O'Reilly on Data

JULY 28, 2020

Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. 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.

Marketing 361

Marketing Experimentation Metrics Testing 361

Smart Data Collective

OCTOBER 8, 2023

Methodologies in Deploying Data Analytics The application of data analytics in fast food legal cases requires a thorough understanding of the methodologies involved. This involves data collection , data cleaning, data analysis, and data interpretation.

Data Analytics 93

Data Analytics Analytics Statistics Data Collection 93

Rocket-Powered Data Science

JUNE 17, 2022

Here is a list of my top moments, learnings, and musings from this year’s Splunk.conf : Observability for Unified Security with AI (Artificial Intelligence) and Machine Learning on the Splunk platform empowers enterprises to operationalize data for use-case-specific functionality across shared datasets. is here, now!

Machine Learning 238

Machine Learning Recreation/Entertainment Risk Business Objectives 238

IBM Big Data Hub

SEPTEMBER 28, 2023

This process is designed to help mitigate risks so that model outputs can be deployed responsibly with the assistance of watsonx.data and watsonx.governance (coming soon). Building transparency into IBM-developed AI models To date, many available AI models lack information about data provenance, testing and safety or performance parameters.

Testing 88

Testing Finance Enterprise Modeling 88

CIO Business Intelligence

MARCH 30, 2022

But that takes a deep understanding of the decision-making process, the risks and rewards of each decision, the acceptable margin of error, and the ability to figure how confident you should be in any decision offered by your automated decision processes. Risk scoring traditionally involved a series of if-then decisions.

Machine Learning 142

Machine Learning Testing Risk Data-driven 142

IBM Big Data Hub

MAY 28, 2024

A good DLM process can help organize and structure critical data, particularly when organizations rely on diverse types of data storage. It can also help them reduce vulnerabilities and ensure data is efficiently managed, compliant with regulations, and not at risk of misuse or loss.

Strategy 73

Strategy Measurement Risk Cost-Benefit 73

IBM Big Data Hub

SEPTEMBER 7, 2023

IBM’s watsonx AI and data platform lets you go beyond being an AI user and become an AI value creator. Since the Granite models will be available to clients to adapt to their own applications, every dataset that is used in training undergoes a defined governance, risk and compliance (GRC) review process. Test out watsonx.ai

Modeling 102

Modeling Risk Unstructured Data Enterprise 102

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 292

Consulting Risk Cost-Benefit Modeling 292

Rocket-Powered Data Science

JULY 21, 2023

From these data streams, real-time actionable insights can feed decision-making and risk mitigations at the moment of need. testing for hypothesized threats, behaviors, and activities), (2) Baseline (i.e., search for deviations from normal behaviors through EDA: Exploratory Data Analysis), and (3) M-ATH (i.e.,

Machine Learning 190

Machine Learning Metrics Reporting Internet of Things 190

Smart Data Collective

FEBRUARY 14, 2023

They test the product and find bugs that turn customers away. Game analysts are exclusively engaged in testing and reporting, and the elimination of identified problems falls on the shoulders of the development team. Creation of hypotheses and their testing. A/B testing is mandatory to check the viability of the idea.

Big Data 117

Big Data Data Analytics Analytics Testing 117

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 343

Machine Learning Statistics Data Quality Modeling 343

IBM Big Data Hub

MARCH 20, 2024

Development and testing A public cloud setting offers an ideal environment for developing and testing new applications compared to the traditional waterfall method, which can be far costlier and more time-consuming. When developers finish using a testing environment, they can easily take it down.

Internet of Things 90

Internet of Things Cost-Benefit Data Processing IoT 90

datapine

MAY 2, 2023

Your Chance: Want to test a professional logistics analytics software? 10 Essential Big Data Use Cases in Logistics Now that you’re up to speed on the perks of investing in analytics, let’s look at some practical examples that highlight the growing importance of data in logistics, based on different business scenarios.

Big Data 275

Big Data Cost-Benefit Internet of Things Optimization 275

Smart Data Collective

JULY 9, 2023

Collecting Relevant Data for Conversion Rate Optimization Here is some vital data that e-commerce businesses need to collect to improve their conversion rates. Identifying Key Metrics for Conversion Rate Optimization Data collection and analysis are both essential processes for optimizing your conversion rate.

Optimization 73

Optimization Data Analytics Analytics Data-driven 73

Cloudera

MARCH 18, 2021

The Fundamental Review of the Trading Book (FRTB), introduced by the Basel Committee on Banking Supervision (BCBS), will transform how banks measure risk. In order to help make banks more resilient to drastic market changes, it will impose capital requirements that are more closely aligned with the market’s actual risk factors.

Risk 55

Risk Machine Learning Risk Management Measurement 55

datapine

JANUARY 6, 2022

Qualitative data, as it is widely open to interpretation, must be “coded” so as to facilitate the grouping and labeling of data into identifiable themes. Frequency distribution is extremely keen in determining the degree of consensus among data points. What is the keyword? Dependable. minimal growth).

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246

CIO Business Intelligence

JULY 17, 2023

Picture years and years of paper Until recently, ZEISS’s highly regulated manufacturing environment relied heavily on two documentation types: Digital History Records (DHR) to validate data for compliance and Work Instruction documentation to stipulate the required steps in performing specific activities. Reams of it, in fact.

Manufacturing 74

Manufacturing Snapshot Uncertainty Digital Transformation 74

Smart Data Collective

AUGUST 2, 2022

Companies that fail to leverage AI effectively risk falling behind in a competitive industry. Vehicle data processing allows to increase industry standards and design better solutions for maximum benefits. Data collected with these technologies provide insights for autonomous driving solutions.

Software 126

Software Machine Learning B2B Manufacturing 126

CIO Business Intelligence

JANUARY 3, 2024

At the planning stage, this can enable plan simulation and various what-if scenario testing prior to committing to real-world investment. According to Rapos, early incorporation allows for better data collection, more accurate modeling, and immediate feedback during the construction or development phase.

Cost-Benefit 115

Cost-Benefit ROI Manufacturing Optimization 115

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 167

Insurance Metadata Data Collection Marketing 167

DataRobot

OCTOBER 20, 2021

Because of the multidisciplinary nature of AI products, stakeholders across an entire organization must share a common understanding of each project’s scope, deployment, governance , impact, and projected risk. Achieving that level of governance at scale requires a common understanding of AI and data concepts. WHITE PAPER.

Machine Learning 52

Machine Learning Metrics Risk Deep Learning 52

CIO Business Intelligence

MAY 16, 2023

Big Data collection at scale is increasing across industries, presenting opportunities for companies to develop AI models and leverage insights from that data. Regulation: Lawmakers worldwide are considering privacy legislation and other rules that could limit the scope of data collection and AI use cases.

Advertising 79

Advertising Recreation/Entertainment Experimentation Enterprise 79

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. Load the dataset into Amazon S3.

Snapshot 84

Snapshot Data Lake Testing Strategy 84

IBM Big Data Hub

JUNE 14, 2023

Cloud computing helps organizations manage data collection and storage remotely, eliminating the need for on-premises software and hardware and increasing data visibility in the supply chain. This can help reduce the time and cost associated with manual processes, while also improving accuracy and reducing the risk of errors.

Manufacturing 72

Manufacturing Technology Internet of Things Cost-Benefit 72

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

AUGUST 24, 2022

This data is integrated with a range of other data points, providing easy-to-use visuals for plant operators to analyze, Melkote says. They can quickly assess potential hazards and risks in real-time and proactively take preventive actions.”. In August 2021, Owens Corning set developing the loss prevention platform.

Manufacturing 82

Manufacturing Risk Digital Transformation Data-driven 82

DataKitchen

MARCH 16, 2023

Errors can originate from various sources, including data collection, integration, models, visualization, governance, and security. Organizations will make better-informed, data-driven decisions by minimizing errors and avoiding the negative consequences of relying on inaccurate information.

Metrics 130

Metrics Data Analytics Analytics Measurement 130

Ontotext

FEBRUARY 12, 2024

This calls for additional planning, documentation, and testing. A data mesh will likely require more engineers to get started, so a critical mass is needed for successful adoption. Each team should be accountable for providing their prepared data sets to downstream systems. For instance, JPMorgan Chase & Co.

Data Quality 69

Data Quality Data-driven Data Lake Data Governance 69

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

FineReport

APRIL 15, 2020

In the United States, White House has asked the nation’s nearly 4,700 hospitals to submit the daily patients’ data via email, including how many patients have been tested for coronavirus, . However, in this way, the data gathering is time-consuming, and it is hard to do statistics because of the ununified data formats. .

Visualization 52

Visualization Dashboards Statistics Data Collection 52

Smart Data Collective

DECEMBER 17, 2020

When clinicians have an opportunity to review this data during the diagnostic process, they can create a more effective treatment strategy. The risk of medical errors is also significantly reduced. As a result, patients don’t have to do the same lab tests multiple times, even if they treat several diseases at once.

Data-driven 116

Data-driven Big Data Software Risk 116

CIO Business Intelligence

SEPTEMBER 2, 2022

The average salary for a financial software engineer is $116,670 per year, with a reported salary range of $85,000 to $177,000 per year, according to data from Glassdoor. Full-stack software engineers are essentially high-level software engineers who are focused on designing, testing, and implementing software applications.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

The average salary for a financial software engineer is $116,670 per year, with a reported salary range of $85,000 to $177,000 per year, according to data from Glassdoor. Full-stack software engineers are essentially high-level software engineers who are focused on designing, testing, and implementing software applications.

Finance 98

Finance IT Software Reporting 98

CDW Research Hub

NOVEMBER 6, 2020

Every year companies invest resources on data collection, and employees spend countless hours mulling over that data to make informed business decisions like how to market to their target audience or where to expand the business. Will just any data protection solution get the job done? Know your security risks.

Scorecard 40

Scorecard Risk Business Driver Strategy 40

CIO Business Intelligence

SEPTEMBER 8, 2022

Most organizations understand the profound impact that data is having on modern business. 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.

Cost-Benefit 101

Cost-Benefit Internet of Things Data-driven Data Lake 101

CIO Business Intelligence

AUGUST 25, 2023

This is largely due to bandwidth issues, as healthcare providers are always in firefighting mode and data management takes a backseat to saving a human life. The need is for a user-friendly system that captures all the data. Initiatives like Ayushman Bharat or National Digital Health Mission are a step towards formal data collection.

Experimentation 80

Experimentation Digital Transformation Technology Measurement 80

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