erwin

NOVEMBER 6, 2019

In most companies, an incredible amount of data flows from multiple sources in a variety of formats and is constantly being moved and federated across a changing system landscape. And this time, you guessed it – we’re focusing on data automation and how it could impact metadata management and data governance.

Metadata 102

Metadata Data Governance Management Cost-Benefit 102

Octopai

JUNE 26, 2020

In order to figure out why the numbers in the two reports didn’t match, Steve needed to understand everything about the data that made up those reports – when the report was created, who created it, any changes made to it, which system it was created in, etc. Enterprise data governance. Metadata in data governance.

Metadata 84

Metadata Data Governance Enterprise Reporting 84

Octopai

JANUARY 31, 2022

If you’re a mystery lover, I’m sure you’ve read that classic tale: Sherlock Holmes and the Case of the Deceptive Data, and you know how a metadata catalog was a key plot element. In The Case of the Deceptive Data, Holmes is approached by B.I. He goes on to explain: Reasons for inaccurate data. Big data is BIG.

Metadata 77

Metadata IT Unstructured Data IoT 77

AWS Big Data

APRIL 17, 2024

In this post, we discuss how the reimagined data flow works with OR1 instances and how it can provide high indexing throughput and durability using a new physical replication protocol. We also dive deep into some of the challenges we solved to maintain correctness and data integrity.

Optimization 112

Optimization Snapshot Metadata Cost-Benefit 112

AWS Big Data

FEBRUARY 6, 2023

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning (ML), and application development. MongoDB Atlas is a developer data service from AWS technology partner MongoDB, Inc.

Metadata 73

Metadata Data Lake Machine Learning Management 73

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

Ontotext

JANUARY 10, 2024

And each of these gains requires data integration across business lines and divisions. Limiting growth by (data integration) complexity Most operational IT systems in an enterprise have been developed to serve a single business function and they use the simplest possible model for this. We call this the Bad Data Tax.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

Ontotext

APRIL 10, 2024

In most enterprises data teams lack a data map and data asset inventory and are often unaware of data that exists across the organization, its associated profile, quality and associated metadata. Teams can’t access data to build their business use cases. For example, a product data tag is basic metadata.

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

AWS Big Data

APRIL 3, 2024

Data engineers use Apache Iceberg because it’s fast, efficient, and reliable at any scale and keeps records of how datasets change over time. Apache Iceberg offers integrations with popular data processing frameworks such as Apache Spark, Apache Flink, Apache Hive, Presto, and more.

Data Lake 93

Data Lake Snapshot Metadata Data Architecture 93

Ontotext

AUGUST 22, 2023

Context: The Key to Making Data Useful It goes without saying that data without meaning can yield incorrect insights, leading to potentially dangerous decisions. Beyond that, and without a way to visualize, connect, and utilize the data, it’s still just a bunch of random information.

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. This can save time.

Data Lake 100

Data Lake Metadata Snapshot Recreation/Entertainment 100

AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 86

Metadata Data Lake Visualization Data Transformation 86

Octopai

SEPTEMBER 27, 2023

Octopai’s real-time capabilities provide a transparent, up-to-the-moment view of data integrations across platforms like Airflow, Azure Data Factory, Snowflake, Redshift, and Azure Synapse. Instead, it’s an intuitive journey where every step of data is transparent and trustworthy.

Metadata 52

Metadata Visualization Data Integration Data-driven 52

Ontotext

JUNE 27, 2019

Ontotext’s GraphDB is an enterprise-ready semantic graph database (also called RDF triplestore as it stores data in RDF triples). It provides the core infrastructure for solutions where modeling agility, data integration, relationship exploration, cross-enterprise data publishing and consumption are critical.

Metadata 40

Metadata Management Enterprise Optimization 40

Ontotext

AUGUST 4, 2023

A data fabric utilizes an integrated data layer over existing, discoverable, and inferenced metadata assets to support the design, deployment, and utilization of data across enterprises, including hybrid and multi-cloud platforms. It also helps capture and connect data based on business or domains.

Metadata 52

Metadata Data-driven Data Architecture Data Quality 52

AWS Big Data

SEPTEMBER 7, 2023

We will partition and format the server access logs with Amazon Web Services (AWS) Glue , a serverless data integration service, to generate a catalog for access logs and create dashboards for insights. Both the user data and logs buckets must be in the same AWS Region and owned by the same account.

Metadata 98

Metadata Dashboards Metrics Visualization 98

Rocket-Powered Data Science

JULY 6, 2021

This is accomplished through tags, annotations, and metadata (TAM). granules) of the data collection for fast search, access, and retrieval is also important for efficient orchestration and delivery of the data that fuels AI, automation, and machine learning operations. Collect, curate, and catalog (i.e.,

Strategy 266

Strategy Machine Learning Metadata Knowledge Discovery 266

DataKitchen

OCTOBER 20, 2023

Example 2: The Data Engineering Team Has Many Small, Valuable Files Where They Need Individual Source File Tracking In a typical data processing workflow, tracking individual files as they progress through various stages—from file delivery to data ingestion—is crucial.

Insurance 176

Insurance Metadata Data-driven Data Quality 176

CIO Business Intelligence

MARCH 24, 2023

The program must introduce and support standardization of enterprise data. Programs must support proactive and reactive change management activities for reference data values and the structure/use of master data and metadata.

Data Governance 142

Data Governance Management Metadata Data Quality 142

Jen Stirrup

MARCH 29, 2023

However, to turn data into a business problem, organizations need support to move away from technical issues to start getting value as quickly as possible. SAP Datasphere simplifies data integration, cataloging, semantic modeling, warehousing, federation, and virtualization through a unified interface. Why is this interesting?

Metadata 120

Metadata Data Warehouse Data Integration Business Intelligence 120

Alation

DECEMBER 6, 2022

Diby Malakar joins as our new Vice President of Product Management, Cloud & Technical Metadata Platform and Jonathan Bruce is our new Vice President of Product Management, Catalog, Governance & Data Exploration Apps & Logical Metadata Platform. Oversee the connectors and lineage product areas.

Metadata 52

Metadata Enterprise Data Integration Data Quality 52

erwin

JANUARY 9, 2020

That’s because it’s the best way to visualize metadata , and metadata is now the heart of enterprise data management and data governance/ intelligence efforts. So here’s why data modeling is so critical to data governance. erwin Data Modeler: Where the Magic Happens.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

Ontotext

FEBRUARY 7, 2024

However, what we usually don’t talk about when generating an asset, are the huge invisible or unplanned costs occurring at a later stage when the data needs to be made available for analysis or secondary usage. As a result, a big portion of the IT capacity in Pharma is bound by data integration.

Metadata 52

Metadata Data Integration Measurement Data-driven 52

CIO Business Intelligence

MARCH 4, 2024

This is where data fabric tools with their focus on orchestration, contextual layering, and metadata management are important elements to add to the equation. Data fabric introduces an intelligent semantic layer that orchestrates disparate data sources, applications, and services into a unified and easily accessible framework.

Insurance 85

Insurance Strategy Data Governance Data Integration 85

AWS Big Data

FEBRUARY 29, 2024

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. Data discoverability Unlike structured data, which is managed in well-defined rows and columns, unstructured data is stored as objects.

Data Governance 93

Data Governance Unstructured Data Metadata Data Lake 93

Smart Data Collective

JULY 15, 2021

A data catalog serves the same purpose. By using metadata (or short descriptions), data catalogs help companies gather, organize, retrieve, and manage information. You can think of a data catalog as an enhanced Access database or library card catalog system. What Does a Data Catalog Consist Of?

Metadata 126

Metadata IT Data-driven Data Quality 126

Ontotext

DECEMBER 1, 2023

So, KGF 2023 proved to be a breath of fresh air for anyone interested in topics like data mesh and data fabric , knowledge graphs, text analysis , large language model (LLM) integrations, retrieval augmented generation (RAG), chatbots, semantic data integration , and ontology building.

Metadata 78

Metadata Sales Consulting Enterprise 78

Octopai

FEBRUARY 26, 2024

A Strategic Approach to Data Cleansing With Octopai’s automated data lineage, data cleansing transcends its traditional role, becoming a strategic endeavor that drives efficiency, ensures data integrity, and unlocks business insights.

Metadata 52

Metadata ROI Optimization Data-driven 52

Smarten

JANUARY 30, 2024

Business users cannot even hope to prepare data for analytics – at least not without the right tools. Gartner predicts that, ‘data preparation will be utilized in more than 70% of new data integration projects for analytics and data science.’ So, why is there so much attention paid to the task of data preparation?

Analytics 67

Analytics Data Quality Visualization Metadata 67

erwin

OCTOBER 8, 2020

These tools range from enterprise service bus (ESB) products, data integration tools; extract, transform and load (ETL) tools, procedural code, application program interfaces (APIs), file transfer protocol (FTP) processes, and even business intelligence (BI) reports that further aggregate and transform data.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

O'Reilly on Data

JANUARY 29, 2019

These include data integration and extract, transform, and load (ETL) (60% of respondents indicated they were building or evaluating solutions), data preparation and cleaning (52%), data governance (31%), metadata analysis and management (28%), and data lineage management (21%).

Deep Learning 208

Deep Learning Machine Learning Data Science Metadata 208

erwin

MAY 13, 2020

The role of data modeling (DM) has expanded to support enterprise data management, including data governance and intelligence efforts. Metadata management is the key to managing and governing your data and drawing intelligence from it. Types of Data Models: Conceptual, Logical and Physical.

Data Governance 93

Data Governance Modeling Enterprise Management 93

Ontotext

MARCH 23, 2023

At the same time, there are more demands for data to be used in real-time and for businesses to have a better understanding of it. In addition, there is a growing trend of automating data integration and management processes. All this makes it difficult to navigate the enterprise data landscape and stay ahead of the competition.

Management 52

Management Metadata Unstructured Data Data Integration 52

IBM Big Data Hub

JULY 6, 2022

With traditional approaches , data issues are reported by data users as they try to access and use the data and may take weeks to fix, if they’re found at all. starts at the data source, collecting data pipeline metadata across key solutions in the modern data stack like Airflow, dbt, Databricks and many more.

Metadata 57

Metadata Data Quality Snapshot Cost-Benefit 57

Ontotext

MARCH 27, 2024

For example, GPS, social media, cell phone handoffs are modeled as graphs while data catalogs, data lineage and MDM tools leverage knowledge graphs for linking metadata with semantics. This verbosity allows schema, metadata, and instance data to be in one place, enabling accessibility and manageability.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

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 91

Data Lake Snapshot Metadata Optimization 91

Ontotext

JULY 29, 2021

KGs bring the Semantic Web paradigm to the enterprises, by introducing semantic metadata to drive data management and content management to new levels of efficiency and breaking silos to let them synergize with various forms of knowledge management. The RDF data model and the other standards in W3C’s Semantic Web stack (e.g.,

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124