erwin

JANUARY 24, 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. With an automation framework, data professionals can meet these needs at a fraction of the cost of the traditional manual way. Governing metadata.

Data Governance 71

Data Governance Metadata Data-driven Cost-Benefit 71

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

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

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 56

Metadata Data Quality Snapshot Cost-Benefit 56

erwin

JANUARY 17, 2020

Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise. SQL or NoSQL?

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

IBM Big Data Hub

JULY 13, 2022

This information is then automatically scanned into Watson Knowledge Catalog’s Data Lineage UI and becomes available to view alongside the data quality, business terms, and other metadata previously available to Watson Knowledge Catalog users. The post Do you know your data’s complete story?

Metadata 64

Metadata Data Governance Data Quality Data Integration 64

Data Virtualization

OCTOBER 18, 2022

The post The Data Warehouse is Dead, Long Live the Data Warehouse, Part I appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information. In times of potentially troublesome change, the apparent paradox and inner poetry of these.

Data Warehouse 98

Data Warehouse ROI Data Integration Internet of Things 98

IBM Big Data Hub

NOVEMBER 4, 2022

Increasingly enterprise data is spread across multiple environments which contributes to inconsistent data silos that complicate data governance initiatives and create data integrity issues that could impact Business Intelligence and analytics applications. IBM’s holistic approach to Data Quality.

Data Quality 56

Data Quality Metadata Data Governance Data-driven 56

erwin

APRIL 27, 2022

Best Data Modeling Solution (erwin Data Modeler). Read more about erwin® Data Modeler by Quest. These industry-leading data operations solutions automate routine tasks, such as schema comparisons, script execution, report creation and distribution – allowing DBAs to focus on more meaningful and high value initiatives.

Data Governance 52

Data Governance Digital Transformation Metadata Data Warehouse 52

Cloudera

FEBRUARY 11, 2019

The January 2019 “Magic Quadrant for Data Management Solutions for Analytics” provides valuable insights into the status, direction, and players in the DMSA market. In this blog, we share our takeaways as they relate to the DMSA market trends. 3. Expansion beyond core data management. Cloudera’s Positioning.

Management 43

Management Metadata Analytics Machine Learning 43

IBM Big Data Hub

MAY 9, 2022

These use cases provide a foundation that delivers a rich and intuitive data shopping experience. This data marketplace capability will enable organizations to efficiently deliver high quality governed data products at scale across the enterprise. Multicloud data integration.

Management 56

Management Data Quality Metadata Data Integration 56

IBM Big Data Hub

JUNE 23, 2022

The ability to compose and re-use data services with IBM’s data fabric on IBM Cloud Pak for Data allows you to tackle a variety of use cases such as multi-cloud data integration, governance and privacy, customer 360, and MLOps and Trustworthy AI. Providing the semantic.

Enterprise 52

Enterprise Metadata Data Governance Machine Learning 52

AWS Big Data

JUNE 7, 2023

This is a guest blog post co-written with Sumesh M R from Cargotec and Tero Karttunen from Knowit Finland. For this, Cargotec built an Amazon Simple Storage Service (Amazon S3) data lake and cataloged the data assets in AWS Glue Data Catalog. An AWS Glue job (metadata exporter) runs daily on the source account.

Metadata 56

Metadata Data Lake Machine Learning Big Data 56

Cloudera

AUGUST 31, 2021

Running on CDW is fully integrated with streaming, data engineering, and machine learning analytics. It has a consistent framework that secures and provides governance for all data and metadata on private clouds, multiple public clouds, or hybrid clouds. Consideration of both data & metadata in the migration.

Data Warehouse 81

Data Warehouse Cost-Benefit Metadata Data-driven 81

AWS Big Data

SEPTEMBER 13, 2023

To process data effectively, we use AWS Glue , a serverless data integration service that uses the Spark Structured Streaming framework and enables near-real-time data processing. An AWS Glue streaming job can handle large volumes of incoming data from MSK Serverless with IAM authentication. boot-30vvr5lg.c1.kafka-serverless.us-

Data Processing 94

Data Processing Management Interactive Metadata 94

IBM Big Data Hub

SEPTEMBER 20, 2022

Often data scientists aren’t thrilled with the prospect of generating all the documentation necessary to meet ethical and regulatory standards. This is where technology such as IBM FactSheets , can help by reducing the manual labor needed to capture metadata and other facts about a model across stages of the AI lifecycle.

Metadata 56

Metadata Machine Learning Data-driven Modeling 56

erwin

FEBRUARY 19, 2021

Metadata management is key to wringing all the value possible from data assets. However, most organizations don’t use all the data at their disposal to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or accomplish other strategic objectives. What Is Metadata? Harvest data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. In short, yes.

Data Quality 66

Data Quality Data Integration Metadata Cost-Benefit 66

Data Virtualization

MARCH 3, 2021

To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is. The post Data Management Challenges for the Modern Enterprise appeared first on Data Virtualization blog.

Enterprise 75

Enterprise Management Strategy Data Lake 75

Ontotext

NOVEMBER 23, 2023

Ontotext started with the basic assumption for big data — everyone will want to validate everything, and since data is large, it better be incremental, as performance will be poor otherwise. The next step is to link the data graph to the shapes graph: ex:TolkienDragonShape sh:shapesGraph ex:TolkienShapesGraph.

Data Quality 69

Data Quality Reporting Metadata IT 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 95

Data Lake Snapshot Metadata Optimization 95

AWS Big Data

SEPTEMBER 7, 2023

It is also crucial to audit granular data access for security and compliance needs. This blog post presents an architecture solution that allows customers to extract key insights from Amazon S3 access logs at scale. Both the user data and logs buckets must be in the same AWS Region and owned by the same account.

Metadata 102

Metadata Dashboards Metrics Visualization 102

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 96

Data Lake Data Warehouse Metadata Data Architecture 96

AWS Big Data

SEPTEMBER 29, 2023

Analyzing XML files can help organizations gain insights into their data, allowing them to make better decisions and improve their operations. Analyzing XML files can also help in data integration, because many applications and systems use XML as a standard data format. Choose Add a data store. Choose Create.

Metadata 66

Metadata Visualization Data-driven Optimization 66

IBM Big Data Hub

JANUARY 9, 2024

The entire generative AI pipeline hinges on the data pipelines that empower it, making it imperative to take the correct precautions. 4 key components to ensure reliable data ingestion Data quality and governance: Data quality means ensuring the security of data sources, maintaining holistic data and providing clear metadata.

Enterprise 75

Enterprise Data Integration Data Quality Contextual Data 75

Alation

JANUARY 25, 2022

Data fabric is now on the minds of most data management leaders. In our previous blog, Data Mesh vs. Data Fabric: A Love Story , we defined data fabric and outlined its uses and motivations. The data catalog is a foundational layer of the data fabric. The Power of Social Metadata.

Metadata 52

Metadata IT Metrics Data-driven 52

IBM Big Data Hub

APRIL 27, 2022

Gartner defines a data fabric as “a design concept that serves as an integrated layer of data and connecting processes. The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale. 11 May 2021. . 3 March 2022.

Management 83

Management Metadata Data Architecture Data Lake 83

erwin

MAY 27, 2020

What, then, should users look for in a data modeling product to support their governance/intelligence requirements in the data-driven enterprise? Nine Steps to Data Modeling. Provide metadata and schema visualization regardless of where data is stored. naming and database standards, formatting options, and so on.

Modeling 98

Modeling Metadata Data Governance Visualization 98

IBM Big Data Hub

MARCH 25, 2022

A data fabric is an architectural approach that enables organizations to simplify data access and data governance across a hybrid multicloud landscape for better 360-degree views of the customer and enhanced MLOps and trustworthy AI. The post What is a data fabric architecture? appeared first on Journey to AI Blog.

Metadata 109

Metadata Data Quality Data Governance Data Integration 109

IBM Big Data Hub

JANUARY 17, 2023

IBM Cloud Pak for Data Express solutions offer clients a simple on ramp to start realizing the business value of a modern architecture. Data governance. The data governance capability of a data fabric focuses on the collection, management and automation of an organization’s data. Data integration.

Data-driven 56

Data-driven Enterprise Data Governance Prescriptive Analytics 56

IBM Big Data Hub

OCTOBER 12, 2023

They’re built on machine learning algorithms that create outputs based on an organization’s data or other third-party big data sources. Sometimes, these outputs are biased because the data used to train the model was incomplete or inaccurate in some way.

Cost-Benefit 79

Cost-Benefit Metadata Data Governance Modeling 79

erwin

FEBRUARY 4, 2021

Automate code generation : Alleviate the need for developers to hand code connections from data sources to target schema. It also makes it easier for business analysts, data architects, ETL developers, testers and project managers to collaborate for faster decision-making.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

IBM Big Data Hub

SEPTEMBER 12, 2022

To understand how a data fabric helps maintain compliance to privacy regulations, it’s helpful to look at some essential elements of that single pane of glass. Build a foundation using a common catalog and metadata. It lets appropriate parties, such as the company’s chief data analyst, know what the data is and where it resides.

Metadata 95

Metadata Data Governance Enterprise Data Architecture 95

Cloudera

JUNE 6, 2019

When a mix of batch, interactive, and data serving workloads are added to the mix, the problem becomes nearly intractable. While this approach provides isolation, it creates another significant challenge: duplication of data, metadata, and security policies, or ‘split-brain’ data lake.

Metadata 85

Metadata Data Lake Optimization Strategy 85

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 89

Data Lake Analytics Snapshot Optimization 89

IBM Big Data Hub

AUGUST 7, 2023

Transparency throughout the data lifecycle and the ability to demonstrate data integrity and consistency are critical factors for improvement. The ledger delivers tamper evidence, enabling the detection of any modifications made to the data, even if carried out by privileged users.

Data Governance 65

Data Governance Manufacturing Interactive IoT 65

O'Reilly on Data

MARCH 20, 2019

Data integrity constraints: Many databases don’t allow for strange or unrealistic combinations of input variables and this could potentially thwart watermarking attacks. Applying data integrity constraints on live, incoming data streams could have the same benefits. Disparate impact analysis: see section 1.

Modeling 222

Modeling Machine Learning Predictive Modeling Consulting 222