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 105

Advertising Recreation/Entertainment Experimentation Enterprise 105

Smart Data Collective

AUGUST 11, 2022

Research conducted by the Harvard Business Review found that the interaction between machines and humans significantly improves firms’ performance. Although the primary goal of AI is to enhance data quality, not all data collected is of high quality. However, Ai uses algorithms that can screen and handle large data sets.

Data Quality 127

Data Quality Machine Learning Digital Transformation Big Data 127

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 122

Cost-Benefit Internet of Things Data-driven Data Lake 122

DataRobot

OCTOBER 20, 2021

Achieving that level of governance at scale requires a common understanding of AI and data concepts. Individuals interacting with AI systems should possess a baseline data literacy, especially in high-risk use cases that require human collaboration at the final decision-making stage. Data Literacy for Responsible AI.

Machine Learning 52

Machine Learning Metrics Risk Deep Learning 52

Smart Data Collective

FEBRUARY 24, 2022

The three biggest enemies to user onboarding are the lack of data analysis, data collection, and the wrong amount of information. Unfortunately, many businesses worldwide are not doing a good job collecting data and thus, fail to enhance customer relationships. Pay attention to the metrics.

Data Analytics 107

Data Analytics Analytics Visualization Optimization 107

Cloudera

APRIL 9, 2021

This blog series follows the manufacturing and operations data lifecycle stages of an electric car manufacturer – typically experienced in large, data-driven manufacturing companies. The first blog introduced a mock vehicle manufacturing company, The Electric Car Company (ECC) and focused on Data Collection.

Machine Learning 98

Machine Learning Forecasting Manufacturing Predictive Analytics 98

Smart Data Collective

JUNE 29, 2022

NLP chatbots can automate the workflow and collect valuable data through these interactions. The first basic step is to compare and test different samples of training data for representativeness. Since AI relies on high-quality and high quantity data, staying compliant with data collection laws is crucial.

Cost-Benefit 84

Cost-Benefit Predictive Analytics Finance Forecasting 84

IBM Big Data Hub

SEPTEMBER 6, 2023

AI marketing is the process of using AI capabilities like data collection, data-driven analysis, natural language processing (NLP) and machine learning (ML) to deliver customer insights and automate critical marketing decisions. What is AI marketing?

Marketing 86

Marketing Technology Advertising ROI 86

datapine

OCTOBER 14, 2020

Visualizing the data and interacting on a single screen is no longer a luxury but a business necessity. That’s why we welcome you to the world of interactive dashboards. But before we delve into the bits and pieces of our topic, let’s answer the basic questions: What is an interactive dashboard, and why you need one?

Dashboards 235

Dashboards Interactive Reporting KPI 235

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? On my test set, this approach resulted in~75–95% accuracy and ~.65

Modeling 59

Modeling Metadata Publishing Sales 59

datapine

SEPTEMBER 1, 2020

Your Chance: Want to test a market research reporting software? An effective modern means of extracting real value from your research results such as brand analysis, market research reports present and arrange data in a way that is digestible and logical in equal measures through professional online reporting software and tools.

Reporting 247

Reporting Marketing KPI Dashboards 247

Ontotext

APRIL 4, 2019

Within a large enterprise, there is a huge amount of data accumulated over the years – many decisions have been made and different methods have been tested. They have different metrics for judging whether some content is interesting or not. This is one of the main diagnostic tests. Bulgaria’s Place in the AI Race.

Recreation/Entertainment 76

Recreation/Entertainment Testing Enterprise Knowledge Discovery 76

Jet Global

MAY 15, 2020

A financial Key Performance Indicator (KPI) or metric is a quantifiable measure that a company uses to gauge its financial performance over time. Under modern day reporting standards, companies are formally obligated to present their financial data in the following statements: balance sheet, income statement, and cash flow statement.

Metrics 98

Metrics Finance Reporting KPI 98

Occam's Razor

SEPTEMBER 15, 2014

They will need two different implementations, it is quite likely that you will end up with two sets of metrics (more people focused for mobile apps, more visit focused for sites). In this post we will look mobile sites first, both data collection and analysis, and then mobile applications. Tag your mobile website.

Metrics 141

Metrics Reporting Analytics Marketing 141

datapine

AUGUST 12, 2020

In your daily business, many different aspects and ‘activities’ are constantly changing – sales trends and volume, marketing performance metrics, warehouse operational shifts, or inventory management changes. Your Chance: Want to test professional business reporting software? Let’s get started. Explore our 14-day free trial.

Reporting 297

Reporting Dashboards Visualization Cost-Benefit 297

Alation

OCTOBER 12, 2022

It is important to take into account that not all numeric data can be part of a calculation or aggregated. These terms that cannot aggregate, like a percentage, are often called non-aggregatable metrics. What Is Quantitative Data Analysis? What Is the Role of Statistics in Quantitative Data Analysis?

Statistics 52

Statistics Sales Testing Marketing 52

Occam's Razor

JULY 12, 2010

Please click on the above image for a higher resolution version , including all the other metrics.]. In the last month data was copied off one of my posts 5,616 times, with most of it being content and some of it images. This entire interaction that was completely invisible to me is now a bit more visible. Why is this cool?

Analytics 96

Analytics Measurement Metrics KPI 96

Occam's Razor

JUNE 6, 2007

Bonus: Interactive CD: Contains six podcasts, one video, two web analytics metrics definitions documents and five insightful powerpoint presentations. Experimentation & Testing (A/B, Multivariate, you name it). What ideas to test first on your site? Bonus: Interactive CD. It is a book about Web Analytics 2.0.

Analytics 60

Analytics Metrics Marketing Dashboards 60

datapine

JUNE 13, 2019

So they taste test frequently throughout the whole process. They can be of various forms: a daily sales report format will track sales metrics that are relevant on a daily basis: the number of phone calls or meetings set up by a rep, number of leads created. Instead, you want to focus more on process metrics.

Sales 264

Sales Reporting KPI B2B 264

Cloudera

AUGUST 17, 2020

In order to deliver effective results in the context of a chat interaction, we had to re-think how people search. Data Collection Request – A sentence requesting data from the customer. Next is to join this all together along with some metrics to help promote the more relevant content. Testing the Results.

Testing 83

Testing Machine Learning Interactive Metrics 83

CIO Business Intelligence

AUGUST 15, 2023

In partnership with OpenAI and Microsoft, CarMax worked to develop, test, and iterate GPT-3 natural language models aimed at achieving those results. The CarMax team also gathered, scrubbed and formatted data from thousands of vehicles to feed into the models, fine-tuning them as the project advanced.

IT 98

IT Manufacturing IoT Cost-Benefit 98

Sisense

JUNE 9, 2021

Like every other business, football has experienced rapid technological advances that generate and capture data from training and match play. And also like their counterparts in the business world, coaches are relying on metrics to guide their decision-making. Gleaning actionable intelligence from disparate data sources.

Analytics 98

Analytics Data-driven Internet of Things Measurement 98

Domino Data Lab

JUNE 23, 2019

Companies with successful ML projects are often companies that already have an experimental culture in place as well as analytics that enable them to learn from data. Ensure that product managers work on projects that matter to the business and/or are aligned to strategic company metrics. It is similar to R&D. Transcript.

Management 110

Management Machine Learning Experimentation Metrics 110

AWS Big Data

NOVEMBER 15, 2023

Each CDH dataset has three processing layers: source (raw data), prepared (transformed data in Parquet), and semantic (combined datasets). It is possible to define stages (DEV, INT, PROD) in each layer to allow structured release and test without affecting PROD.

Dashboards 95

Dashboards Analytics Metadata Optimization 95

Occam's Razor

AUGUST 13, 2012

That means: All of these metrics are off. If you want to make the smartest decisions about your budget allocation then leveraging the time tested methodology of media mix modeling (at its core powered by controlled experiments) is the only way to go. "Was the data correct?" Hopefully soon! Edward Cowell. "Was

Modeling 124

Modeling Metrics Data Quality Data-driven 124

Domino Data Lab

MAY 8, 2019

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. Here’s where I get baffled by people who use words such as agile or lean to describe process for data science.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Cloudera

JUNE 6, 2019

When a mix of batch, interactive, and data serving workloads are added to the mix, the problem becomes nearly intractable. We sometimes refer to this as splitting “dev/test” from “production” workloads, but we can generalize the approach by referring to the overall priority of the workload for the business. Cloudera Manager 6.2

Metadata 86

Metadata Data Lake Optimization Strategy 86

O'Reilly on Data

OCTOBER 18, 2022

Audits are usually more official, tracking adherence to some policy, regulation, or law, and tend to be conducted by independent third parties with varying degrees of limited interaction between auditor and auditee organizations. Data labeling is a problem. Despite flaws, start with simple metrics and clear thresholds.

Risk Management 291

Risk Management Risk Testing Measurement 291

Occam's Razor

MARCH 23, 2010

Having two tools guarantees you are going to be data collection, data processing and data reconciliation organization. Because every tool uses its own sweet metrics definitions, cookie rules, session start and end rules and so much more. Usually at least a test. Usually for free. success measures.

Analytics 118

Analytics Consulting Metrics Experimentation 118

Domino Data Lab

OCTOBER 23, 2019

You can add a Makefile command test that will run all of your notebooks by issuing. test: py.test --nbval notebooks/*.ipynb. One of the things this data set doesn’t have, however, is a single metric to rank both offensive and defensive performance in a single statistic. df = pd.DataFrame(data=records).

Statistics 59

Statistics Machine Learning Testing Modeling 59

Rocket-Powered Data Science

JULY 21, 2023

Here are four specific metrics from the report, highlighting the potentially huge enterprise system benefits coming from implementing Splunk’s observability and monitoring products and services: Four times as many leaders who implement observability strategies resolve unplanned downtime in just minutes, not hours or days.

Machine Learning 189

Machine Learning Metrics Reporting Internet of Things 189

datapine

JANUARY 31, 2022

The companies that are most successful at marketing in both B2C and B2B are using data and online BI tools to craft hyper-specific campaigns that reach out to targeted prospects with a curated message. Everything is being tested, and then the campaigns that succeed get more money put into them, while the others aren’t repeated.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Domino Data Lab

AUGUST 1, 2021

The need for interaction – complex decision making systems often rely on Human–Autonomy Teaming (HAT), where the outcome is produced by joint efforts of one or more humans and one or more autonomous agents. After forming the X and y variables, we split the data into training and test sets. show_in_notebook().

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

IBM Big Data Hub

OCTOBER 17, 2023

Many solutions now move beyond traditional application performance monitoring (APM) tools toward observability—“ performance data collection and analysis technology better suited to the complexity of modern, distributed cloud-native applications.” Increasingly, the application monitoring field is evolving.

Metrics 78

Metrics Optimization Software Measurement 78

datapine

APRIL 16, 2019

While sometimes it’s okay to follow your instincts, the vast majority of your business-based decisions should be backed by metrics, facts, or figures related to your aims, goals, or initiatives that can ensure a stable backbone to your management reports and business operations. 3) Gather data now. 6) Analyze and understand.

Data-driven 287

Data-driven Dashboards Visualization Cost-Benefit 287

Alation

AUGUST 26, 2021

Data intelligence first emerged to support search & discovery, largely in service of analyst productivity. For years, analysts in enterprises had struggled to find the data they needed to build reports. This problem was only exacerbated by explosive growth in data collection and volume. Data lineage features.

Metadata 64

Metadata Data Governance Dashboards Software 64

Jet Global

MAY 1, 2023

that gathers data from many sources. As rich, data-driven user experiences are increasingly intertwined with our daily lives, end users are demanding new standards for how they interact with their business data. It’s all about context. BI is a set of independent systems (technologies, processes, people, etc.)

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52