CIO Business Intelligence

APRIL 16, 2024

With the emergence of GenAI capabilities, fast-tracking digital transformation deployments are likely to change manufacturing as we know it, creating an expanding chasm of leaders versus followers, the latter of which will risk obsolescence. However, despite the benefits of GenAI, there are some areas of risk. Data quality dependence.

Manufacturing 142

Manufacturing Digital Transformation Risk Dashboards 142

CIO Business Intelligence

APRIL 1, 2024

Deloitte 2 meanwhile found that 41% of business and technology leaders said a lack of talent, governance, and risks are barriers to broader GenAI adoption. Capturing the “as-is” state of your environment, you’ll develop topology diagrams and document information on your technical systems. Assess your readiness. Pick the right partners.

Uncertainty 142

Uncertainty Data Lake Consulting Risk 142

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. Data-related decisions, processes, and controls subject to data governance must be auditable.

Data Governance 142

Data Governance Management Metadata Data Quality 142

Alation

SEPTEMBER 7, 2021

In this blog we will discuss how Alation helps minimize risk with active data governance. Now that you have empowered data scientists and analysts to access the Snowflake Data Cloud and speed their modeling and analysis, you need to bolster the effectiveness of your governance models. Find Trusted Data.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

CIO Business Intelligence

MAY 2, 2023

Worse is when prioritized initiatives don’t have a documented shared vision, including a definition of the customer, targeted value propositions, and achievable success criteria. The risk of derailments increases as I hear inconsistent answers or too many conflicting priorities.

Digital Transformation 141

Digital Transformation IT Data-driven Metrics 141

O'Reilly on Data

NOVEMBER 28, 2023

Unexpected outcomes, security, safety, fairness and bias, and privacy are the biggest risks for which adopters are testing. And there are tools for archiving and indexing prompts for reuse, vector databases for retrieving documents that an AI can use to answer a question, and much more. Only 4% pointed to lower head counts.

Enterprise 277

Enterprise Testing Modeling Reporting 277

Octopai

JUNE 19, 2024

A data contract is a formal agreement between data producers and data consumers that specifies the structure, quality, and meaning of the data being exchanged. Data contracts work by establishing clear expectations and responsibilities.

Data Quality 52

Data Quality Data-driven Data Integration Risk 52

Octopai

JUNE 19, 2024

A data contract is a formal agreement between data producers and data consumers that specifies the structure, quality, and meaning of the data being exchanged. Data contracts work by establishing clear expectations and responsibilities.

Data Quality 52

Data Quality Data-driven Data Integration Risk 52

CIO Business Intelligence

AUGUST 15, 2024

Many of those gen AI projects will fail because of poor data quality, inadequate risk controls, unclear business value , or escalating costs , Gartner predicts. CIOs should first launch internal projects with low public-facing exposure , which can mitigate risk and provide a controlled environment for experimentation.

ROI 143

ROI Cost-Benefit Experimentation Deep Learning 143

CIO Business Intelligence

DECEMBER 19, 2023

Create these six generative AI workstreams CIOs should document their AI strategy for delivering short-term productivity improvements while planning visionary impacts. These workstreams require documenting a vision, assigning leaders, and empowering teams to experiment.

Digital Transformation 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

AWS Big Data

FEBRUARY 29, 2024

Data governance is a critical building block across all these approaches, and we see two emerging areas of focus. 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.

Data Governance 102

Data Governance Unstructured Data Metadata Data Lake 102

CIO Business Intelligence

APRIL 8, 2024

Working with partner Amazon Web Services (AWS), the NFL has developed Digital Athlete, a platform that uses computer vision and ML to predict which players are at the highest risk of injury based on plays and their body positions. million video frames and documents about 100 million locations and positions of players on the field.

Analytics 118

Analytics Broadcasting Predictive Analytics Machine Learning 118

erwin

APRIL 29, 2020

In the event of a change in data expectations, data lineage provides a way to determine which downstream applications and processes are affected by the change and helps in planning for application updates. Business terms and data policies should be implemented through standardized and documented business rules.

Key Performance Indicator 111

Key Performance Indicator Metadata Data Governance Data Quality 111

CIO Business Intelligence

MAY 15, 2024

“If you have a data center that happens to have capacity, why pay someone else?” According to Synopsys’ open source security and risk analysis released in February, 96% of all commercial code bases contained open source components. It also focuses largely on risk and governance issues. But that might not always be the case.

Modeling 137

Modeling Risk Software Enterprise 137

DataRobot Blog

JULY 21, 2022

Inquire whether there is sufficient data to support machine learning. Document assumptions and risks to develop a risk management strategy. For a credit risk model, the target could be defined as “fully repays loan” or “payments in first 2 years are current” or or “collateral is repossessed.”. Define project scope.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

CIO Business Intelligence

JANUARY 23, 2024

Quality metrics can be used to measure the improvements that come from reducing defects, lowering the impacts of human errors, improving data quality, and other program outcomes that illustrate how increasing quality connects to business impact.

Measurement 141

Measurement Digital Transformation KPI Metrics 141

erwin

MARCH 25, 2021

Risk Management and Regulatory Compliance. Risk management, specifically around regulatory compliance, is an important use case to demonstrate the true value of data governance. According to Pörschmann, risk management asks two main questions. Strengthen data security. How likely is a specific event to happen? “You

Data Governance 109

Data Governance Cost-Benefit IT Risk 109

Octopai

MAY 15, 2023

Data lineage helps identify redundant or inefficient data integration steps, allowing organizations to streamline their processes and reduce development, maintenance, and operational costs associated with ETL. Data quality costs: Poor data quality can result in significant costs for organizations.

Data Quality 52

Data Quality Data Governance Data Integration Risk 52

IBM Big Data Hub

JANUARY 9, 2024

Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextual data is what enables LLMs to change from general-purpose to domain-specific knowledge. This may also entail working with new data through methods like web scraping or uploading.

Enterprise 71

Enterprise Data Integration Data Quality Contextual Data 71

erwin

JANUARY 11, 2019

A company can’t effectively implement data governance – documenting and applying business rules and processes, analyzing the impact of changes and conducting audits – if it fails at data management. The problem usually starts by relying on manual integration methods for data preparation and mapping.

Data Governance 40

Data Governance Risk Metadata Management 40

Alation

AUGUST 17, 2022

We’ve seen the emergence of new, less invasive approaches, yet the question remains: What do CIOs think is most required to deliver a successful data governance program? The Risks of Early Data Governance Programs. The biggest risk was a lack of ownership. If your definitions are bad, so is your governance/risk/security.

Data Governance 92

Data Governance Risk Data-driven Measurement 92

CIO Business Intelligence

JANUARY 9, 2024

He and his team have created information decks, documents, and presentations that describe the various types of AI and how they can be used and explain how and where AI and machine learning may be useful — and why it’s not the solution to all the problems they have. What is our appetite for risk and how do we address it?

IT 140

IT Risk Cost-Benefit Machine Learning 140

erwin

FEBRUARY 19, 2021

A strong data management strategy and supporting technology enables the data quality the business requires, including data cataloging (integration of data sets from various sources), mapping, versioning, business rules and glossaries maintenance and metadata management (associations and lineage). Harvest data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

Ontotext

FEBRUARY 12, 2024

Domain teams should continually monitor for data errors with data validation checks and incorporate data lineage to track usage. Establish and enforce data governance by ensuring all data used is accurate, complete, and compliant with regulations. This calls for additional planning, documentation, and testing.

Data Quality 69

Data Quality Data-driven Data Lake Data Governance 69

Grooper

APRIL 9, 2020

The heart of digital transformation is data, and organizations without a clear strategy for data curation and enrichment from documents are at risk of failed transformation and missing out on massive revenue opportunities. The way we’ve thought about curating data from documents over the years is fundamentally flawed.

Digital Transformation 65

Digital Transformation Data Quality Enterprise Risk 65

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)? Clean it, annotate it, catalog it, and bring it into the data family (connect the dots and see what happens). In short, you must be willing and able to answer the seven WWWWWH questions (Who?

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

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 89

Metadata Risk Management Business Intelligence Data Governance 89

erwin

FEBRUARY 4, 2021

However, organizations still encounter a number of bottlenecks that may hold them back from fully realizing the value of their data in producing timely and relevant business insights. It uncovered a number of obstacles that organizations have to overcome to improve their data operations. Overcoming Data Governance Bottlenecks.

Data Governance 89

Data Governance Metadata Data Quality IoT 89

Octopai

JUNE 9, 2024

The inability to trace data lineage accurately made it difficult to demonstrate compliance during audits. This situation posed legal risks and threatened the organization’s reputation. The lack of trust in data created inertia. Accurate data lineage rebuilt trust among decision-makers.

IT 52

IT Data-driven Predictive Analytics Metadata 52

datapine

APRIL 15, 2020

Working software over comprehensive documentation. The agile BI implementation methodology starts with light documentation: you don’t have to heavily map this out. But before production, you need to develop documentation, test driven design (TDD), and implement these important steps: Actively involve key stakeholders once again.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

CIO Business Intelligence

AUGUST 2, 2024

Another priority area is to allow AI to find information from other sources such as the intranet and document management systems. Some older systems are linked to the new platform, though, which makes all the data in there better available to the business. It’s also about how we work with suppliers.”

IT 119

IT Cost-Benefit Data-driven Management 119

erwin

FEBRUARY 13, 2020

The numerous data types and data sources that exist today weren’t designed to work together, and data infrastructures have been cobbled together over time with disparate technologies, poor documentation and little thought for downstream integration. Finding metadata, “the data about the data,” isn’t easy.

Metadata 135

Metadata Data Governance Management Cost-Benefit 135

CIO Business Intelligence

JANUARY 30, 2024

“Always the gatekeepers of much of the data necessary for ESG reporting, CIOs are finding that companies are even more dependent on them,” says Nancy Mentesana, ESG executive director at Labrador US, a global communications firm focused on corporate disclosure documents.

Reporting 115

Reporting Data Quality Strategy Data-driven 115

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

CIO Business Intelligence

AUGUST 14, 2024

“They’re more able to connect to a diverse set of data sources, build more complex context around queries going through the model, and do retrieval augmented generation,” he adds. For most of our customers, Azure is where their identity is, where people’s credentials are, where people’s data already is,” he says.

Enterprise 136

Enterprise Cost-Benefit Experimentation Modeling 136

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. Strengthen data security.

Data Governance 110

Data Governance Management Metadata Risk Management 110

IBM Big Data Hub

NOVEMBER 24, 2023

Collectively, discovery and design is where significant time is spent during modernization, whereas development is much easier once the team has decoded the legacy application functionality, integration aspects, logic and data complexity. Generative AI also helps generate use cases based on code insights and functional mapping.

Cost-Benefit 89

Cost-Benefit Testing Data-driven Enterprise 89