Alation

FEBRUARY 13, 2020

In an earlier blog, I defined a data catalog as “a collection of metadata, combined with data management and search tools, that helps analysts and other data users to find the data that they need, serves as an inventory of available data, and provides information to evaluate fitness data for intended uses.”.

Metadata 52

Metadata Management Data Lake Data Governance 52

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

AWS Big Data

MARCH 22, 2024

Benchmark setup In our testing, we used the 3 TB dataset stored in Amazon S3 in compressed Parquet format and metadata for databases and tables is stored in the AWS Glue Data Catalog. This benchmark uses unmodified TPC-DS data schema and table relationships. As shown in this blog post, our TPC-DS benchmark showed a 2.7

Metadata 86

Metadata Statistics Broadcasting Optimization 86

Octopai

JANUARY 31, 2021

We have identified the top ten sites, videos, or podcasts online that deal with data lineage. Our list of Top 10 Data Lineage Podcasts, Blogs, and Websites To Follow in 2021. Data Engineering Podcast. This podcast centers around data management and investigates a different aspect of this field each week.

Data Governance 57

Data Governance Data Processing Data Quality Metadata 57

TDAN

MAY 17, 2022

There is… but one… Data Governance. Maybe you are one who believes that there is something called Master Data Governance, Information Governance, Metadata Governance, Big Data Governance, Customer [or insert domain name here] Data Governance, Data Governance 1.0 – 2.0 – 3.0,

Data Governance 98

Data Governance Metadata Big Data Data Strategy 98

erwin

DECEMBER 20, 2018

So with the impetus of the General Data Protection Regulation (GDPR) and the opportunities presented by data-driven transformation, many organizations are re-evaluating their data management and data governance practices. Defining Data Governance. www.erwin.com/blog/defining-data-governance/.

Data Governance 40

Data Governance ROI Risk Management Metadata 40

Ontotext

AUGUST 22, 2023

The age of Big Data inevitably brought computationally intensive problems to the enterprise. Central to today’s efficient business operations are the activities of data capturing and storage, search, sharing, and data analytics. As a result, organizations have spent untold money and time gathering and integrating data.

Metadata 52

Metadata Knowledge Discovery Big Data Enterprise 52

AWS Big Data

OCTOBER 3, 2023

In-place data upgrade In an in-place data migration strategy, existing datasets are upgraded to Apache Iceberg format without first reprocessing or restating existing data. In this method, the metadata are recreated in an isolated environment and colocated with the existing data files.

Data Lake 98

Data Lake Metadata Snapshot Recreation/Entertainment 98

AWS Big Data

MARCH 2, 2023

Apache Iceberg is an open table format for very large analytic datasets, which captures metadata information on the state of datasets as they evolve and change over time. Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback.

Data Lake 114

Data Lake Data Processing Metadata Snapshot 114

AWS Big Data

SEPTEMBER 7, 2023

Customers want to know how their data is being accessed, when it is being accessed, and who is accessing it. With exponential growth in data volume, centralized monitoring becomes challenging. It is also crucial to audit granular data access for security and compliance needs. Big Data Architect.

Metadata 95

Metadata Dashboards Metrics Visualization 95

AWS Big Data

NOVEMBER 15, 2023

As the organization receives data from multiple external vendors, it often arrives in different formats, typically Excel or CSV files, with each vendor using their own unique data layout and structure. In this blog post, we’ll explore a solution that streamlines this process by leveraging the capabilities of AWS Glue DataBrew.

Metadata 80

Metadata Sales Data Lake Big Data 80

AWS Big Data

NOVEMBER 22, 2023

Many AWS customers adopted Apache Hudi on their data lakes built on top of Amazon S3 using AWS Glue , a serverless data integration service that makes it easier to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning (ML), and application development.

Data Lake 89

Data Lake Snapshot Metadata Optimization 89

AWS Big Data

JUNE 15, 2023

AWS Glue crawlers provide a straightforward way to catalog data in the AWS Glue Data Catalog that removes the heavy lifting when it comes to schema management and data classification. AWS Glue crawlers extract the data schema and partitions from Amazon S3 to automatically populate the Data Catalog, keeping the metadata current.

Data Lake 84

Data Lake Metadata Cost-Benefit Management 84

AWS Big Data

JUNE 2, 2023

It starts with setting up the migration configuration to connect to Google BigQuery, then converts the database schemas, and finally migrates the data to Amazon Redshift. This JSON file contains the migration metadata, namely the following: A list of Google BigQuery projects and datasets. Do not change the default.

Metadata 106

Metadata Data Warehouse Big Data Testing 106

AWS Big Data

OCTOBER 3, 2023

In our previous post Improve operational efficiencies of Apache Iceberg tables built on Amazon S3 data lakes , we discussed how you can implement solutions to improve operational efficiencies of your Amazon Simple Storage Service (Amazon S3) data lake that is using the Apache Iceberg open table format and running on the Amazon EMR big data platform.

Optimization 106

Optimization Snapshot Data Lake Metadata 106

Rocket-Powered Data Science

JULY 6, 2021

If you include the title of this blog, you were just presented with 13 examples of heteronyms in the preceding paragraphs. This is accomplished through tags, annotations, and metadata (TAM). Smart content includes labeled (tagged, annotated) metadata (TAM). What you have just experienced is a plethora of heteronyms.

Strategy 266

Strategy Machine Learning Metadata Knowledge Discovery 266

IBM Big Data Hub

OCTOBER 4, 2022

Furthermore, 59% of executives claim AI can improve the use of big data in their organizations, facts about artificial intelligence show. ( This includes capturing of the metadata, tracking provenance and documenting the model lifecycle. The post AI Governance: Break open the black box appeared first on Journey to AI Blog.

Metadata 103

Metadata Risk Risk Management Experimentation 103

AWS Big Data

FEBRUARY 12, 2024

As mentioned in the previous blog, AWS Clean Rooms enables multiple organizations to analyze their data and unlock insights they can act upon, without having to share sensitive, restricted, or proprietary records. When the status changes to SUCCESS, it proceeds to the next step to retrieve the AWS Glue table metadata information.

Publishing 87

Publishing Dashboards Metadata Visualization 87

Alation

FEBRUARY 13, 2020

Why do we need a data catalog? What does a data catalog do? These are all good questions and a logical place to start your data cataloging journey. Data catalogs have become the standard for metadata management in the age of big data and self-service analytics. What is a Data Catalog?

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

erwin

JANUARY 14, 2021

When the pandemic first hit, there was some negative impact on big data and analytics spending. Digital transformation was accelerated, and budgets for spending on big data and analytics increased. Technical metadata is what makes up database schema and table definitions.

Digital Transformation 143

Digital Transformation Metadata Big Data Data-driven 143

AWS Big Data

MAY 24, 2023

Some of the important non-functional use cases for an S3 data lake that organizations are focusing on include storage cost optimizations, capabilities for disaster recovery and business continuity, cross-account and multi-Region access to the data lake, and handling increased Amazon S3 request rates. write.tags.write-tag-name and s3.delete.tags.delete-tag-name

Data Lake 80

Data Lake Snapshot Metadata Optimization 80

CIO Business Intelligence

DECEMBER 13, 2023

Unlike that energy company, many organizations have yet to feel an urgency to capitalize on the value of their vast reservoirs of unstructured data. After all, we in the information management and technology industry have talked at length about unstructured data since “Big Data” was big news more than a decade ago.

Unstructured Data 98

Unstructured Data IoT Metadata Manufacturing 98

Cloudera

AUGUST 26, 2021

This means that there is out of the box support for Ozone storage in services like Apache Hive , Apache Impala, Apache Spark, and Apache Nifi, as well as in Private Cloud experiences like Cloudera Machine Learning (CML) and Data Warehousing Experience (DWX). Data ingestion through ‘s3’. Ozone Namespace Overview.

Data Science 110

Data Science Forecasting Metadata Machine Learning 110

AWS Big Data

OCTOBER 4, 2023

Additionally, data owners and data stewards can make data discovery simpler by adding business context to data while balancing access governance to the data via pre-defined approval workflows in the user interface. The metadata forms types, and asset types can be used as templates for defining your assets.

Metadata 96

Metadata Data Lake Publishing Data Governance 96

AWS Big Data

AUGUST 31, 2023

Iceberg stores the metadata pointer for all the metadata files. When a SELECT query is reading an Iceberg table, the query engine first goes to the Iceberg catalog, then retrieves the entry of the location of the latest metadata file, as shown in the following diagram. In this post, we use Athena to convert the data.

Data Lake 89

Data Lake Data Warehouse Metadata Data Architecture 89

AWS Big Data

APRIL 26, 2023

This is a guest blog post co-written with Corey Johnson from Huron. Having an accurate and up-to-date inventory of all technical assets helps an organization ensure it can keep track of all its resources with metadata information such as their assigned oners, last updated date, used by whom, how frequently and more.

Metadata 52

Metadata Dashboards Visualization Consulting 52

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Cloudera

JUNE 7, 2022

Big data is cool again. As the company who taught the world the value of big data, we always knew it would be. But this is not your grandfather’s big data. It has evolved into something new – hybrid data. We believe that data can make what is impossible today, possible tomorrow.

IT 109

IT Data Architecture Unstructured Data Big Data 109

datapine

SEPTEMBER 29, 2022

With quality data at their disposal, organizations can form data warehouses for the purposes of examining trends and establishing future-facing strategies. Industry-wide, the positive ROI on quality data is well understood. 2 – Data profiling. Data profiling is an essential process in the DQM lifecycle.

Data Quality 241

Data Quality Metrics Data-driven Management 241

IBM Big Data Hub

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

AWS Big Data

FEBRUARY 20, 2024

You can read from all the ingested data files at a specified Amazon S3 location with different schemas through a single Amazon Redshift Spectrum table by referring to the AWS Glue metadata catalog. In this post, we showcased how you can derive metrics from common atomic data elements from different data sources with unique schemas.

IoT 90

IoT Analytics Prescriptive Analytics Internet of Things 90

AWS Big Data

JULY 20, 2023

The Orca Platform is powered by a state-of-the-art anomaly detection system that uses cutting-edge ML algorithms and big data capabilities to detect potential security threats and alert customers in real time, ensuring maximum security for their cloud environment. Why did Orca choose Apache Iceberg?

Data Lake 84

Data Lake Analytics Snapshot Optimization 84

erwin

JANUARY 24, 2019

With an automation framework, data professionals can meet these needs at a fraction of the cost of the traditional manual way. In data governance terms, an automation framework refers to a metadata-driven universal code generator that works hand in hand with enterprise data mapping for: Pre-ETL enterprise data mapping.

Data Governance 71

Data Governance Metadata Data-driven Cost-Benefit 71

Cloudera

JULY 14, 2023

Introduction For more than a decade now, the Hive table format has been a ubiquitous presence in the big data ecosystem, managing petabytes of data with remarkable efficiency and scale. Depending on the size and usage patterns of the data, several different strategies could be pursued to achieve a successful migration.

Snapshot 70

Snapshot Metadata Data Warehouse Testing 70

AWS Big Data

SEPTEMBER 29, 2023

To analyze XML files stored in Amazon S3 using AWS Glue and Athena, we complete the following high-level steps: Create an AWS Glue crawler to extract XML metadata and create a table in the AWS Glue Data Catalog. We use the AWS Glue crawler to extract XML file metadata. Choose Add a data store. Choose Create.

Metadata 65

Metadata Visualization Data-driven Optimization 65

Alation

FEBRUARY 20, 2020

We define it as this: Data acquisition is the processes for bringing data that has been created by a source outside the organization, into the organization, for production use. Prior to the Big Data revolution, companies were inward-looking in terms of data. THE NEED FOR METADATA TOOLS.

Metadata 52

Metadata IT Data Governance Data Warehouse 52

IBM Big Data Hub

JANUARY 3, 2024

Organizations should also offer interpretable metadata to patients that details the accountability and accuracy of that model, the source of the training data for that model and the audit results of that model. The metadata should also show how a user can opt out of using that model (and get the same service elsewhere).

Metadata 81

Metadata Modeling Testing Manufacturing 81