Anmut

OCTOBER 29, 2020

Although COVID-19 tracking data is highly complex and is subject to many data quality issues, it is still better to release good-enough data to inform decision making, rather than to take the risk of losing more lives without using any data. COVID-19 exposes shortcomings in data management.

Data Governance 52

Data Governance Data Collection Data-driven Statistics 52

O'Reilly on Data

MARCH 31, 2020

You might have millions of short videos , with user ratings and limited metadata about the creators or content. Job postings have a much shorter relevant lifetime than movies, so content-based features and metadata about the company, skills, and education requirements will be more important in this case.

Management 332

Management Machine Learning Experimentation Metrics 332

bridgei2i

MARCH 11, 2021

From eliminating the need for human assistance in repetitive tasks to reducing the risk of human errors in manual processes – AI can do a lot for large-scale businesses. With improved data cataloging functionality, their systems can become responsive. The post How Can Small Businesses Benefit from an AI Data Company?

Key Performance Indicator 52

Key Performance Indicator Data Governance Data Lake Metadata 52

IBM Big Data Hub

FEBRUARY 14, 2024

The IBM team is even using generative AI to create synthetic data to build more robust and trustworthy AI models and to stand in for real-world data protected by privacy and copyright laws. These systems can evaluate vast amounts of data to uncover trends and patterns, and to make decisions.

Cost-Benefit 89

Cost-Benefit Insurance Unstructured Data Machine Learning 89

erwin

DECEMBER 20, 2018

The driving factors behind data governance adoption vary. Whether implemented as preventative measures (risk management and regulation) or proactive endeavors (value creation and ROI), the benefits of a data governance initiative is becoming more apparent. The Top 6 Benefits of Data Governance.

Data Governance 40

Data Governance ROI Risk Management Metadata 40

Alation

FEBRUARY 13, 2020

Today, we’re announcing that Alation has closed a $50 million Series C funding led by Sapphire Ventures, with participation from new investor Salesforce Ventures and our existing investors Costanoa Ventures, DCVC (Data Collective), Harmony Partners and Icon Ventures.

Enterprise 52

Enterprise Data Lake Machine Learning Data-driven 52

Peter James Thomas

AUGUST 29, 2018

However, in reality, the CDO role encompasses Enterprise Data Management, although generally speaking the EDM role includes responsibility for the day to day operations of the collection processes, which in my current role I don’t have. Helping organisations become “data-centric” is a key part of what you do.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

Ontotext

MAY 5, 2023

It is reused in modeling the publication of entity data or regulatory-mandated data exchange, as seen in the example provided below. Integrating reporting to move to a more streamlined, efficient approach to data collection. We think their adoption will bring benefits well beyond reporting.

Data Collection 64

Data Collection Risk Data-driven Interactive 64

O'Reilly on Data

MARCH 18, 2020

Whether it’s controlling for common risk factors—bias in model development, missing or poorly conditioned data, the tendency of models to degrade in production—or instantiating formal processes to promote data governance, adopters will have their work cut out for them as they work to establish reliable AI production lines.

Enterprise 311

Enterprise Deep Learning Data Governance Risk 311

IBM Big Data Hub

FEBRUARY 8, 2023

There is a growing need to proactively drive responsible, fair, and ethical decisions, designed to: Manage risk and reputation No organization wants to be in the news for the wrong reasons, and recently there have been a lot of stories in the press regarding issues of unfair, unexplainable, or biased AI.

Risk Management 52

Risk Management Risk Modeling Metadata 52

AWS Big Data

MARCH 26, 2024

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. We recommend building your data strategy around five pillars of C360, as shown in the following figure.

Data Strategy 72

Data Strategy Strategy Data Warehouse Prescriptive Analytics 72

O'Reilly on Data

JANUARY 28, 2019

Almost everyone who reads this article has consented to some kind of medical procedure; did any of us have a real understanding of what the procedure was and what the risks were? The problems with consent to data collection are much deeper. The problems with consent to data collection are much deeper.

Insurance 170

Insurance Metadata Data Collection Marketing 170

CIO Business Intelligence

JANUARY 30, 2024

Even for more straightforward ESG information, such as kilowatt-hours of energy consumed, ESG reporting requirements call for not just the data, but the metadata, including “the dates over which the data was collected and the data quality,” says Fridrich. “The complexity is at a much higher level.”

Reporting 115

Reporting Data Quality Strategy Data-driven 115

Cloudera

AUGUST 4, 2021

Data governance used to be considered a “nice to have” function within an enterprise, but it didn’t receive serious attention until the sheer volume of business and personal data started taking off with the introduction of smartphones in the mid-2000s.

Data Governance 87

Data Governance Metadata Data-driven Enterprise 87

Cloudera

DECEMBER 16, 2022

There are six key capabilities that cement our leadership in enterprise data platforms: 1-Hybrid and multi-cloud portability and scale to support the most demanding workloads. Anything else requires integration, sometimes between multiple vendors, which means complexity and risk. 4-Ready for modern data fabric architectures.

Management 92

Management Metadata Machine Learning Data Lake 92

Cloudera

JANUARY 21, 2021

And you also already know siloed data is costly, as that means it will be much tougher to derive novel insights from all of your data by joining data sets. Of course you don’t want to re-create the risks and costs of data silos your organization has spent the last decade trying to eliminate. Must you be: .

Data Lake 95

Data Lake Data Warehouse IT Analytics 95

erwin

MARCH 4, 2021

Modern data governance is a strategic, ongoing and collaborative practice that enables organizations to discover and track their data, understand what it means within a business context, and maximize its security, quality and value. Virginia residents also would be able to opt out of data collection.

Data Governance 122

Data Governance Digital Transformation Data-driven Cost-Benefit 122

erwin

APRIL 21, 2020

Another foundational purpose of a data catalog is to streamline, organize and process the thousands, if not millions, of an organization’s data assets to help consumers/users search for specific datasets and understand metadata , ownership, data lineage and usage. Clearly Document Data Policies and Rules.

Measurement 97

Measurement Sales Data Governance Metadata 97

erwin

APRIL 21, 2020

One of the biggest lessons we’re learning from the global COVID-19 pandemic is the importance of data, specifically using a data catalog to comply, collaborate and innovate to crisis-proof our businesses. So one of the biggest lessons we’re learning from COVID-19 is the need for data collection, management and governance.

Measurement 96

Measurement Sales Data Governance Metadata 96

Domino Data Lab

JULY 22, 2019

What I’m trying to say is this evolution of system architecture, the hardware driving the software layers, and also, the whole landscape with regard to threats and risks, it changes things. You see these drivers involving risk and cost, but also opportunity. How can you trace that all the way back into the data collection?

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Cloudera

JUNE 6, 2019

While this approach provides isolation, it creates another significant challenge: duplication of data, metadata, and security policies, or ‘split-brain’ data lake. Now the admins need to synchronize multiple copies of the data and metadata and ensure that users across the many clusters are not viewing stale information.

Metadata 87

Metadata Data Lake Optimization Strategy 87

Alation

FEBRUARY 20, 2020

For example, a risk insurance company that has sensitive customer information and transactional data, can store that information in an on-premise system. The cloud could then be leveraged for burst out scenarios, such as processing and adjusting risk policies around a real-time event (e.g. How to Catalog AWS S3 with Alation.

Data Lake 52

Data Lake ROI Metadata Cost-Benefit 52

AWS Big Data

FEBRUARY 21, 2023

Loading complex multi-point datasets into a dimensional model, identifying issues, and validating data integrity of the aggregated and merged data points are the biggest challenges that clinical quality management systems face. Additionally, scalability of the dimensional model is complex and poses a high risk of data integrity issues.

Data Warehouse 65

Data Warehouse Data Lake Cost-Benefit Modeling 65

AWS Big Data

JULY 3, 2023

Backtesting is a process used in quantitative finance to evaluate trading strategies using historical data. This helps traders determine the potential profitability of a strategy and identify any risks associated with it, enabling them to optimize it for better performance.

Snapshot 87

Snapshot Data Lake Testing Strategy 87

Alation

FEBRUARY 8, 2022

Middlemen — data engineering or IT teams — can’t possibly possess all the expertise needed to serve up quality data to the growing range of data consumers who need it. As data collection has surged, and demands for data have grown in the enterprise, one single team can no longer meet the data demands of every department.

Data Governance 52

Data Governance Data-driven Metadata Enterprise 52

Domino Data Lab

OCTOBER 9, 2019

We’ll examine National Oceanic and Atmospheric Administration (NOAA) data management practices which I learned about at their workshop, as a case study in how to handle data collection, dataset stewardship, quality control, analytics, and accountability when the stakes are especially high. Metadata Challenges.

Deep Learning 69

Deep Learning Metadata Machine Learning Data Science 69

Domino Data Lab

JANUARY 21, 2021

There is a risk of injecting bias. First, I load the dataset and do a quick check to see the size of the data we’re working with: Note: the full dataset, with data collection back to 1987, is significantly larger than 300,000 samples. Our customized profile, complete with key metadata and variable descriptions.

Statistics 106

Statistics Unstructured Data Data Science Predictive Modeling 106

Andrew White

JANUARY 9, 2022

Where these efforts break down is in the data that goes into the connection at one end and comes out the other. So, I hear you say, let’s share metadata and make the data self-describing. I would think a key importance would be how you generate and what data points are used to analyze especially if it is manually retrieved.

Analytics 64

Analytics Measurement Modeling Data-driven 64

Alation

DECEMBER 15, 2021

Modern business is built on a foundation of trusted data. Yet high-volume collection makes keeping that foundation sound a challenge, as the amount of data collected by businesses is greater than ever before. An effective data governance strategy is critical for unlocking the full benefits of this information.

Data Governance 52

Data Governance Strategy Metadata Data Strategy 52

Alation

NOVEMBER 11, 2021

Cloud data governance is a set of policies, rules, and processes that streamline data collection, storage, and use within the cloud. This framework maintains compliance and democratizes data. It enables collaboration, even as your data landscape grows larger and more complex. Data Sovereignty and Cross?Border

Data Governance 52

Data Governance Data Quality Metrics Metadata 52

Alation

JULY 6, 2021

There are new ways to quickly and effectively overcome these data governance challenges. A person or team with influence must take responsibility for reducing data governance risks. They should have resources, tools for connectivity and integration, and insights into data usage and needs. Why Do Data Silos Happen?

Data Governance 52

Data Governance Metadata Data Quality Risk 52

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. It uses knowledge graphs, semantics and AI/ML technology to discover patterns in various types of metadata.

Data Architecture 65

Data Architecture Data Lake Machine Learning Data Governance 65

erwin

JULY 17, 2019

EA and BP modeling squeeze risk out of the digital transformation process by helping organizations really understand their businesses as they are today. Once you’ve determined what part(s) of your business you’ll be innovating — the next step in a digital transformation strategy is using data to get there.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

Alation

AUGUST 26, 2021

What Is Data Intelligence? Data intelligence is a system to deliver trustworthy, reliable data. It includes intelligence about data, or metadata. IDC coined the term, stating, “data intelligence helps organizations answer six fundamental questions about data.” Yet finding data is just the beginning.

Metadata 64

Metadata Data Governance Dashboards Software 64

Jet Global

MAY 1, 2023

CEO Priorities Grow revenue and “hit the number” Manage costs and meet profitability goals Attract and retain talent Innovate and out-perform the competition Manage risk Connect the Dots Present embedded analytics as a way to differentiate from the competition and increase revenue. Let’s just give our customers access to the data.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52