O'Reilly on Data

JULY 28, 2020

This isn’t always simple, since it doesn’t just take into account technical risk; it also has to account for social risk and reputational damage. A product needs to balance the investment of resources against the risks of moving forward without a full understanding of the data landscape. Data Quality and Standardization.

Marketing 362

Marketing Experimentation Metrics Testing 362

Alation

JULY 15, 2022

I recently led an online session, Data Monetisation and Governance , looking at the evolution of data governance , defining data ethics (from the Turing Institute ), and touching on the balancing act between using data to monetise (by increasing revenue, decreasing spend, or mitigating risk) and meeting ethical obligations.

Cost-Benefit 89

Cost-Benefit Data Governance ROI Risk 89

CIO Business Intelligence

NOVEMBER 22, 2022

As a result, a growing number of IT leaders are looking for data strategies that will allow them to manage the massive amounts of disparate data located in silos without introducing new risk and compliance challenges. Data collection and management shouldn’t be classified as just another project, Gusher notes.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

O'Reilly on Data

OCTOBER 22, 2020

The safest course of action is also the slowest and most expensive: obtain your training data as part of a collection strategy that includes efforts to obtain the correct representative sample under an explicit license for use as training data. How I use it: I like to ask this as early as possible.

Consulting 296

Consulting Risk Cost-Benefit Modeling 296

FineReport

MARCH 24, 2024

They identify and interpret trends in complex datasets, optimize statistical results, and maintain databases while devising new data collection processes. Additionally, they facilitate organizational risk assessments, provide consulting services to leadership, and mentor junior analysts. JPMorgan Chase & Co.:

Statistics 52

Statistics Data mining Visualization Reporting 52

Anmut

OCTOBER 29, 2020

As a result, concerns of data governance and data quality were ignored. The direct consequence of bad quality data is misinformed decision making based on inaccurate information; the quality of the solutions is driven by the quality of the data. COVID-19 exposes shortcomings in data management.

Data Governance 52

Data Governance Data Collection Data-driven Statistics 52

CIO Business Intelligence

SEPTEMBER 8, 2022

In Foundry’s 2022 Data & Analytics Study , 88% of IT decision-makers agree that data collection and analysis have the potential to fundamentally change their business models over the next three years. The ability to pivot quickly to address rapidly changing customer or market demands is driving the need for real-time data.

Cost-Benefit 114

Cost-Benefit Internet of Things Data-driven Data Lake 114

CIO Business Intelligence

SEPTEMBER 2, 2022

Finance companies collect massive amounts of data, and data engineers are vital in ensuring that data is maintained and that there’s a high level of data quality, efficiency, and reliability around data collection.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

Finance companies collect massive amounts of data, and data engineers are vital in ensuring that data is maintained and that there’s a high level of data quality, efficiency, and reliability around data collection.

Finance 98

Finance IT Software Reporting 98

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

O'Reilly on Data

MARCH 31, 2020

Because it’s so different from traditional software development, where the risks are more or less well-known and predictable, AI rewards people and companies that are willing to take intelligent risks, and that have (or can develop) an experimental culture. If you can’t walk, you’re unlikely to run.

Management 332

Management Machine Learning Experimentation Metrics 332

DataKitchen

MARCH 16, 2023

Under Efficiency, the Number of Data Product Owners metric measures the value of the business’s data products. Under Quality, the Data Quality Incidents metric measures the average data quality of datasets, while the Active Daily Users metric measures user activity across data platforms.

Metrics 130

Metrics Data Analytics Analytics Measurement 130

Cloudera

FEBRUARY 14, 2018

operations, and our CISO’s team while we invest in and form a stronger data and analytics team. their customer insights, connected products, risk mitigation). Mitigate risk to Cloudera’s business – for example in the area of Cybersecurity, and to ensure compliance with regulatory and consumer privacy policies and concerns.

Data-driven 44

Data-driven Data Quality Risk Interactive 44

Alation

FEBRUARY 13, 2020

Benefits of a Data Catalog. What Does a Data Catalog Do? A modern data catalog includes many features and functions that all depend on the core capability of cataloging data—collecting the metadata that identifies and describes the inventory of shareable data. Benefits of a Data Catalog. Conclusion.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

Sisense

SEPTEMBER 3, 2020

Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization. Data analysts in one organization might be called data scientists or statisticians in another. See an example: Explore Dashboard.

Statistics 97

Statistics Metrics Visualization Finance 97

FineReport

MAY 31, 2023

Finance and accounting teams often deal with data residing in multiple systems, such as accounting software, ERP systems, spreadsheets, and data warehouses. Ensuring seamless data integration and accuracy across these sources can be complex and time-consuming.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

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 309

Enterprise Deep Learning Data Governance Risk 309

CIO Business Intelligence

JANUARY 30, 2024

Birgit Fridrich, who joined Allianz as sustainability manager responsible for ESG reporting in late 2022, spends many hours validating data in the company’s Microsoft Sustainability Manager tool. Data quality is key, but if we’re doing it manually there’s the potential for mistakes.

Reporting 106

Reporting Data Quality Strategy Data-driven 106

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. This is where the process efficiency impacts good data collection.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

Domino Data Lab

FEBRUARY 4, 2019

Eric’s article describes an approach to process for data science teams in a stark contrast to the risk management practices of Agile process, such as timeboxing. As the article explains, data science is set apart from other business functions by two fundamental aspects: Relatively low costs for exploration.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Domino Data Lab

MARCH 3, 2019

Then, when we received 11,400 responses, the next step became obvious to a duo of data scientists on the receiving end of that data collection. Over the past six months, Ben Lorica and I have conducted three surveys about “ABC” (AI, Big Data, Cloud) adoption in enterprise.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Domino Data Lab

JUNE 23, 2019

If you have a user facing product, the data that you had when you prototype the model may be very different from what you actually have in production. This really rewards companies with an experimental culture where they can take intelligent risks and they’re comfortable with those uncertainties.

Management 110

Management Machine Learning Experimentation Metrics 110

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

IBM Big Data Hub

SEPTEMBER 11, 2023

A pain point tracker (a repository of business, human-centered design and technology issues that inhibit users’ ability to execute critical tasks) captures themes that arise during the data collection process. The pain point tracker clusters the foundational data in which value metrics are then applied.

Data-driven 90

Data-driven IT Measurement Cost-Benefit 90

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. One is data quality, cleaning up data, the lack of labelled data.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

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. Security: It must serve data throughout a system.

Data Governance 83

Data Governance Metadata Data-driven Enterprise 83

Andrew White

JANUARY 9, 2022

– We see most, if not all, of data management being augmented with ML. Much as the analytics world shifted to augmented analytics, the same is happening in data management. You can find research published on the infusion of ML in data quality, and also data catalogs, data discovery, and data integration.

Analytics 64

Analytics Measurement Modeling Data-driven 64

datapine

AUGUST 29, 2022

The book has three main ideas: The biggest risk your company faces is investing a lot of time and resources into building something that the market doesn’t want. Most people are aware that companies collect our GPS locale, text messages, credit card purchases, social media posts, Google search history, etc.,

Big Data 263

Big Data Data Analytics Analytics Data mining 263

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

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

datapine

FEBRUARY 22, 2022

Improved risk management: Another great benefit from implementing a strategy for BI is risk management. Before going all-in with data collection, cleaning, and analysis, it is important to consider the topics of security, privacy, and most importantly, compliance. Clean data in, clean analytics out.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

Alation

MARCH 5, 2021

How Alation Activates Data Governance. Why is Data Governance Important? As data collection and storage grow, so too does the need for data governance. Where data governance once focused primarily on compliance, the age of big data has broadened its applications. Data Governance Roles.

Data Governance 59

Data Governance Data Quality Dashboards Risk 59

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

Key considerations for data democratization As more organizations seek to evolve toward a culture of data democratization and build the architecture to support a data literate culture, they’ll realize several benefits—and encounter a few challenges along the way.

Data Architecture 64

Data Architecture Data Lake Machine Learning Data Governance 64

O'Reilly on Data

MARCH 24, 2020

Beyond the autonomous driving example described, the “garbage in” side of the equation can take many forms—for example, incorrectly entered data, poorly packaged data, and data collected incorrectly, more of which we’ll address below. Data collected for one purpose can have limited use for other questions.

Machine Learning 346

Machine Learning Statistics Data Quality Modeling 346

Alation

OCTOBER 12, 2021

Folks can work faster, and with more agility, unearthing insights from their data instantly to stay competitive. Yet the explosion of data collection and volume presents new challenges. There are inconsistent definitions and inconsistent metrics, and a lack of trust in the data used in the metrics.

Strategy 52

Strategy Enterprise Analytics Data Governance 52

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. The Right Tools.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98