CDW Research Hub

NOVEMBER 29, 2021

Data collection: IoT infrastructure often serves as the nucleus to integrate data from multiple sensors— and this data must be modeled processed to achieve your desired outcome. Data modeling: Modeling is necessary to normalize this data across all platforms and sensor groups.

IoT 89

IoT Cost-Benefit Internet of Things ROI 89

O'Reilly on Data

MARCH 31, 2020

That foundation means that you have already shifted the culture and data infrastructure of your company. Although machine learning projects differ in subtle ways from traditional projects, they tend to require similar infrastructure, similar data collection processes, and similar developer habits. What delivers the greatest ROI?

Management 327

Management Machine Learning Experimentation Metrics 327

IBM Big Data Hub

AUGUST 4, 2023

Risk of data swamps A data swamp is the result of a poorly managed data lake that lacks appropriate data quality and data governance practices to provide insightful learnings, rendering the data useless. MLOps creates a process where it’s easier to cull insights from business data.

Data Architecture 60

Data Architecture Data Lake Machine Learning Data Governance 60

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

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

Occam's Razor

AUGUST 13, 2012

The questions reveal a bunch of things we used to worry about, and continue to, like data quality and creating data driven cultures. Bjoern Sjut3: My main issue at the moment: How will multi-channel funnels and ROI calculations work in a multi device world? They also reveal things that starting to become scary (Privacy!

Modeling 124

Modeling Metrics Data Quality Data-driven 124

FineReport

MAY 31, 2023

Dupont Analysis Dashboard FineReport simplifies the implementation of the Dupont analysis model, enabling an in-depth examination of an enterprise’s financial condition through Return on Investment (ROI). Ensuring seamless data integration and accuracy across these sources can be complex and time-consuming.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

Domino Data Lab

JUNE 23, 2019

And then you’ll do a lot of work to get it out and then there’ll be no ROI at the end. The biggest time sink is often around data collection, labeling and cleaning. ” There’s either incomplete data, missing tracking data or duplicative tracking data, things like that.

Management 110

Management Machine Learning Experimentation Metrics 110

Domino Data Lab

FEBRUARY 4, 2019

Of course, some questions in business cannot be answered with historical data. Instead they require investment, tooling, and time for data collection. Given the two points above, that’s okay—there are good ways to direct data exploration toward ROI. Lack of data, or data quality issues (silos).

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

Occam's Razor

APRIL 21, 2014

Grow traffic first, with even with bad measurement I can find positive ROI areas for growth or invest time getting Analytics in order first for more objective decision making? We wonder why data people are not loved. :). Both are large scale issues requiring buy in from execs and multiple departments. Six years go by.

Marketing Analytics 131

Marketing Analytics Marketing Analytics Measurement 131

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