CDW Research Hub

NOVEMBER 29, 2021

The CompTIA IoT Advisory Council recently published a white paper called The Six Layers of an IoT Solution guide, which breaks down these layers and provides overarching guidance on IoT security to give IT solution practitioners more holistic knowledge of IoT solutions.

IoT 89

IoT Cost-Benefit Internet of Things ROI 89

DataKitchen

MARCH 16, 2023

What are the metrics that matter? Gartner attempted to list every metric under the sun in their recent report , “T oolkit: Delivery Metrics for DataOps, Self-Service Analytics, ModelOps, and MLOps, ” published February 7, 2023. For example, Gartner’s DataOps metrics can be categorized into Velocity, Efficiency, and Quality.

Metrics 130

Metrics Data Analytics Analytics Measurement 130

Jet Global

FEBRUARY 25, 2025

Data cleansing is the process of identifying and correcting errors, inconsistencies, and inaccuracies in a dataset to ensure its quality, accuracy, and reliability. This process is crucial for businesses that rely on data-driven decision-making, as poor data quality can lead to costly mistakes and inefficiencies.

Cost-Benefit 52

Cost-Benefit Data Collection Finance Reporting 52

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. Database design is often an important part of the business analyst role.

Statistics 97

Statistics Metrics Visualization Finance 97

Ontotext

NOVEMBER 16, 2023

Data mesh solves this by promoting data autonomy, allowing users to make decisions about domains without a centralized gatekeeper. It also improves development velocity with better data governance and access with improved data quality aligned with business needs.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

Alation

JANUARY 26, 2023

Offer the right tools Data stewardship is greatly simplified when the right tools are on hand. So ask yourself, does your steward have the software to spot issues with data quality, for example? 2) Always Remember Compliance Source: Unsplash There are now many different data privacy and security laws worldwide.

Data Governance 52

Data Governance Strategy Data Quality Data Collection 52

CIO Business Intelligence

MARCH 29, 2022

Lowering the entry cost by re-using data and infrastructure already in place for other projects makes trying many different approaches feasible. Fortunately, learning-based projects typically use data collected for other purposes. . And the problem is not just a matter of too many copies of data.

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 52

Andrew White

JANUARY 9, 2022

I try to relate as much published research as I can in the time available to draft a response. – In the webinar and Leadership Vision deck for Data and Analytics we called out AI engineering as a big trend. – In the webinar and Leadership Vision deck for Data and Analytics we called out AI engineering as a big trend.

Analytics 64

Analytics Measurement Data-driven Modeling 64

Domino Data Lab

MARCH 3, 2019

This month, the theme is not specifically about conference summaries; rather, it’s about a set of follow-up surveys from Strata Data attendees. We had big surprises at several turns and have subsequently published a series of reports. Evolving Data Infrastructure: Tools and Best Practices for Advanced Analytics and AI (Jan 2019).

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Occam's Razor

DECEMBER 12, 2016

Data quality plays a role into this. And, most of the time, regardless of the size of the size of the company, you only know your code is not working post-launch when data is flowing in (not!). You got me, I am ignoring all the data layer and custom stuff! All that is great.

Analytics 142

Analytics Data-driven Strategy Consulting 142

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

Depict Data Studio

MAY 12, 2020

Amanda said, “There are different points in which we make decisions about how and what we visualize, and then how we publish and share. Amanda went through some of the top considerations, from data quality, to data collection, to remembering the people behind the data, to color choices.

Visualization 52

Visualization Uncertainty Data Collection Data Quality 52

Domino Data Lab

FEBRUARY 4, 2019

In other words, your talk didn’t quite stand out enough to put onstage, but you still get “publish or perish” credits for presenting. These two points provide a different kind of risk management mechanism which is effective for science, specifically data science. Instead they require investment, tooling, and time for data collection.

Data Science 66

Data Science Experimentation Machine Learning Data-driven 66

Domino Data Lab

JULY 22, 2019

One is data quality, cleaning up data, the lack of labelled data. Frankly, leading data science teams early on, you almost always had to struggle against the BI teams. It was also the year, 2001, when “ Agile Manifesto ” was published. They’re years away from being up to that point.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

The Unofficial Google Data Science Blog

JULY 18, 2023

Measurement challenges Assessing reliability is essentially a process of data collection and analysis. To do this, we collect multiple measurements for each unit of observation, and we determine if these measurements are closely related. Both published articles in the same volume of the British Journal of Psychology.

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 52

Jet Global

APRIL 14, 2022

Having accurate data is crucial to this process, but finance teams struggle to easily access and connect with data. Improve data quality. Δ The post Automate Your Yardi Real Estate Data Collection and Management appeared first on insightsoftware. Near real-time information is vital to: Save time.

Data Collection 52

Data Collection Management Finance Reporting 52

datapine

AUGUST 29, 2022

Due to this book being published recently, there are not any written reviews available. 4) Big Data: Principles and Best Practices Of Scalable Real-Time Data Systems by Nathan Marz and James Warren. and this book will give you an insight into their data collecting procedures and the reasons behind them.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Jet Global

MAY 9, 2024

ETL pipelines are commonly used in data warehousing and business intelligence environments, where data from multiple sources needs to be integrated, transformed, and stored for analysis and reporting. Technologies used for data ingestion include data connectors, ingestion frameworks, or data collection agents.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

MARCH 4, 2024

Companies will have to publish their first sustainability reports under the new standards by as soon as 2025 1. What is the best way to collect the data required for CSRD disclosure? Offering a validation and quality assurance service to check the accuracy and consistency of your XBRL tags, and alert you of any errors or issues.

Reporting 52

Reporting Management Cost-Benefit Publishing 52

Jet Global

MARCH 4, 2024

Moving data across siloed systems is time-consuming and prone to errors, hurting data quality and reliability. Built on proven technology trusted by thousands, it delivers investor-grade data with robust controls, audit trails, and security. It’s not just a solution, it’s a partnership for a greener future.

Reporting 52

Reporting Data-driven Metrics Software 52

Jet Global

MAY 16, 2022

And using data collected during a close to make smart company decisions outside of finance is an emerging expectation for the Office of the CFO. This means real-time validation on XBRL documents to instantly flag any errors to improve overall quality in first and subsequent filings.

Finance 52

Finance Reporting Management Software 52

CIO Business Intelligence

MAY 8, 2025

Whether youre developing large language models (LLMs), computer vision systems or specialized industry applications, the breadth and depth of training data directly impact a models capabilities, reliability, performance and consistency. Do we have enough data? The median training dataset contained about 3,300 datapoints in 2020.

Modeling 85

Modeling Cost-Benefit Data Collection Predictive Analytics 85