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 100

Data Governance Enterprise Data Quality Metadata 100

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

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 101

Data Governance Unstructured Data Metadata Data Lake 101

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

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

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 59

Data-driven Enterprise Data Governance Data Lake 59

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. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Alation

MAY 20, 2021

Alation has upgraded search with ranking that weights valuable social signals, and a new view that shares metadata alongside results. 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.

Enterprise 52

Enterprise Metadata Data Quality Machine Learning 52

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

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

erwin

MARCH 30, 2020

To marry the epidemiological data to the population data it will require a tremendous amount of data intelligence about the: Source of the data; Currency of the data; Quality of the data; and. Unraveling Data Complexities with Metadata Management. Data lineage to support impact analysis.

Metadata 122

Metadata IT Data Governance Data Quality 122

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. The unified need Despite these criticisms, the need for unified, integrated data solutions at the enterprise level remains.

Insurance 98

Insurance Strategy Data Governance Data Integration 98

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 69

Data Governance Data Quality Insurance Predictive Analytics 69

erwin

DECEMBER 3, 2020

Ultra Mobile recently shared how it uses erwin Data Intelligence (erwin DI) as part of a modern, ongoing approach to data governance and therefore control versus chaos. To manage not only risk but also to grow and compete effectively requires the ability to deal with both planned and unplanned change.

Metadata 141

Metadata Data Governance Data-driven Digital Transformation 141

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. The latter is essential for Generative AI implementations.

Strategy 289

Strategy Experimentation Uncertainty Machine Learning 289

Ontotext

MAY 2, 2024

Data-centric approach In the data-centric approach, metadata serves as a layer of interoperability between the data sources. It also enables business teams to have their data at their fingertips and have a uniform view of it. Here we talk about metadata management, catalog of catalogs, and so on.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

erwin

APRIL 29, 2020

Many large organizations, in their desire to modernize with technology, have acquired several different systems with various data entry points and transformation rules for data as it moves into and across the organization. Who are the data owners? Data lineage offers proof that the data provided is reflected accurately.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

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

Octopai

JUNE 19, 2023

Data Catalogs also allow for Improved Collaboration by serving as a central repository for enterprise data, a data catalog facilitates collaboration among different teams. Everyone has access to the same data and the same understanding of what the data represents, reducing miscommunications and discrepancies.

Metadata 88

Metadata Data Governance Measurement Risk Management 88

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. So questions linger about whether transformed data can be trusted. Data Quality Obstacles.

Data Governance 40

Data Governance Risk Metadata Management 40

Alation

APRIL 18, 2023

For any data user in an enterprise today, data profiling is a key tool for resolving data quality issues and building new data solutions. In this blog, we’ll cover the definition of data profiling, top use cases, and share important techniques and best practices for data profiling today.

IT 52

IT Metadata Data Quality Data Governance 52

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

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

CIO Business Intelligence

APRIL 29, 2022

Preparing for an artificial intelligence (AI)-fueled future, one where we can enjoy the clear benefits the technology brings while also the mitigating risks, requires more than one article. This first article emphasizes data as the ‘foundation-stone’ of AI-based initiatives. Establishing a Data Foundation. era is upon us.

Data Governance 145

Data Governance IT Risk Data Lake 145

erwin

JANUARY 30, 2020

Digital transformation and data standards/uniformity round out the top five data governance drivers, with 37 and 36 percent, respectively. Constructing a Digital Transformation Strategy: How Data Drives Digital. However, more than 50 percent say they have deployed metadata management, data analytics, and data quality solutions.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

Ontotext

JULY 6, 2023

In today’s fast changing environment, enterprises that have transitioned from being focused on applications to becoming data-driven gain a significant competitive edge. internal metadata, industry ontologies, etc.) Transaction and pricing data (e.g., Knowledge organization (e.g., M&A events, role changes, etc.)

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 52

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

AUGUST 7, 2019

A data catalog benefits organizations in a myriad of ways. 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.

Metadata 90

Metadata Data Governance Data Quality Data Warehouse 90

Octopai

JANUARY 21, 2020

How much time has your BI team wasted on finding data and creating metadata management reports? BI groups spend more than 50% of their time and effort manually searching for metadata. In fact, BI projects used to take many months to complete and require huge numbers of IT professionals to extract data.

OLAP 56

OLAP Metadata Online Analytical Processing Data Quality 56

erwin

MARCH 8, 2019

Following are two examples that illustrate the data governance stock check, including the Any 2 approach in action, based on real consulting engagements. Then the metadata is classified against a semantic model held in a business glossary. This, among other safeguards, ensures data quality.

Data Governance 65

Data Governance Metadata Data Warehouse Data Quality 65

Domino Data Lab

OCTOBER 1, 2020

Combining the power of Domino Data Labs with Okera, your data scientists only get access to the columns, rows, and cells allowed, easily removing or redacting sensitive data such as PII and PHI not relevant to training models. For the compliance team, the combination of Okera and Domino Data Lab is extremely powerful.

Enterprise 105

Enterprise Metadata Cost-Benefit Data Processing 105

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

Ontotext

APRIL 21, 2021

Ontotext clients have used enterprise knowledge graphs to ensure inventory control is done in an intelligent and automated way. Inventory here refers to the vast amounts of information and data that financial institutions need on a daily basis, which are core assets to the business. Manage Regulation, Manage Risk.

Metadata 59

Metadata Finance Cost-Benefit Risk 59

Octopai

MAY 31, 2022

The ultimate data organizational tool, letting any data user in your organization easily see what data assets you have and all the pertinent details about them, is a data catalog. Bonus tool: active metadata management. An active metadata management tool adds a maître d’ to self-serve analytics.

Management 52

Management Metadata Business Intelligence ROI 52

erwin

APRIL 16, 2021

For a fully mature or “enhanced” data governance program, IT and the business need to take responsibility for selling the benefits of data governance across the enterprise and ensure all stakeholders are properly educated about it. used erwin Data Intelligence for its digital transformation and innovation efforts.

Data Governance 128

Data Governance Metadata Cost-Benefit Digital Transformation 128

Alation

OCTOBER 5, 2021

Yet there is often lack of awareness of the trustworthiness (or lack thereof) of the data that these algorithms are being trained on. It is commonplace for a company to create an enterprise data governance strategy that fails to even consider the end user. Data governance and AI. Develop measurable KPIs.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

Alation

MARCH 22, 2022

As the latest iteration in this pursuit of high-quality data sharing, DataOps combines a range of disciplines. It synthesizes all we’ve learned about agile, data quality , and ETL/ELT. So, how can you quickly take advantage of the DataOps opportunity while avoiding the risk and costs of DIY?

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52