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

Smart Data Collective

APRIL 10, 2019

When that happens, tens of thousands of people are put at risk for identity theft when their metadata is stolen. What is metadata and how is it used? What Metadata Contains. Metadata is basically a trail of data that is spread out across a network. Why a Cyber-Criminal Steals Metadata.

Metadata 67

Metadata Risk Technology Management 67

TDAN

APRIL 6, 2021

There is an ever-increasing awareness of concerns about data privacy, corporate data breaches, increasing demands for regulatory compliance. There are also emerging concerns about the ways that big data analytics potentially influence and bias automated decision-making.

Risk Management 64

Risk Management Risk Management Big Data 64

IBM Big Data Hub

OCTOBER 4, 2022

Today, AI presents an enormous opportunity to turn data into insights and actions, to amplify human capabilities, decrease risk and increase ROI by achieving break through innovations. Furthermore, 59% of executives claim AI can improve the use of big data in their organizations, facts about artificial intelligence show. (

Metadata 103

Metadata Risk Risk Management Experimentation 103

AWS Big Data

APRIL 19, 2023

Many customers run big data workloads such as extract, transform, and load (ETL) on Apache Hive to create a data warehouse on Hadoop. Instead, we can use automation to speed up the process of migration and reduce heavy lifting tasks, costs, and risks. The script generates a metadata JSON file for each step.

Metadata 80

Metadata Testing Data Lake Consulting 80

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time. The program must introduce and support standardization of enterprise data.

Data Governance 142

Data Governance Management Metadata Data Quality 142

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

AWS Big Data

FEBRUARY 29, 2024

Data discoverability Unlike structured data, which is managed in well-defined rows and columns, unstructured data is stored as objects. For users to be able to discover and comprehend the data, the first step is to build a comprehensive catalog using the metadata that is generated and captured in the source systems.

Data Governance 98

Data Governance Unstructured Data Metadata Data Lake 98

IBM Big Data Hub

MAY 9, 2023

Today, AI presents an enormous opportunity to turn data into insights and actions, to help amplify human capabilities, decrease risk and increase ROI by achieving break through innovations. It drives an AI governance solution without the excessive costs of switching from your current data science platform. It is an imperative.

Metadata 80

Metadata Risk Experimentation Dashboards 80

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

erwin

OCTOBER 31, 2019

While sometimes at rest in databases, data lakes and data warehouses; a large percentage is federated and integrated across the enterprise, introducing governance, manageability and risk issues that must be managed. A well-formed security architecture that is driven by and aligned by data intelligence is your best defense.

Data Governance 105

Data Governance Metadata Risk Data Lake 105

erwin

APRIL 2, 2021

With more companies increasingly migrating their data to the cloud to ensure availability and scalability, the risks associated with data management and protection also are growing. Data Security Starts with Data Governance. Lack of a solid data governance foundation increases the risk of data-security incidents.

Data Governance 106

Data Governance Cost-Benefit Risk Metadata 106

Cloudera

AUGUST 3, 2021

Advanced analytics empower risk reduction . 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. . Leveraging data where it lies.

Analytics 109

Analytics Digital Transformation Risk Forecasting 109

AWS Big Data

FEBRUARY 12, 2024

To ensure these dashboards showcase the most updated insights, the organization builders and data architects need to catalog and update AWS Clean Rooms collaboration outputs on an ongoing basis, which often involves repetitive and manual processes that, if not done well, could delay your organization’s access to the latest data insights.

Publishing 93

Publishing Dashboards Metadata Visualization 93

IBM Big Data Hub

DECEMBER 4, 2023

IBM’s governance framework is built around four core roles within the company: The Policy Advisory Committee: senior global leaders who provide oversight of the AI Ethics Board and help to establish the company’s strategy and risk tolerance. It helps accelerate responsible, transparent and explainable AI workflows.

Consulting 84

Consulting Risk Metadata Risk Management 84

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 127

Metadata IT Data-driven Data Quality 127

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

Smart Data Collective

OCTOBER 28, 2020

Many healthcare organizations also retain data for future research into care improvements or related projects, in which case it’s critical to ensure that when you decommission a data system , you also export and appropriately store any associated metadata. That’s a problem since old software quickly becomes a security risk.

Cost-Benefit 128

Cost-Benefit Risk Metadata Software 128

AWS Big Data

NOVEMBER 17, 2023

Starting today, the Athena SQL engine uses a cost-based optimizer (CBO), a new feature that uses table and column statistics stored in the AWS Glue Data Catalog as part of the table’s metadata. By using these statistics, CBO improves query run plans and boosts the performance of queries run in Athena. Pathik Shah is a Sr.

Optimization 115

Optimization Statistics Metadata Data Lake 115

IBM Big Data Hub

APRIL 20, 2023

When consumers lose trust in a bank’s ability to manage risk, the system stops working. Banks and their employees place trust in their risk models to help ensure the bank maintains liquidity even in the worst of times. We’ve seen what follows—financial crises, bailouts, destruction of capital, and losses of jobs.

Risk 76

Risk Risk Management Reporting Metadata 76

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

CIO Business Intelligence

DECEMBER 16, 2022

The top-earning skills were big data analytics and Ethereum, with a pay premium of 20% of base salary, both up 5.3% Security, as ever, made a strong showing, with big premiums paid for experience in cryptography, penetration testing, risk analytics and assessment, and security testing. in the previous six months.

Testing 98

Testing Metadata Data Processing Machine Learning 98

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

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

Alation

MAY 19, 2022

Gartner Data & Analytics Summit 2022: Keynote Highlights. A Gartner survey found that 57% of Boards of Directors have increased their risk appetites, and data & analytics are fueling more risky (and potentially rewarding) projects. Leaders agree: Data needs to drive business results. Establish what data you have.

Metadata 52

Metadata Data Analytics Analytics Data Governance 52

AWS Big Data

APRIL 26, 2023

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. This is a guest blog post co-written with Corey Johnson from Huron.

Metadata 52

Metadata Dashboards Visualization Consulting 52

Rocket-Powered Data Science

JULY 19, 2023

The latter is associated primarily with “watching” the data for interesting patterns, while precursor analytics is associated primarily with training the business systems to quickly identify those specific patterns and events that could be associated with high-risk events, thus requiring timely attention, intervention, and remediation.

Data-driven 186

Data-driven Enterprise Analytics Machine Learning 186

IBM Big Data Hub

APRIL 10, 2023

A well-designed data architecture should support business intelligence and analysis, automation, and AI—all of which can help organizations to quickly seize market opportunities, build customer value, drive major efficiencies, and respond to risks such as supply chain disruptions.

Strategy 96

Strategy Data Architecture Cost-Benefit Reporting 96

IBM Big Data Hub

JUNE 26, 2023

Each organization must balance opportunities for value creation with the risks involved. Depending on the business and the use case, if tolerance for risk is low, organizations will find that either building in house or working with a trusted partner will yield better results. What is watsonx.governance?

Risk 73

Risk Deep Learning Metadata Modeling 73

CIO Business Intelligence

DECEMBER 4, 2023

Although less complex than the “4 Vs” of big data (velocity, veracity, volume, and variety), orienting to the variety and volume of a challenging puzzle is similar to what CIOs face with information management. Beyond “records,” organizations can digitally capture anything and apply metadata for context and searchability.

Unstructured Data 52

Unstructured Data Data Lake Metadata Business Objectives 52

IBM Big Data Hub

JANUARY 3, 2024

Outputs for these high-risk models should offer test-retest reliability. Outputs should be 100% accurate and detail data sources along with evidence. The metadata should also show how a user can opt out of using that model (and get the same service elsewhere). Require transparency.

Metadata 82

Metadata Modeling Testing Manufacturing 82

IBM Big Data Hub

MAY 9, 2024

Conversely, confidence in the accuracy and consistency of your data can minimize the risk of adverse health outcomes, rather than merely reacting to or causing them. Also, using predictive analytics can help identify trends, patterns and potential future health risks in your patients. Instead, it uses active metadata.

Data Governance 70

Data Governance Data Quality Insurance Predictive Analytics 70

Cloudera

SEPTEMBER 28, 2020

Cloudera delivers an enterprise data cloud that enables companies to build end-to-end data pipelines for hybrid cloud, spanning edge devices to public or private cloud, with integrated security and governance underpinning it to protect customers data. The total data size is over one petabyte (1PB). Phase 1: Planning.

Testing 131

Testing Metadata Risk Data Science 131

erwin

APRIL 11, 2019

Your chosen data governance solution should enable you to automate the scanning, detection and tagging of sensitive data by: Monitoring and controlling sensitive data – Gain better visibility and control across the enterprise to identify data security threats and reduce associated risks.

Insurance 100

Insurance Data-driven Data Governance Metadata 100

IBM Big Data Hub

SEPTEMBER 20, 2022

Alongside the significant brand reputation risk, there’s also a growing set of data and AI regulations across the world and across industries — like the upcoming European Union AI Act — that companies must adhere to. It’s not just about granting proper access to data science teams.

Metadata 57

Metadata Machine Learning Data-driven Modeling 57

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

AWS Big Data

JUNE 15, 2023

Because they are looking at populations at risk, they need the flexibility of a line list of cases, stripped of personally identifiable information (PII). With this information, they can assess risk based on a variety of demographic and social factors available in the data sources without divulging PII.

Metadata 91

Metadata Dashboards Risk Statistics 91