Data Engineering Podcast

APRIL 22, 2018

Summary The information about how data is acquired and processed is often as important as the data itself. For this reason metadata management systems are built to track the journey of your business data to aid in analysis, presentation, and compliance. What is involved in deploying your metadata collection agents?

Business Intelligence 113

Business Intelligence Metadata Management Data Governance 113

Precisely

MAY 13, 2024

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. A notable capability that achieves this is the data catalog. If so, how do you combine that metadata with other data across the enterprise? #4.

Data Integration 52

Data Integration Metadata Amazon Web Services Data Governance 52

Cloudera

APRIL 18, 2024

In those discussions, it was clear that everyone understood the need to treat data estates more cohesively as a whole—that means bringing more attention to security, data governance, and metadata management, the latter of which has become increasingly popular.

Metadata 105

Metadata Government Data Governance Data 105

Knowledge Hut

MARCH 7, 2024

Two, it creates a commonality of data definitions, concepts, metadata and the like. The traditional data management and data warehouses, and the sequence of data transformation, extraction and migration- all arise a situation in which there are risks for data to become unsynchronized.

Big Data 98

Big Data Bytes Data Governance Raw Data 98

Data Science Blog: Data Engineering

MAY 20, 2024

Saving time allows them to focus on their core job function – getting the insight out of the data and helping businesses make better decisions. Enter AnalyticsCreator AnalyticsCreator, a powerful tool for data management, brings a new level of efficiency and reliability to the CI/CD process.

Data Pipeline 52

Data Pipeline BI Data Lake Data Warehouse 52

Databand.ai

JULY 19, 2023

Data lineage tools are not a new concept. However, their importance has grown significantly in recent years due to the increasing complexity of data architectures and the growing need for data governance and compliance. In this article: Why Are Data Lineage Tools Important?

Pipeline-centric 52

Pipeline-centric Data Governance Metadata Government 52

Data Engineering Podcast

JUNE 5, 2022

In this episode Sean Falconer explains the idea of a data privacy vault and how this new architectural element can drastically reduce the potential for making a mistake with how you manage regulated or personally identifiable information. Atlan is the metadata hub for your data ecosystem.

Data Security 100

Data Security Metadata MongoDB Scala 100

Data Engineering Podcast

JULY 10, 2022

They also discuss how they have established a guild system for training and supporting data professionals in the organization. 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.

Metadata 100

Metadata MongoDB MySQL Data Pipeline 100

Snowflake

APRIL 29, 2024

The Snowflake Data Cloud can be a valuable tool for FEs to achieve compliance with DORA and strengthen their overall operational resilience through robust security and advanced data management capabilities. This prioritizes security measures and simplifies data discovery.

Transportation 85

Transportation Data Governance Government Consulting 85

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. This may include tasks such as data profiling, data cleansing, and metadata management.

Building 52

Building Data Cleanse Data Governance Datasets 52

Monte Carlo

FEBRUARY 21, 2023

Enter data fabric: a data management architecture designed to serve the needs of the business, not just those of data engineers. A data fabric is an architecture and associated data products that provide consistent capabilities across a variety of endpoints spanning multiple cloud environments.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Monte Carlo

FEBRUARY 21, 2023

Enter data fabric: a data management architecture designed to serve the needs of the business, not just those of data engineers. A data fabric is an architecture and associated data products that provide consistent capabilities across a variety of endpoints spanning multiple cloud environments.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

The Modern Data Company

APRIL 15, 2024

Understands how different pieces of data (books) relate to each other, helping users find related information. Keeps the library orderly, adjusting as new data arrives. Tracks key performance indicators to understand the use and value of the data. Manages information about data access and monitors data quality.

Government 52

Government Metadata Data Data Lake 52

phData: Data Engineering

SEPTEMBER 19, 2023

With many data modeling methodologies and processes available, choosing the right approach can be daunting. This blog will guide you through the best data modeling methodologies and processes for your data lake, helping you make informed decisions and optimize your data management practices. What is a Data Lake?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Precisely

JUNE 6, 2023

Tendü Yogurtçu offered that organizations today are viewing data as a product, and they are working to streamline access to both data and metadata for faster insights that help business users deliver tangible value. Data observability also helps users identify the root cause of problem in the data.

Data Architecture 52

Data Architecture Architecture Metadata 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. also as a data observability platform, but done differently. This is where you should use pre-commit and SQLFluff.

Programming Language 130

Programming Language SQL PostgreSQL Data 130

Precisely

MAY 31, 2023

Data Integrity Processes Run Where Data Lives Traditional data management solutions have required that data be brought to where the tools run. As a result, organizations have had to bring copies of their data to the tools – one copy for data quality, one copy for data governance, and so on.

Data Integration 52

Data Integration Metadata Data Governance Data 52

Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

AltexSoft

FEBRUARY 11, 2023

Data architecture is the organization and design of how data is collected, transformed, integrated, stored, and used by a company. Bad data management be like, Source: Makeameme Data architects are sometimes confused with other roles inside the data science team.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Precisely

SEPTEMBER 11, 2023

By 2025, 80% of mainstream data quality vendors will expand their product capabilities to provide greater data insights by discovering patterns, trends, data relationships, and error resolution. Context-based bots expedite information retrieval from documentation, knowledge bases, or metadata.

Metadata 52

Metadata Data Integration Datasets Data Analysis Tools 52

Data Engineering Podcast

APRIL 5, 2021

She explains how the design of the platform is informed by the needs of managing data projects for large and small teams across her previous roles, how it integrates with your existing systems, and how it can work to bring everyone onto the same page. What portions of the data workflow is Atlan responsible for?

Data Warehouse 100

Data Warehouse Data Pipeline BI Metadata 100

Data Engineering Podcast

JUNE 19, 2022

Summary Metadata is the lifeblood of your data platform, providing information about what is happening in your systems. In order to level up their value a new trend of active metadata is being implemented, allowing use cases like keeping BI reports up to date, auto-scaling your warehouses, and automated data governance.

Metadata 130

Metadata MongoDB Scala MySQL 130

Data Engineering Podcast

NOVEMBER 9, 2020

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. If you hand a book to a new data engineer, what wisdom would you add to it? If you hand a book to a new data engineer, what wisdom would you add to it?

Building 100

Building PostgreSQL BI Metadata 100

Data Engineering Podcast

SEPTEMBER 23, 2018

He also explains which layers are useful for the different members of the business, and which pitfalls to look out for along the path to a mature and flexible data platform. How do you define data curation? How does the size and maturity of a company affect the ways that they architect and interact with their data systems?

Data Lake 100

Data Lake Data Warehouse Data Architecture Architecture 100

Monte Carlo

APRIL 24, 2023

Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption. Databricks Data Catalog and AWS Lake Formation are examples in this vein. AWS is one of the most popular data lake vendors.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Monte Carlo

JULY 13, 2023

In this article, we will explore how automation can help data engineering teams overcome these challenges and provide a more seamless and effective data management process. Automating and centralizing auditing and monitoring provides a level of visibility and understanding across all data stores. Image courtesy of Satori.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

AltexSoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works. Data lake on AWS.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

DataKitchen

JANUARY 5, 2021

The data teams share a common objective; to create analytics for the (internal or external) customer. Execution of this mission requires the contribution of several groups: data center/IT, data engineering, data science, data visualization, and data governance.

Data Governance 59

Data Governance Government Metadata Data Science 59

phData: Data Engineering

DECEMBER 16, 2021

As a result, it is important to know what is happening to your data. Is your data just being scanned, or is it being moved? Where is your metadata stored? How easy is it to offboard your data if you choose another tool? It can let the user know about the quality and age of the data as well as any policies attached to it.

Metadata 52

Metadata Datasets ETL Tools Cloud 52

Cloudera

FEBRUARY 16, 2022

Within the CML data service, model lineage is managed and tracked at a project level by the SDX. SDX provides open metadata management and governance across each deployed environment by allowing organisations to catalogue, classify as well as control access to and manage all data assets.

Machine Learning 81

Machine Learning Algorithm Government Metadata 81

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. What is data governance? billion in 2020 to $5.28

Data Governance 52

Data Governance Government Healthcare Programming 52

The Modern Data Company

MARCH 7, 2023

Data governance can be a powerful agent in scaling the use and distribution of trusted data throughout the company. If you missed it, make sure to catch up on Part 1 – Data Timeliness. What Is Data Taxonomy? Data that is properly classified, catalogued, and tagged is usually well-governed data.

Data Governance 52

Data Governance Government Metadata Datasets 52

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

Cloudera

NOVEMBER 10, 2021

The main difference in Impala is the caching of Sentry metadata (privileges) by Impala Catalog server. Apache Ranger enables authorization as a part of Shared Data Experience (SDX), which is the fundamental part of Cloudera Data Platform architecture and is critical for data management and data governance.

Hadoop 74

Hadoop SQL Database Kafka 74

Precisely

MAY 23, 2024

Integrated data catalog for metadata support As you build out your IT ecosystem, it is important to leverage tools that have the capabilities to support forward-looking use cases. A notable capability that achieves this is the data catalog.

Data Integration 52

Data Integration Metadata Telecommunication Data Governance 52

dbt Developer Hub

JULY 2, 2023

How to get started with dbt Cloud and Data Vault ​ There are many decisions to make before you roll up your sleeves and start implementing your Data Vault data warehouse. We at Infinite Lambda treat data quality very seriously and we push for high test coverage as well as overall data governance in every project.

Cloud 52

Cloud Data Warehouse Data BI 52

Snowflake

NOVEMBER 29, 2023

While the former can be solved by tokenization strategies provided by external vendors, the latter mandates the need for patient-level data enrichment to be performed with sufficient guardrails to protect patient privacy, with an emphasis on auditability and lineage tracking. The principles emphasize machine-actionability (i.e.,

Metadata 84

Metadata Healthcare Medical Data Storage 84