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. They must be accompanied by documentation to support compliance-based and operational auditing requirements.

Data Governance 142

Data Governance Management Metadata Data Quality 142

erwin

JUNE 26, 2020

Organizations with particularly deep data stores might need a data catalog with advanced capabilities, such as automated metadata harvesting to speed up the data preparation process. Three Types of Metadata in a Data Catalog. The metadata provides information about the asset that makes it easier to locate, understand and evaluate.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

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. Manual processes that introduce risk and make it hard to scale. Challenges around managing risk. It is an imperative.

Metadata 102

Metadata Risk Risk Management Experimentation 102

AWS Big Data

FEBRUARY 29, 2024

First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses. From here, object metadata (such as file owner, creation date, and confidentiality level) is extracted and queried using Amazon S3 capabilities.

Data Governance 92

Data Governance Unstructured Data Metadata Data Lake 92

erwin

SEPTEMBER 3, 2020

It documents your data assets from end to end for business understanding and clear data lineage with traceability. Data governance and EA also provide many of the same benefits of enterprise architecture or business process modeling projects: reducing risk, optimizing operations, and increasing the use of trusted data.

Data Governance 144

Data Governance Enterprise Risk Data Lake 144

erwin

APRIL 9, 2020

If we have not yet ingested and organized both at-rest and in-motion metadata from across our system landscape, then we may be at a disadvantage when it comes to business continuity. Documented Policies and Procedures. Therefore, we need to be aware of our potential risks and put plans in place to mitigate those risks.

Metadata 132

Metadata Risk Data Governance IT 132

erwin

OCTOBER 8, 2020

And you can’t risk false starts or delayed ROI that reduces the confidence of the business and taint this transformational initiative. But even with the “need for speed” to market, new applications must be modeled and documented for compliance, transparency and stakeholder literacy. GDPR, CCPA, HIPAA, SOX, PIC DSS).

Data Governance 145

Data Governance Metadata Testing Data Lake 145

CIO Business Intelligence

DECEMBER 13, 2023

and applying and enriching metadata helps organizations take a big step toward innovating with generative AI. Balancing reward and risk Once in the shadows, unstructured data is pivotal in helping generative AI enable human creativity and problem-solving.

Unstructured Data 98

Unstructured Data IoT Metadata Modeling 98

Octopai

JANUARY 19, 2020

BCBS 239 is a document published by that committee entitled, Principles for Effective Risk Data Aggregation and Risk Reporting. The document, first published in 2013, outlines best practices for global and domestic banks to identify, manage, and report risks, including credit, market, liquidity, and operational risks.

Metadata 61

Metadata Risk Management Business Intelligence Data Governance 61

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. And there’s control of that landscape to facilitate insight and collaboration and limit risk.

Data Governance 40

Data Governance Risk Metadata Management 40

CIO Business Intelligence

MAY 10, 2023

As companies open this “pandora’s box” of new capabilities, they must be prepared to manage data inputs and outputs in secure ways or risk allowing their private data to be consumed in public AI models. The first step in this process is to ensure the right technical and business metadata is in place.

Metadata 98

Metadata Data Governance Modeling Technology 98

erwin

SEPTEMBER 10, 2020

Not Documenting End-to-End Data Lineage Is Risky Busines – Understanding your data’s origins is key to successful data governance. Data lineage helps answer questions about the origin of data in key performance indicator (KPI) reports, including: How are the report tables and columns defined in the metadata?

Data Governance 131

Data Governance Key Performance Indicator Digital Transformation Metadata 131

Ontotext

DECEMBER 16, 2021

Organizations in this sector often deal with multiple repositories of millions of documents on top of proprietary data from labs and other internal sources. Domain experts can document their knowledge of terms and concepts within the graph and then connect the nodes to data stored in any number of external sources. See figure 1.).

Metadata 98

Metadata Reporting Unstructured Data Risk 98

erwin

JANUARY 30, 2020

However, more than 50 percent say they have deployed metadata management, data analytics, and data quality solutions. erwin Named a Leader in Gartner 2019 Metadata Management Magic Quadrant. And close to 50 percent have deployed data catalogs and business glossaries. Top Five: Benefits of An Automation Framework for Data Governance.

Data Governance 145

Data Governance Metadata Digital Transformation Cost-Benefit 145

erwin

SEPTEMBER 17, 2020

For example, automatically importing mappings from developers’ Excel sheets, flat files, Access and ETL tools into a comprehensive mappings inventory, complete with auto generated and meaningful documentation of the mappings, is a powerful way to support overall data governance. Data quality is crucial to every organization.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

erwin

APRIL 29, 2020

An understanding of the data’s origins and history helps answer questions about the origin of data in a Key Performance Indicator (KPI) reports, including: How the report tables and columns are defined in the metadata? Business terms and data policies should be implemented through standardized and documented business rules.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

Rocket-Powered Data Science

FEBRUARY 15, 2023

3) How do we get started, when, who will be involved, and what are the targeted benefits, results, outcomes, and consequences (including risks)? (2) Why should your organization be doing it and why should your people commit to it? (3) In short, you must be willing and able to answer the seven WWWWWH questions (Who?

Strategy 289

Strategy Experimentation Uncertainty Machine Learning 289

Cloudera

SEPTEMBER 28, 2020

In order to minimize risk and downtime, the upgrades were performed in that order and the learning from each upgrade was applied to the next upgraded environment. Major upgrades of production environments can require hours to days of downtime, so it is critical that upgrades are efficient and planned to minimize risks. or Ubuntu 18.04.

Testing 130

Testing Metadata Risk Data Science 130

Alation

SEPTEMBER 7, 2021

In this blog we will discuss how Alation helps minimize risk with active data governance. Governance influences how an organization’s objectives are set and achieved, how risk is monitored and addressed, and how performance is optimized. Organizations that run afoul of such laws risk damaging their reputation.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

erwin

JANUARY 24, 2019

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. Governing metadata. The 100-percent metadata-driven approach is critical to creating reliable and consistent CATs.

Data Governance 71

Data Governance Metadata Data-driven Cost-Benefit 71

Smart Data Collective

JULY 15, 2021

By using metadata (or short descriptions), data catalogs help companies gather, organize, retrieve, and manage information. A data catalog will usually have a search tool, a separate data discovery tool, a glossary, and a metadata registry. Metadata registries organize various data sets according to categories and fields.

Metadata 124

Metadata IT Data-driven Data Quality 124

erwin

JULY 12, 2019

Modern, strategic data governance , which involves both IT and the business, enables organizations to plan and document how they will discover and understand their data within context, track its physical existence and lineage, and maximize its security, quality and value. Five Steps to GDPR/CCPA Compliance. Strengthen data security.

Data Governance 110

Data Governance Management Metadata Risk Management 110

erwin

AUGUST 7, 2019

With the right data catalog tool, organizations can automate enterprise metadata management – including data cataloging, data mapping, data quality and code generation for faster time to value and greater accuracy for data movement and/or deployment projects. At each stage, the discovered pieces of lineage are documented.

Metadata 90

Metadata Data Governance Data Quality Data Warehouse 90

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. So being prepared means you can minimize your risk exposure and the damage to your reputation. No Hocus Pocus.

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. Lack of a solid data governance foundation increases the risk of data-security incidents. Is it sensitive data or are there any risks associated with it?

Data Governance 106

Data Governance Cost-Benefit Risk Metadata 106

Alation

MARCH 31, 2023

Ehtisham Zaidi, Gartner’s VP of data management, and Robert Thanaraj, Gartner’s director of data management, gave an update on the fabric versus mesh debate in light of what they call the “active metadata era” we’re currently in. The active metadata helix Indeed, automation was on everyone’s minds. We couldn’t agree more.

Data Analytics 52

Data Analytics Analytics Metadata Data Governance 52

Ontotext

FEBRUARY 12, 2024

This calls for additional planning, documentation, and testing. It’s also critical to advocate a smooth culture change because data mesh involves shifting from thinking about data as tables to data as a combination of multiple elements, such as code, infrastructure, and metadata. Not all organizations are ready to make that investment.

Data Quality 69

Data Quality Data-driven Data Lake Data Governance 69

erwin

JANUARY 17, 2020

Data models provide visualization, create additional metadata and standardize data design across the enterprise. Thanks to organizations like Amazon, Netflix and Uber, businesses have changed how they leverage their data and are transforming their business models to innovate – or risk becoming obsolete. SQL or NoSQL?

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

Alation

APRIL 18, 2023

This is accomplished by analyzing one or multiple data sources and collecting metadata that shows the condition of the data and enables the data steward to investigate the origin of data errors. Do you need to add metadata to information to put it in a data lake? Do you need to define a data quality rule and add that to the profile?

IT 52

IT Data Quality Metadata Data Governance 52

Alation

FEBRUARY 13, 2020

A Data Catalog is 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. Figure 1 – Data Catalog Metadata Subjects. Conclusion.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

Smart Data Collective

JULY 27, 2021

Over the years, Snapshot has grown into the industry’s most comprehensive toolset for org management, relational data migration, documentation, technical debt removal, and more. As such, when it starts generating piles of technical debt, customers are at risk of system failure. What about SAP and Oracle? Visualize the problem.

Big Data 129

Big Data Snapshot IT Dashboards 129

Alation

MARCH 14, 2023

All critical data elements (CDEs) should be collated and inventoried with relevant metadata, then classified into relevant categories and curated as we further define below. Store Where individual departments have their own databases for metadata management, data will be siloed, meaning it can’t be shared and used business-wide.

Data Strategy 52

Data Strategy Strategy Metadata Data Quality 52

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. Your model risk management team, IT operations team and line-of-business employees also need appropriate access.

Metadata 57

Metadata Machine Learning Data-driven Modeling 57

datapine

SEPTEMBER 29, 2022

It involves: Reviewing data in detail Comparing and contrasting the data to its own metadata Running statistical models Data quality reports. Data processes that depended upon the previously defective data will likely need to be re-initiated, especially if their functioning was at risk or compromised by the defected data.

Data Quality 241

Data Quality Metrics Data-driven Management 241

CIO Business Intelligence

DECEMBER 4, 2023

With constant advances in intelligent document processing, compute power, DevOps workflows, and AI, the content, context, and value of unstructured data is rapidly increasing. Beyond “records,” organizations can digitally capture anything and apply metadata for context and searchability. Iron Mountain Capture/Enrich. Preserve/Dispose.

Unstructured Data 52

Unstructured Data Data Lake Business Objectives Metadata 52

Octopai

DECEMBER 11, 2022

Banks didn’t accurately assess their credit and operational risk and hold enough capital reserves, leading to the Great Recession of 2008-2009. Data lineage and financial risk data compliance. All these models need to be informed by data, with operational risk assessment mandating loss data that goes back 10 years. .

Insurance 52

Insurance Risk Metadata Reporting 52

Octopai

JULY 9, 2020

By adopting automated data lineage and automated metadata tagging, companies have the opportunity to increase their data processing speed. It required banks to develop a data architecture that could support risk-management tools. A key piece of legislation that emerged from that crisis was BCBS-239.

Insurance 86

Insurance Risk Management Machine Learning Metadata 86