DataRobot Blog

MAY 10, 2022

Addressing the Key Mandates of a Modern Model Risk Management Framework (MRM) When Leveraging Machine Learning . The regulatory guidance presented in these documents laid the foundation for evaluating and managing model risk for financial institutions across the United States. To reference SR 11-7: .

Risk 64

Risk Modeling Machine Learning Data Quality 64

Cloudera

JULY 15, 2021

We recently hosted a roundtable focused on o ptimizing risk and exposure management with data insights. For financial institutions and insurers, risk and exposure management has always been a fundamental tenet of the business. Now, risk management has become exponentially complicated in multiple dimensions. .

Risk 96

Risk Optimization Management Insurance 96

CIO Business Intelligence

APRIL 16, 2024

You’re fast asleep aboard the USS Enterprise Star Trek. 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. Data privacy and security.

Manufacturing 142

Manufacturing Digital Transformation Risk Dashboards 142

IBM Big Data Hub

AUGUST 23, 2023

The recent success of artificial intelligence based large language models has pushed the market to think more ambitiously about how AI could transform many enterprise processes. However, consumers and regulators have also become increasingly concerned with the safety of both their data and the AI models themselves.

Data Governance 57

Data Governance Enterprise Modeling Risk 57

Cloudera

MARCH 3, 2022

Whether the enterprise uses dozens or hundreds of data sources for multi-function analytics, all organizations can run into data governance issues. Bad data governance practices lead to data breaches, lawsuits, and regulatory fines — and no enterprise is immune. . Everyone Fails Data Governance.

Data Governance 95

Data Governance Enterprise Data Quality Metadata 95

Ontotext

MARCH 8, 2023

Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions. Each team and system need to keep diverse sets of data about their customers in order to play their specific role – inadvertently leading to siloed experiences.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

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. Data preparation, including anonymizing, labeling, and normalizing data across sources, is key. Low-cost proof-of-concepts can help you reduce the risk of overprovisioning.

Data Lake 142

Data Lake Consulting Uncertainty Risk 142

AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 95

Data Governance Unstructured Data Metadata Data Lake 95

IBM Big Data Hub

JUNE 8, 2022

Implementing the right data strategy spurs innovation and outstanding business outcomes by recognizing data as a critical asset that provides insights for better and more informed decision-making. By taking advantage of data, enterprises can shape business decisions, minimize risk for stakeholders, and gain competitive advantage.

Data-driven 58

Data-driven Enterprise Data Governance Data Lake 58

DataRobot Blog

MAY 26, 2022

To start with, SR 11-7 lays out the criticality of model validation in an effective model risk management practice: Model validation is the set of processes and activities intended to verify that models are performing as expected, in line with their design objectives and business uses.

Risk 52

Risk Modeling Metrics Business Objectives 52

Jim Harris

JANUARY 1, 2016

1 — Investigate Data quality is not exactly a riddle wrapped in a mystery inside an enigma. However, understanding your data is essential to using it effectively and improving its quality. In order for you to make sense of those data elements, you require business context.

Data Quality 61

Data Quality Data Governance Cost-Benefit ROI 61

CIO Business Intelligence

JANUARY 9, 2024

But they are being grilled in executive suites and boardrooms, as enterprise leaders turn to their technology chiefs with all sorts of challenging questions that CIOs are expected to answer. Enterprise investments in AI are paying off — big time. Can the current state of our data operations deliver the results we seek?

IT 140

IT Risk Cost-Benefit Enterprise 140

Octopai

JUNE 26, 2020

Steve needed a robust and automated metadata management solution as part of his organization’s data governance strategy. Enterprise data governance. Enterprises, such as Steve’s company, understand that they need a proper data governance strategy in place to successfully manage all the data they process.

Metadata 84

Metadata Data Governance Enterprise Reporting 84

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 Governance 142

Data Governance Management Metadata Data Quality 142

CIO Business Intelligence

JANUARY 24, 2024

Organizations can’t afford to mess up their data strategies, because too much is at stake in the digital economy. How enterprises gather, store, cleanse, access, and secure their data can be a major factor in their ability to meet corporate goals. Here are some data strategy mistakes IT leaders would be wise to avoid.

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

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

DECEMBER 8, 2023

But as the numbers of new gen AI-powered chatbots grow, so do the risks of their occasional glitches—nonsensical or inaccurate outputs or answers that are not easily screened out of the large language models (LLMs) that the tools are trained on. Minimizing risk Many companies are starting to invest in mitigating risk.

Risk 122

Risk Finance Data Quality Modeling 122

IBM Big Data Hub

NOVEMBER 29, 2023

To build that trust and drive broad adoption, vendors of synthetic data generation tools will need to address two critical questions that many business leaders ask: Will synthetic data expose my business to additional data privacy risks? How accurately does synthetic data reflect my existing data?

Metrics 88

Metrics Machine Learning Risk Statistics 88

CIO Business Intelligence

FEBRUARY 8, 2024

As a company, Stack Overflow’s products are built for the developer and for enterprises, so we understand the needs of developers and the needs of the thousands of enterprises they work for. AIs are more than the base knowledge or underlying “data” layer of the LLM or its “experience” layer.

Cost-Benefit 119

Cost-Benefit Experimentation Interactive Risk 119

CIO Business Intelligence

DECEMBER 19, 2023

First, enterprises have long struggled to improve customer, employee, and other search experiences. Improving search capabilities and addressing unstructured data processing challenges are key gaps for CIOs who want to deliver generative AI capabilities.

Digital Transformation 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

CIO Business Intelligence

MARCH 4, 2024

Despite these benefits, the core problems that data centralization so often fails to address are the pragmatic realities of many enterprise data ecosystems. Isolated data sources requiring long data transformation and integration timelines can become stumbling blocks to the realization of combined organizational benefits.

Insurance 98

Insurance Strategy Data Governance Data Integration 98

Ontotext

MARCH 18, 2020

According to an article in Harvard Business Review , cross-industry studies show that, on average, big enterprises actively use less than half of their structured data and sometimes about 1% of their unstructured data. Why Enterprise Knowledge Graphs? The third challenge is how to combine data management with analytics.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

Alation

MAY 20, 2021

Searchers can now hunt through data domains, with filters that help them spotlight the best asset more quickly. When it comes to enterprise search, Alation has always led the industry. Use at your own risk! This update coincides with Alation being named a winner for the Best Data Governance Solution by IMD/IRD!

Enterprise 52

Enterprise Metadata Data Quality Machine Learning 52

IBM Big Data Hub

NOVEMBER 28, 2022

How do you keep pace with growing data volumes and increased demand from data consumers and deliver real-time data governance for trusted outcomes? It is imperative to evolve metadata management approaches to keep pace with the proliferation of enterprise data. Provide early indicators of data quality.

Metadata 57

Metadata Data Quality Data-driven Data Governance 57

O'Reilly on Data

NOVEMBER 28, 2023

In enterprises, we’ve seen everything from wholesale adoption to policies that severely restrict or even forbid the use of generative AI. Unexpected outcomes, security, safety, fairness and bias, and privacy are the biggest risks for which adopters are testing. What’s the reality? Only 4% pointed to lower head counts.

Enterprise 273

Enterprise Modeling Testing Reporting 273

CIO Business Intelligence

MAY 2, 2023

The risk of derailments increases as I hear inconsistent answers or too many conflicting priorities. But there are common pitfalls , such as selecting the wrong KPIs , monitoring too many metrics, or not addressing poor data quality. The five derailments I focus on here fall within the CIO’s responsibilities to address.

Digital Transformation 141

Digital Transformation IT Data-driven Metrics 141

erwin

JULY 12, 2019

With all the advance notice and significant chatter for GDPR/CCPA, why aren’t organizations more prepared to deal with data regulations? The complexity of regulatory requirements in and of themselves is aggravated by the complexity of the business and data landscapes within most enterprises. Complexity. How erwin Can Help.

Data Governance 110

Data Governance Management Metadata Risk Management 110

DataKitchen

OCTOBER 2, 2023

Data Teams and Their Types of Data Journeys In the rapidly evolving landscape of data management and analytics, data teams face various challenges ranging from data ingestion to end-to-end observability. It explores why DataKitchen’s ‘Data Journeys’ capability can solve these challenges.

Data Quality 100

Data Quality Testing Uncertainty Data Enablement 100

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)? Love thy data: data are never perfect, but all the data may produce value, though not immediately. Think strategically, but act tactically: think big, start small, learn fast.

Strategy 289

Strategy Experimentation Uncertainty Machine Learning 289

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. But the attempts to standardize data across the entire enterprise haven’t produced the desired results.

Data Governance 40

Data Governance Risk Metadata Management 40

IBM Big Data Hub

JANUARY 15, 2024

Enterprises now recognize the importance of leveraging innovative technologies to drive digital transformation and achieve cost efficiency. How do organizations avoid the digital risks of ‘technology misuse’ and achieve efficient innovation that ‘technology promotes production’?

Digital Transformation 75

Digital Transformation Insurance Optimization ROI 75

CIO Business Intelligence

APRIL 19, 2023

Moving data into a cloud-based environment enables faster data sharing, improves workflows, and can ease workloads on mainframe systems and data centers. But moving critical infrastructure out of the data center is a process that is easier said than done. Enterprises store a vast amount of data.

Digital Transformation 98

Digital Transformation Data Governance Unstructured Data Risk 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

Ontotext

FEBRUARY 12, 2024

As discussed in part one, the data mesh paradigm is still a relatively new concept with implementations in the early stages. Most enterprises have years of legacy systems, processes, and practices that make it more demanding to quickly jump onto the data mesh bandwagon. For instance, JPMorgan Chase & Co.

Data Quality 69

Data Quality Data-driven Data Lake Data Governance 69

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

Ontotext

SEPTEMBER 1, 2023

Enterprises worldwide are analyzing Generative AI capabilities and seeking ways to leverage them for a variety of use cases to improve their competitive edge and incorporate automation and efficiency. Additionally, data is the fulcrum of AI, and the data used to train LLMs must be properly governed and controlled.

Risk 52

Risk Modeling Data Quality Data Governance 52

IBM Big Data Hub

JANUARY 25, 2024

Considering that IDC surveyed 37% of companies that manage spare parts inventory by using spreadsheets, email, shared folders or an uncertain approach, it becomes evident that this practice carries more risk than it might seem. Master data enrichment to enhance categorization and materials attributes.

Optimization 81

Optimization Cost-Benefit Prescriptive Analytics Manufacturing 81