Smart Data Collective

MAY 29, 2023

Understanding Bias in AI Translation Bias in AI translation refers to the distortion or favoritism present in the output results of machine translation systems. This bias can emerge due to multiple factors, such as the training data, algorithmic design, and human influence. AI translation models must collect and annotate data fairly.

Metrics 68

Metrics Measurement Data Collection Strategy 68

datapine

JULY 6, 2022

2) How To Measure Productivity? For years, businesses have experimented and narrowed down the most effective measurements for productivity. Use our 14-day free trial and start measuring your productivity today! In shorter words, productivity is the effectiveness of output; metrics are methods of measurement.

Measurement 243

Measurement Metrics KPI Sales 243

Smart Data Collective

OCTOBER 16, 2023

Examples include CCTV records, automated vacuum cleaners, weather station data, and other sensor-generated data. All in all, big data refers to massive data collections obtained from various sources. Big data can also be utilized to improve security measures.

Big Data 102

Big Data IoT Cost-Benefit Advertising 102

IBM Big Data Hub

FEBRUARY 9, 2023

Technology and data architecture play a crucial role in enabling data governance and achieving these objectives. Focus and prioritize what you’re delivering to the business, determine what you need, deliver and measure results, refine, expand, and deliver against the next priority objectives. Don’t try to do everything at once!

Data Governance 80

Data Governance Business Objectives Strategy Data Quality 80

O'Reilly on Data

JULY 28, 2020

These measures are commonly referred to as guardrail metrics , and they ensure that the product analytics aren’t giving decision-makers the wrong signal about what’s actually important to the business. When a measure becomes a target, it ceases to be a good measure ( Goodhart’s Law ). Any metric can and will be abused.

Marketing 362

Marketing Experimentation Metrics Testing 362

Smart Data Collective

AUGUST 25, 2022

IoT refers to any connected physical device that can send or receive data over the internet, including smartphones, computers, speakers, security cameras, thermostats, door locks, vehicles—the list goes on and on. For businesses, these considerations include data privacy, security, and liability.

IoT 127

IoT Internet of Things IT Manufacturing 127

Rocket-Powered Data Science

JULY 7, 2019

Such approaches can enable more accurate and faster modeling and analysis of the characteristics and behaviors of a system and can exploit data in intelligent ways to convert them to new capabilities, including decision support systems with the accuracy of full scale modeling, efficient data collection, management, and data mining.

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

IBM Big Data Hub

JANUARY 22, 2024

Put another way, it’s the person the data relates to. Say a company collects phone numbers to send marketing messages via SMS. The owners of those phone numbers would be data subjects. When the GDPR refers to data subjects, it means data subjects who reside in the EEA.

Measurement 86

Measurement Risk Data Processing Data Collection 86

FineReport

MARCH 7, 2024

Data Acquisition I categorize data sources into three types: (1) First-party data: User factual data, such as financial products purchased at a certain institution, time of purchase, issuing branch, name, phone number, or operational data, such as user behavioral data on a financial app. (2)

Dashboards 52

Dashboards Reporting Advertising Statistics 52

Smart Data Collective

MAY 4, 2023

UMass Global has a very insightful article on the growing relevance of big data in business. Big data has been discussed by business leaders since the 1990s. It refers to datasets too large for normal statistical methods. Furthermore, many websites have implemented anti-scraping measures to prevent bots from collecting data.

Data mining 78

Data mining Big Data Data-driven Measurement 78

CIO Business Intelligence

JULY 10, 2023

The choice for brands Regardless of what the regulators say, brands and retailers still need to take certain measures to ensure they can collect needed customer data in a safe and secure manner. Broadly speaking, those looking to gather customer data currently have two options.

Interactive 90

Interactive Measurement Data Collection Risk 90

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. The program must introduce and support standardization of enterprise data.

Data Governance 142

Data Governance Management Metadata Data Quality 142

Data Science 101

JANUARY 15, 2020

Bias ( syatematic unfairness in data collection ) can be a potential problem in experiments and we need to take it into account while designing experiments. Reliability: It means measurements should have repeatable results. For eg: you measure the blood pressure of a person. REFERENCES. McCabe & B.

Experimentation 96

Experimentation Statistics Measurement Testing 96

IBM Big Data Hub

FEBRUARY 7, 2024

” Similar to “carbon neutral” in the context of emissions, nature positive refers to stopping, avoiding and reversing environmental destruction. This can be quantified by measuring metrics like tree cover, habitat integrity and number of species, and is guided by sustainable development principles.

Reporting 96

Reporting Cost-Benefit Internet of Things Data-driven 96

FineReport

APRIL 9, 2021

However, companies operation generates numerous and complicated data every day, beyond traditional manual reporting capacity. If the financial analysis will go to non-financial professionals, the financial analysis report only needs conclusive key indicators and data. This article provides four ideas for reference.

Reporting 98

Reporting Finance Dashboards Enterprise 98

O'Reilly on Data

OCTOBER 16, 2018

Create a coherent BI strategy that aligns data collection and analytics with the general business strategy. They recognize the instrumental role data plays in creating value and see information as the lifeblood of the organization. That’s why decision-makers consider business intelligence their top technology priority.

Business Intelligence 149

Business Intelligence Data Science Descriptive Analytics Strategy 149

Smart Data Collective

MARCH 23, 2022

For instance, it is the same case with Amazon when they recommend related products, so the term “ basket” refers to what shoppers use the most when shopping. When possessing this type of data , you can predict future consumer behavior based on past purchases and preferences.

Data mining 121

Data mining Marketing Insurance Data Collection 121

CIO Business Intelligence

FEBRUARY 13, 2023

The name references the Greek letter sigma, which is a statistical symbol that represents a standard deviation. Measure performance of the current process by establishing a data collection plan to determine defects and gather metrics. Six Sigma was trademarked by Motorola in 1993.

Management 81

Management Statistics Manufacturing Measurement 81

Smart Data Collective

AUGUST 31, 2020

At Smart Data Collective, we have talked extensively about the benefits of big data in digital marketing. We have focused a lot on using data analytics for SEO. However, there are a lot of other benefits of using big data in marketing. You shouldn’t limit yourself to using data analytics in your SEO strategy.

Data-driven 86

Data-driven Marketing Big Data Broadcasting 86

O'Reilly on Data

MARCH 31, 2020

There may even be someone on your team who built a personalized video recommender before and can help scope and estimate the project requirements using that past experience as a point of reference. Measurement, tracking, and logging is less of a priority in enterprise software. If you can’t walk, you’re unlikely to run.

Management 332

Management Machine Learning Experimentation Metrics 332

Cloudera

AUGUST 6, 2021

Like most labels, “data-driven” is not a binary, black and white measure of capability. In reality, organizations live on a continuum, varying in how sophisticated their data is and the extents to which it influences management decisions. . One esoteric term leads to another. .

Data-driven 103

Data-driven B2B Data Strategy Strategy 103

The Unofficial Google Data Science Blog

JULY 18, 2023

E ven after we account for disagreement, human ratings may not measure exactly what we want to measure. Overview Human-labeled data is ubiquitous in business and science, and platforms for obtaining data from people have become increasingly common. And for thousands of years, measurement was as simple as this.

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 52

Alation

JANUARY 26, 2023

Below are some examples of common data governance goals: All data collection, storage, and usage must meet the terms of legislation. Avoid fines that could result from issues such as data leakage or lack of data minimization practices. This is “table stakes” for any data governance program!).

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

FineReport

MAY 26, 2020

Before doing data analysis, you should think about the purpose of data analysis and determine the scope of our analysis based on the purpose. Only when the scope is determined clearly, the results of data analysis can more accurately guide product improvement and solve practical problems. Collect Data.

Management 98

Management Optimization Measurement Data-driven 98

FineReport

MAY 27, 2022

An income statement, which also refers to a profit and loss report, shows an enterprise’s revenues, expenses, and net income in a certain period of time. Step 2: Collect financial data. Compared with other steps, data collection is a relatively tiring step in financial reporting. Balance sheet by FineReport.

Reporting 52

Reporting Dashboards KPI Metrics 52

O'Reilly on Data

JUNE 18, 2019

There has been a significant increase in our ability to build complex AI models for predictions, classifications, and various analytics tasks, and there’s an abundance of (fairly easy-to-use) tools that allow data scientists and analysts to provision complex models within days. Alex Ratner on “Creating large training data sets quickly”.

Machine Learning 259

Machine Learning Data Quality Statistics Modeling 259

Jet Global

JUNE 5, 2020

An insurance Key Performance Indicator (KPI) or metric is a measure that an insurance company uses to monitor its performance and efficiency. The quote rate measures how many quotes a staff member has been able to provide compared to the number of leads they have contacted. What Is an Insurance KPI?

Insurance 59

Insurance Metrics Reporting KPI 59

datapine

FEBRUARY 9, 2024

The process helps businesses and decision-makers measure the success of their strategies toward achieving company goals. How does Company A measure the success of each individual effort so that it can isolate strengths and weaknesses? Key performance indicators enable businesses to measure their own ability to set and achieve goals.

KPI 221

KPI Management Key Performance Indicator Measurement 221

Jet Global

JULY 8, 2020

A distribution Key Performance Indicator (KPI) or metric is a measure that a company in the distribution sector uses to monitor its performance and efficiency. These metrics help companies identify areas of operational success and failure through measuring specific quantifiable aspects of their business. What Is a Distribution KPI?

Metrics 52

Metrics Reporting KPI Key Performance Indicator 52

Jet Global

AUGUST 14, 2019

And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing. Analytics and reporting: Capturing, structuring, and storing data is good—but being able to analyze and report on it is the ultimate end goal.

Enterprise 70

Enterprise OLAP Business Intelligence Cost-Benefit 70

Occam's Razor

APRIL 8, 2013

We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. First, you figure out what you want to improve; then you create an experiment; then you run the experiment; then you measure the results and decide what to do.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

Insight

MARCH 12, 2020

In this article, I will discuss the construction of the AIgent, from data collection to model assembly. Data Collection The AIgent leverages book synopses and book metadata. The latter is any type of external data that has been attached to a book? Text synopses are ‘tokenized’ with the aid of a reference library.

Modeling 59

Modeling Metadata Publishing Sales 59

Jet Global

OCTOBER 2, 2019

And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing. Analytics and reporting: Capturing, structuring, and storing data is good—but being able to analyze and report on it is the ultimate end goal.

Enterprise 40

Enterprise OLAP Business Intelligence Cost-Benefit 40

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. Perhaps I can refer them to someone else in that case.).

Consulting 296

Consulting Risk Cost-Benefit Modeling 296

Occam's Razor

OCTOBER 14, 2014

[See step four in the process for creating your Digital Marketing and Measurement Model.]. should be 1,356,000), you've set a clear line in the sand as to what performance will be declared a success or a failure at the end of the measurement time period. Just skip the we can give you data and benchmarks on performance bits.

Key Performance Indicator 133

Key Performance Indicator Metrics Reporting Marketing 133

Occam's Razor

JULY 12, 2010

Let's go look at some tools… Measuring "Invisible Virality": Tynt. It measures how often a blog post is tweeted/retweeted. I also measure the # of Comments Per Post as a measure of how "engaging" / "valuable" people found the content to be. Or for that matter how many tools.

Analytics 96

Analytics Measurement Metrics KPI 96

Occam's Razor

JANUARY 12, 2015

Helpful post: You Are What You Measure, So Choose Your KPIs (Incentives) Wisely! ]. As we develop more sophistication to our measurement, they'll morph from being attributes of a Visitor to those of a Person. Traffic sources, like keywords, referring sites, campaigns, countries, are examples of dimensions. Definition?

Analytics 150

Analytics Slice and Dice KPI Metrics 150