI Government ETL Tools 52

Ascend.io

JULY 19, 2023

Process: Building Robust Systems from Data Governance to Product Publishing Just as a well-oiled machine needs precise processes, a successful data mesh needs to establish and adhere to processes regarding data governance, data curation, and data product publishing. Promote cross-domain collaboration.

Data Governance 40

Data Governance Government Metadata Data 40

Monte Carlo

DECEMBER 8, 2023

Enter: data provenance and data lineage. 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.

Metadata 52

Metadata Data Data Warehouse Government 52

Monte Carlo

DECEMBER 8, 2023

Enter: data provenance and data lineage. 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.

Metadata 52

Metadata Data Data Warehouse Government 52

Cloudera

AUGUST 3, 2021

Advanced analytics and enterprise data are empowering several overarching initiatives in supply chain risk reduction – improved visibility and transparency into all aspects of the supply chain balanced with data governance and security. . Improve Visibility within Supply Chains.

Manufacturing 108

Manufacturing Retail Entertainment Government 108

phData: Data Engineering

DECEMBER 16, 2021

While these people are extremely important, establishing a well-balanced team is key to leveraging your data catalog to its fullest potential. We will explore the various actors that can usually be found in a data governance program that could also support your data catalog. How will Human-Driven Metadata be Captured?

Metadata 52

Metadata Datasets Data Education 52

Monte Carlo

MARCH 16, 2023

How do we instill the sense of quality and timeliness in the data?” As a startup, Best Egg had been focused on proving its business model, not establishing organization-wide data governance. Establish a data governance council to drive consensus Get those key stakeholders involved in a data governance council, Randy advises.

Software Engineer 52

Software Engineer Software Engineering Data Governance Government 52

Data Engineering Podcast

NOVEMBER 9, 2020

In this episode Grant Seward explains how he built Tree Schema to be an easy to use and cost effective option for organizations to build their data catalogs. He also shares the internal architecture, how he approached the design to make it accessible and easy to use, and how it autodiscovers the schemas and metadata for your source systems.

Building 100

Building PostgreSQL BI Metadata 100

Monte Carlo

SEPTEMBER 12, 2022

2) Open-source will increasingly infiltrate the data stack While open source isn’t a new trend, it’s definitely an accelerating one. So Maxime predicts that more organizations will do away with the BI-specific semantics altogether, in favor of containing this metadata within the transform layer.

BI 52

BI Data Governance ETL Tools Data Warehouse 52

Monte Carlo

JANUARY 23, 2024

It’s harder to gain consensus on governance – and that’s OK In a previous era of data engineering, data team structure was very much centralized, with data engineers and tech-savvy analysts serving as the “librarians” of the data for the entire company. At least, that’s what we see in our crystal ball.

Data Engineering 98

Data Engineering Data Engineer Engineering Data 98

Precisely

DECEMBER 8, 2023

As you strive to achieve higher levels of data integrity, data governance becomes imperative. What is Data Governance? Robert Seiner, author of Non-Invasive Data Governance and founder of KIK Consulting, defines data governance as “the execution and enforcement of authority over data.”

Data Governance 69

Data Governance Government Datasets Programming 69

Cloudera

SEPTEMBER 15, 2022

What is a data fabric? Mark: Gartner states that a data fabric “enables frictionless access and sharing of data in a distributed data environment.” The data fabric provides direct support for the first element of the architecture — linking the distributed source data into the hybrid, multi-cloud environment. .

Data Lake 79

Data Lake Analytics Application Cloud Storage Architecture 79

Monte Carlo

MARCH 16, 2023

How do we instill the sense of quality and timeliness in the data?” As a startup, Best Egg had been focused on proving its business model, not establishing organization-wide data governance. Establish a data governance council to drive consensus Get those key stakeholders involved in a data governance council, Randy advises.

Software Engineer 40

Software Engineer Software Engineering Data Governance Government 40

Monte Carlo

DECEMBER 20, 2023

Data observability adds the ability to monitor metadata and logs from the data systems across your stack for full visibility into anomalous behavior. The good news is data observability doesn’t have to be an all or nothing proposition. A good place to start is to consider your data products.

Architecture 40

Architecture Data Datasets Machine Learning 40

Monte Carlo

JANUARY 23, 2023

Data lineage , an automated visualization of the relationships for how data flows across tables and other data assets, is a must-have in the data engineering toolbox. Not only is it helpful for data governance and compliance use cases, it also plays a starring role as one of the 5 pillars of data observability.

IT 52

IT BI Government Data Governance 52

AltexSoft

MARCH 2, 2023

As the amount of enterprise data continues to surge, businesses are increasingly recognizing the importance of data governance — the framework for managing an organization’s data assets for accuracy, consistency, security, and effective use. Projections show that the data governance market will expand from $1.81

Data Governance 52

Data Governance Government Healthcare Programming 52

Monte Carlo

JULY 30, 2020

It does not have the same emphasis on decentralization and domain driven architecture as data mesh. Instead of reinventing Zhamak’s very thoughtfully built wheel, we’ll boil down the definition of a data mesh to a few key concepts and highlight how it differs from traditional data architectures. Data governance.

IT 45

IT Data Lake Business Intelligence Data Architecture 45

Monte Carlo

MAY 17, 2023

Many times this is by freeing them from having to manually implement and maintain hundreds of data tests as was the case with Contentsquare and Gitlab. “We We had too many manual data checks by operations and data analysts,” said Otávio Bastos, former global data governance lead, Contentsquare. “It

Data 52

Data Data Pipeline Data Engineering Data Engineer 52

Monte Carlo

MAY 17, 2023

Many times this is by freeing them from having to manually implement and maintain hundreds of data tests as was the case with Contentsquare and Gitlab. “We We had too many manual data checks by operations and data analysts,” said Otávio Bastos, former global data governance lead, Contentsquare. “It

Data Pipeline 52

Data Pipeline Data Data Engineering Data Engineer 52

ProjectPro

NOVEMBER 30, 2021

If you are into Data Science or Big Data, you must be familiar with an ETL pipeline. 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. Stage Data Data that has been transformed is stored in this layer.

Process 52

Process Data Pipeline Data Warehouse AWS 52

AltexSoft

AUGUST 22, 2022

Support for different data types and use cases. A data fabric supports structured, unstructured, and semi-structured data whether it comes in real-time or generated in batches. It is also driven by metadata, which it uses to recognize patterns, map data, and perform continuous analysis. How data fabric works.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

AltexSoft

JUNE 26, 2023

External or third-party data sources, on the other hand, deal with outside information, which comes from partners, competitors, social media, general market studies, databases with publicly available datasets , etc. Our experience shows that you definitely need both internal and external data to make accurate forecasts.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52